CN118733391A - Process monitoring method, process monitoring device, computing device and computer readable storage medium - Google Patents

Abstract

The embodiment of the specification provides a process monitoring method, a process monitoring device, a computing device and a computer readable storage medium, wherein the process monitoring method comprises the following steps: acquiring the starting time of a target process; judging whether the target process runs overtime or not based on the starting time; if yes, identifying the target process as a temporary process or a long-acting process; under the condition that the target process is a temporary process, determining that the target process is abnormal in operation; and under the condition that the target process is a long-acting process, inquiring the update time of the process log of the target process, and determining whether the target process is abnormal in operation or not based on the update time. The automatic process monitoring is realized, the timeliness of the process monitoring is improved, the more refined monitoring is realized, the possibility of misjudgment is reduced, and the effectiveness and the accuracy of the process monitoring are improved.

Description

Process monitoring method, process monitoring device, computing device and computer-readable storage medium

Technical Field

The embodiments of this specification relate to the technical field of software system management, and in particular to a process monitoring method, a process monitoring device, a computing device, and a computer-readable storage medium.

Background Art

With the development of automation software systems, production systems are constructed through multiple automation software systems. Multiple systems have their own software solutions, installed on different servers or workstations, running on multiple systems and with different interfaces and middleware. This diversity brings advanced automation production capabilities, but also puts higher requirements on the operation and maintenance of production systems.

At present, interactive processes are the core components of production systems. They are responsible for information exchange and coordination between different automation software systems, services and even hardware devices, ensuring the smooth transmission of data and accurate execution of instructions.

However, when communication is interrupted due to network or terminal problems, the interactive process will run abnormally and be in a dead state. This dead state is difficult to be discovered quickly because it is no longer running, causing the entire production system to become abnormal, bringing huge risks. Therefore, an automatic, instant, and effective process monitoring method is urgently needed.

Summary of the invention

In view of this, an embodiment of the present specification provides a process monitoring method. One or more embodiments of the present specification also relate to a process monitoring device, a computing device, a computer-readable storage medium and a computer program product to solve the technical defects existing in the prior art.

According to a first aspect of an embodiment of this specification, a process monitoring method is provided, including:

Get the start time of the target process;

Based on the startup time, determine whether the target process has timed out;

If yes, identify the target process as a temporary process or a long-term process;

When the target process is a temporary process, determining that the target process has an abnormal operation;

In the case where the target process is a long-term process, the update time of the process log of the target process is queried, and based on the update time, it is determined whether the target process has an operational abnormality.

According to a second aspect of an embodiment of this specification, a process monitoring device is provided, including:

A first acquisition module is configured to acquire the start time of the target process;

The operation timeout judgment module is configured to judge whether the target process has timed out based on the startup time;

A classification identification module is configured to identify the target process as a temporary process or a long-term process;

A first determination module is configured to determine that a target process has an abnormal operation when the target process is a temporary process;

The second determination module is configured to query the update time of the process log of the target process when the target process is a long-term process, and determine whether the target process has an abnormal operation based on the update time.

According to a third aspect of an embodiment of this specification, a computing device is provided, including:

Memory and processor;

The memory is used to store computer programs/instructions, and the processor is used to execute the computer programs/instructions. When the computer programs/instructions are executed by the processor, the steps of the above-mentioned process monitoring method are implemented.

According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores a computer program/instruction, and when the computer program/instruction is executed by a processor, the steps of the above-mentioned process monitoring method are implemented.

According to a fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program/instruction, which implements the steps of the above-mentioned process monitoring method when executed by a processor.

In one embodiment of the present specification, the start time of the target process is obtained; based on the start time, it is determined whether the target process has timed out; if so, the target process is identified as a temporary process or a long-term process; if the target process is a temporary process, it is determined that the target process has an abnormal operation; if the target process is a long-term process, the update time of the process log of the target process is queried, and based on the update time, it is determined whether the target process has an abnormal operation. The entire process monitoring follows specific monitoring rules to achieve automated process monitoring. By monitoring the start time of the target process and the update time of the process log, it is identified whether the target interactive process is running abnormally, thereby improving the timeliness of process monitoring. By distinguishing between temporary processes and long-term processes, more refined monitoring is achieved, the possibility of misjudgment is reduced, and the effectiveness and accuracy of process monitoring are improved.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a process monitoring method provided by one embodiment of the present specification;

FIG2 is a flow chart of a process monitoring method provided by an embodiment of the present specification;

FIG3 is a process flow chart of a process monitoring method applied to a vehicle and powertrain production system provided by an embodiment of this specification;

FIG4 is a schematic diagram of the structure of a process monitoring device provided by an embodiment of the present specification;

FIG. 5 is a structural block diagram of a computing device provided by an embodiment of the present specification.

DETAILED DESCRIPTION

Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and/or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

First, the terms involved in one or more embodiments of this specification are explained.

Production system: Information technology system for large-scale production operations, covering two core areas: production control and product quality management. Specific examples include, but are not limited to, control systems for parts casting, machining, and assembly processes, as well as corresponding quality control systems, which are applied to the entire chain from parts production to finished product assembly. With the expansion of production bases, the introduction of new product lines, and the deep integration of information technology and data analysis technology, the types and complexity of such systems are growing rapidly. These systems work together to support modern, intelligent, efficient and low-cost production operations.

Production system stability management: Based on the core role of the aforementioned production system in advanced production, system stability has become a key factor in determining production efficiency. Therefore, for the production system, whether it is management process, technical standard formulation, software development, or operation and maintenance practice, strict specifications must be followed to ensure the high stability and reliability of the system.

Software system: specifically refers to various application programs running in a software system environment. Software systems include but are not limited to: Linux systems, various embedded software systems such as real-time software systems (Real Time Operating System, referred to as RTOS), Vx Works, etc.

Interactive processes: In multiple automated software systems, interactive processes are core components of production systems. They are responsible for information exchange and coordination between different systems, services, and even hardware devices, ensuring smooth data transmission and accurate execution of instructions.

Process deadlock: Due to network communication failure or end system abnormality, the interactive process may enter a dead state. At this time, the interactive process can neither continue to execute the predetermined logic nor update the log record, but remains stagnant at a fixed interactive link, and the occupied system resources cannot be released. Although the interactive process still exists from the system management level, it has actually lost its function.

At present, once a failure occurs in a complex production system, it may affect the automated production capacity at the least, or even affect the safety of the entire production or the production system itself. Therefore, ensuring that all automated software systems in the production system can run stably has become a very challenging task.

When the interactive process is dead, it is difficult to find such problems from the software system level. The process in a dead state is called and managed by the software system like other normal processes. At the same time, it also maintains its own allocated resources (such as CPU, memory, etc.). It is difficult to find that the interactive process is in a dead state from the outside. Moreover, the dead state may be different. Some are trapped in a logical dead loop, and some are stuck in a certain logical environment and no longer continue to execute subsequent tasks.

However, process deadlock can have very serious consequences for production. For example, if the interactive process is dead and no longer interacts with the Programmable Logic Controller (PLC) on the production line, the machines and equipment on the production line will stop working due to lack of input, resulting in a serious production stoppage accident. The usual solution to this type of production stoppage problem is: after the production line stops, the accident phenomenon is reported to the operation and maintenance personnel, who check the interactive processes one by one according to the accident phenomenon to locate the interactive process in a dead state. Restart or perform some technical operations to restore the fault.

However, this solution is time-consuming and has serious impacts. Therefore, an automatic, immediate and effective process monitoring method is urgently needed.

Based on this, a process monitoring method is provided in this specification, and this specification also relates to a process monitoring device, a computing device, a computer-readable storage medium and a computer program product, which are described in detail one by one in the following embodiments.

Referring to FIG. 1 , FIG. 1 shows a flow chart of a process monitoring method provided by an embodiment of the present specification, including the following specific steps:

Step 102: Get the start time of the target process.

The embodiments of this specification are applied to a process monitoring functional unit in a production system, which includes multiple automation software systems and/or multiple terminals. The process monitoring functional unit can be a component integrated within the automation software system, or can be an independently deployed service running independently of the automation software system. The process monitoring functional unit collects and analyzes process status information on each automation software system and terminal across systems to achieve unified monitoring of interactive processes in the production system.

The target process is the interactive process being monitored during the current process monitoring process. The target process can be randomly selected or selected according to its priority to ensure that the most critical or high-risk target process in the system is monitored first. This is not limited here. For example, in an automobile production system, the interactive process responsible for controlling the painting robot is the target process. Whether it runs abnormally directly affects the quality and production progress of automobile painting.

The start time of the target process is the timestamp when the target process is started by the software system and begins to execute. The start time includes but is not limited to: the start date and the start time. The software system records the start time of the target process and preliminarily determines whether the target process has a running timeout in step 104 as a basic indicator for determining whether the target process is in a zombie state. For example, the start time of the target process responsible for controlling the painting robot is 2024-06-218:00:00.

Get the start time of the target process, specifically: get the start time of the target process based on the process ID of the target process. Further, an optional way is: get the start time of the target process based on the process ID of the target process from the log of the production system, another optional way is: get the start time of the target process based on the process ID of the target process through a command line tool, for example, in a Linux system, use the ps command with the -o start option to get the start time of the process: ps -o | start -p %V(%PROG_ID %V | awk '{if(NR==2){print$0}}'.

For example, in an automobile production system, a process monitoring functional unit is built in. Currently, the interactive process of controlling the assembly robot is being monitored. Through the command line tool, based on the process identifier "Assembly_Line" of the target process, the start time of the target process is obtained: 2024-06-218:00:00.

By obtaining the start time of the target process, time data support is provided for subsequent judgment of whether the target process has timed out.

Step 104: Based on the start time, determine whether the target process has timed out.

It should be noted that the interactive processes between the automation software systems of the production system are divided into temporary processes and long-term processes. Temporary processes only run for a short time and stop running once the interaction is completed. Long-term processes need to run for a long time. Judging whether the target process has timed out based on the start time cannot be directly used to judge whether the target process is running abnormally, but only as a reference standard.

Based on the startup time, it is determined whether the target process has timed out. One optional method is to perform a fixed threshold timeout judgment based on the startup time to determine whether the target process has timed out. For example, a reasonable timeout threshold is preset based on the expected running time of the process and/or production requirements. Another optional method is to perform a dynamic threshold timeout judgment based on the startup time to determine whether the target process has timed out. Specifically, the timeout threshold is dynamically adjusted based on historical running data, system load, and even external environmental factors (such as network conditions). For example, a machine learning algorithm is used to analyze the historical running time of the process and dynamically set a timeout threshold, or a timeout threshold is dynamically set based on the current resource usage of the production system (such as CPU load, memory usage).

Exemplarily, based on the start time 2024-06-218:00:00, a fixed threshold timeout judgment is performed to determine whether the target process has timed out.

Based on the startup time, it determines whether the target process has timed out, completes the preliminary judgment of the process running time, improves the timeliness of process monitoring, and provides support for subsequent more refined monitoring.

Step 106: If yes, identify the target process as a temporary process or a long-term process.

A temporary process is a process created in an automated software system to complete a short-term task. Once the short-term task is completed or the preset conditions are met, the temporary process will automatically stop running. Temporary processes are characterized by a short life cycle and usually do not stay in the system for a long time. The purpose is to efficiently utilize system resources and avoid unnecessary resource occupation. For example, in an automobile production system, a temporary process is a control process responsible for making special configuration adjustments to a specific batch of vehicles. Once the configuration adjustment of the batch of vehicles is completed, the process will immediately end.

A long-term process is a process created in an automated software system to complete a long-term task. It continuously plays the role of supporting the core functions of the system in the automated software system and will remain in operation unless it encounters a specific exception or is manually stopped. Long-term processes are characterized by a long life cycle and will remain in the system for a long time to ensure their long-term reliability and efficiency. For example, in an automobile production system, the interactive process responsible for the continuous replenishment of parts is a long-term process that needs to run continuously to ensure the smooth operation of the production line.

One optional way to identify a target process as a temporary process or a long-term process is to identify the target process as a temporary process or a long-term process based on a process type identifier of the target process. Another optional way is to identify the target process as a temporary process or a long-term process based on system resource allocation and dependencies, for example, based on the target process's occupation pattern of system resources (such as CPU, memory), and its dependencies with other system components.

Exemplarily, based on the process type identifier "IF_REF_LOG" of the target process, it is identified that the target process is a temporary process or a long-term process.

If so, identify the target process as a temporary process or a long-term process, distinguish the target process, and provide support for subsequent more refined monitoring.

Step 108: When the target process is a temporary process, it is determined that an operation abnormality occurs in the target process.

It should be noted that the life cycle of a temporary process is short. If the process times out, it can be directly determined that the target process has an abnormal operation.

Step 110: When the target process is a long-term process, query the update time of the process log of the target process, and determine whether the target process has an abnormal operation based on the update time.

The process log of the target process is a file that records the operation of the target process, including key events, state changes, error messages, warnings, and other information during the operation of the target process. The information recorded in the process log includes, but is not limited to: start time, end time, key steps in the execution process, and resource usage (such as CPU, memory, and disk I/O). The log format can be plain text, JSON, XML, and other forms. For example, in an automobile production system, the process log of a long-term process that controls a welding robot records: start time, end time, welding parameters used, whether welding was successfully completed, and any welding failures.

The update time of the process log is the timestamp of the last message recorded in the process log, which marks the moment of the target process's most recent activity or state change. If the process log of a long-term process has not been updated for a long time, it means that the long-term process has stopped processing new tasks and is in a dead state. For example, the last message in the process log of the interactive process responsible for continuous replenishment of parts is timestamp 2024-06-217:13:00.

Based on the update time, determine whether the target process has an abnormal operation. One optional method is: based on the update time, perform a fixed threshold timeout judgment to determine whether the target process has an abnormal operation. For example, preset a reasonable timeout threshold based on the process characteristics and/or production requirements of the long-term process. Another optional method is: based on the update time, perform a dynamic threshold timeout judgment to determine whether the target process has an abnormal operation. Specifically, dynamically adjust the timeout threshold based on historical operation data, system load, and even external environmental factors (such as network conditions). For example, use a machine learning algorithm to analyze the historical running time of a long-term process and dynamically set a timeout threshold, or dynamically set a timeout threshold based on the current resource usage of the production system (such as CPU load, memory usage).

Exemplarily, when the target process is a long-term process, the update time 2024-06-217:13:00 of the process log of the target process is queried, and based on the update time, it is determined that the target process has an operational abnormality.

In the embodiments of this specification, the entire process monitoring follows specific monitoring rules to achieve automated process monitoring. By monitoring the start time of the target process and the update time of the process log, it is possible to identify whether the target interactive process is running abnormally, thereby improving the timeliness of process monitoring. By distinguishing between temporary processes and long-term processes, more refined monitoring is achieved, reducing the possibility of misjudgment and improving the effectiveness and accuracy of process monitoring.

In an optional embodiment of the present specification, before step 104, the following specific steps are also included:

Get the preset running time of the target process;

Correspondingly, step 104 includes the following specific steps:

Determine the running time of the target process based on the start time and the current time;

Compare the running time with the preset running time to determine whether the target process has timed out.

The preset running time of the target process is a preset running time threshold for the target process. Once the threshold is exceeded, the target process is deemed to have timed out. The preset running time of the target process is set according to the expected running time of the target process and/or production requirements. For example, the preset running time RUNNING_TIME of the target process is set to 3000ms.

The current time is the instant timestamp of the current process monitoring process, which represents the exact moment when the monitoring operation actually occurs and is a dynamic reference point for measuring whether the target process has timed out. For example, the current time is 2024-06-218:00:05.

The running time of the target process is the duration from the start of the target process to the current time. It is the direct basis for evaluating whether the target process has timed out. If the running time is greater than the preset running time, it is determined that the target process has timed out. More refined monitoring is required to determine whether the target process has run abnormally.

Based on the start time and the current time, determine the running length of the target process. An optional command line is as follows: echo $(($(date+%s-d“%V(CUR_TIME_F1%V)%”)-$(date-d‘%V(%PS_START_TIME%V)%’+%s))).

To compare the running time with the expected running time, an optional command line is as follows: PS_RUN_SEC>RUNNING_TIME?.

Exemplarily, the preset running time (3000ms) of the target process is obtained, and based on the start time 2024-06-218:00:00 and the current time 2024-06-218:00:05, the running time of the target process is determined to be 5000ms. The running time is greater than the preset running time, and it is determined that the target process has timed out.

In the embodiments of this specification, a fixed threshold method is used to complete a more accurate preliminary judgment of the process running time, further improve the timeliness of process monitoring, and provide support for subsequent more refined monitoring.

In an optional embodiment of the present specification, before step 106, the following specific steps are also included:

Get the process type identifier of the target process;

Correspondingly, step 106 includes the following specific steps:

If so, based on the process type identifier, identify the target process as a temporary process or a long-term process.

The process type identifier of the target process is a label symbol used to distinguish the process type of the target process, including: a process type identifier of a temporary process or a process type identifier of a long-term process. Since a long-term process needs to query the process log, the process type identifier can also be an identifier of whether the process log needs to be queried. For example, the process type identifier of a temporary process is "IF_REF_LOG=0", indicating that the process log does not need to be queried, and the process type identifier of a long-term process is "IF_REF_LOG=1", indicating that the process log needs to be queried.

Based on the process type identifier, the target process is identified as a temporary process or a long-term process. An optional command line is as follows: IF_REF_LOG=1?.

Exemplarily, the process type identifier "IF_REF_LOG=1" of the target process is obtained, and based on the process type identifier, the target process is identified as a long-term process.

In the embodiments of this specification, the target process is more accurately distinguished based on the process type identifier, providing support for subsequent more refined monitoring.

In an optional embodiment of the present specification, before determining whether the target process has an abnormal operation based on the update time in step 110, the following specific steps are also included:

Get the preset stop update duration of the process log of the target process;

Correspondingly, based on the update time, determining whether the target process has an abnormal operation includes the following specific steps:

Based on the update time and current time, determine the duration for which the process log will stop updating;

Compare the stop update duration with the preset stop update duration;

When the stop-update time is longer than the preset stop-update time, it is determined that the target process runs abnormally.

The preset stop update time of the process log of the target process is a preset stop update time threshold for the process log of the target process. Once the threshold is exceeded, it can be determined that the long-term process has an abnormal operation. The preset stop update time of the process log of the target process is based on the process characteristics and/or production requirements of the long-term process. For example, the preset stop update time of the process log of the target process LOG_STOP_TIME is set to 120000ms.

The current time is the instant timestamp of the current process monitoring process, which represents the exact moment when the monitoring operation actually occurs and is a dynamic reference point for measuring whether the target process has timed out. For example, the current time is 2024-06-218:33:00.

The stop update duration of the process log is the duration from the update time of the process log to the current time. It is the direct basis for evaluating whether a long-term process has an abnormal operation. If the stop update duration is greater than the preset stop update duration, it is determined that the target process has an abnormal operation.

Get the preset stop update time of the process log of the target process. An optional command line is as follows: echo $(($(date+%s-d“%V(CUR_TIME_F1%V)%”)-$(date-d‘%V(%PS_START_TIME%V)%’+%s))).

Based on the update time and the current time, determine the duration for which the process log will stop updating. An optional command line is as follows: echo $(($(date+%s-d“%V(CUR_TIME_F1%V)%”)-$(date-d‘%V(%LOG_STILL_TIME%V)%’+%s))).

Compare the stop update time with the preset stop update time. An optional command line is as follows: LOG_STILL_SEC>LOG_STOP_TIME?.

Exemplarily, the preset stop update duration (120000ms) of the process log of the target process is obtained, and based on the update time 2024-06-217:13:00 and the current time 2024-06-218:00:05, the stop update duration of the process log is determined to be 282500ms, and the stop update duration is compared with the preset stop update duration. If the stop update duration is greater than the preset stop update duration, it is determined that the target process has an abnormal operation.

In the embodiments of this specification, a fixed threshold method is adopted to achieve more accurate and refined monitoring, further reduce the possibility of misjudgment, and further improve the effectiveness and accuracy of process monitoring.

In an optional embodiment of the present specification, when the stop update time is longer than the preset stop update time, after determining that the target process has run abnormally, the following specific steps are also included:

Stop the target process and record the running information of the target process;

Feedback operation information to the front end.

In the embodiment of this specification, when the stop update time is longer than the preset stop update time, after determining that the target process has an abnormal operation, it is necessary to automatically feedback the monitoring results so that the front end can process it in time to avoid abnormalities in the overall production system and eliminate risks.

The operation information of the target process is the operation status information of the target process collected during the current process monitoring process, including but not limited to: normal operation information of the target process and abnormal operation information of the target process. For example, in the automobile production system, the operation information of a long-term process responsible for monitoring the welding robot includes: the start time is 2024-06-21 8:00:00, the cumulative running time reaches 30 hours, the average CPU occupancy rate is 15%, the peak memory usage is 2GB, an error log of a failed communication with the PLC is recorded at 2024-06-22 10:15:00, and the record of the last successful execution of the welding task by the process is found at 2024-06-22 11:00:00.

The front end is the front end of the process monitoring functional unit in the production system, which can be a monitoring dashboard, a web interface or any graphical user interface, which displays the running information of the target process, so that the operation and maintenance personnel or management personnel can intuitively view the process monitoring results and handle them in time.

Feedback of the operation information to the front end: one optional way is to feed back the operation information to the front end via email, another optional way is to feed back the operation information to the front end via instant messaging, and yet another optional way is to feed back the operation information to the front end via charts.

Exemplarily, the target process is stopped, and abnormal operation information of the target process is recorded, and the abnormal operation information is fed back to the front-end operation and maintenance personnel in the form of emails.

In the embodiments of this specification, when a long-term process has an operational abnormality, operational information is fed back to the front end in a timely manner through an interactive form, thereby improving the abnormal response speed and system security.

In an optional embodiment of the present specification, after step 108, the following specific steps are also included:

Stop the target process and record the running information of the target process;

Feedback operation information to the front end.

In the embodiment of this specification, when the target process is a temporary process, after determining that the target process has an abnormal operation, it is necessary to automatically feedback the monitoring results so that the front end can process it in time to avoid abnormalities in the overall production system and eliminate risks.

Please refer to the above embodiments for the specific details, which will not be described again here.

In the embodiments of this specification, when a temporary process runs abnormally, operation information is fed back to the front end in a timely manner through an interactive form, thereby improving the abnormal response speed and system security.

In an optional embodiment of the present specification, after querying the update time of the process log of the target process in step 110, the following specific steps are also included:

If the target process is not found, stop running the target process and record the running information of the target process;

Feedback operation information to the front end.

In the embodiments of this specification, if the update time of the process log of the target process is not queried, it is characterized that the long-term process can be treated as a temporary process, that is, it is directly determined that an operation abnormality has occurred. As shown in the above embodiment, when the target process is a temporary process, after determining that an operation abnormality has occurred in the target process, it is necessary to automatically feedback the monitoring results so that the front end can process it in a timely manner, avoid abnormalities in the overall production system in a timely manner, and eliminate risks.

Please refer to the above embodiments for the specific details, which will not be described again here.

In the embodiment of the present specification, through the interactive form, when the update time of the process log of the long-term process is not queried, the operation information is promptly fed back to the front end, thereby improving the abnormal response speed and system security.

In an optional embodiment of the present specification, before step 102, the following specific steps are also included:

Obtain configuration information of multiple preset processes to be monitored;

Storing configuration information of multiple processes to be monitored into a monitoring process set;

Determine whether the monitoring process set is empty;

If not, obtain the configuration information of the target process from the monitoring process set, and delete the configuration information of the target process in the monitoring process set;

Parsing the configuration information to obtain a process identifier and configuration parameters of the target process, wherein the configuration parameters include at least one of a preset running time, a process type identifier, and a preset stop updating time of the process log of the target process;

Put the process ID into the process monitoring queue.

It should be noted that process monitoring is implemented based on process monitoring queues, such as job, crontab, etc. Multiple processes to be monitored are put into the process monitoring queue in advance, and the configuration information of the preset multiple processes to be monitored needs to be obtained, and then the processes are monitored one by one during the queue execution process.

The processes to be monitored are interactive processes that need to be monitored. For example, in an automobile production system, the processes to be monitored include the process responsible for controlling the painting robot, the long-term process for parts replenishment, and the temporary process for adjusting the configuration of a specific batch of cars. The stable operation of these processes is directly related to production efficiency and product quality.

The configuration information of the process to be monitored is the preset parameters and characteristic description of the process to be monitored, which is used to guide the process monitoring functional unit to perform process monitoring. The configuration information of the process to be monitored includes but is not limited to: the configuration information index of the process to be monitored, the description information of the process to be monitored, the valid identifier of the configuration information of the process to be monitored, the process identifier of the process to be monitored, the preset running time of the process to be monitored, the process type identifier of the process to be monitored, the process log identifier of the process to be monitored, and the preset stop updating time of the process log of the process to be monitored.

Configuration information of the target process The preset parameters and characteristic description of the target process are used to guide the process monitoring function unit to perform process monitoring on the target process. The configuration information of the target process includes but is not limited to: the configuration information index of the target process, the description information of the target process, the valid identifier of the configuration information of the target process, the process identifier of the target process, the preset running time of the target process, the process type identifier of the target process, the process log identifier of the target process, and the preset stop updating time of the process log of the target process.

The monitoring process set is a storage structure for storing the configuration information of the process to be monitored. This set contains the configuration information of all the processes to be monitored in the system, ensuring that the process monitoring functional unit can monitor and manage these processes in an organized and planned manner. Once the set is empty, it is considered that the monitoring of the process to be monitored is completed and the monitoring ends.

Configuration parameters are predefined variables and thresholds set for interactive processes. These parameters are pre-set according to the characteristics of the process, expected behavior, and production requirements to ensure that the monitoring strategy is both accurate and adaptable. The core role of configuration parameters is to provide decision-making basis for the process monitoring functional unit, so that it can automatically determine whether the process is running normally, when to trigger abnormal alarms, and how to deal with different types of abnormal situations. By flexibly configuring these parameters, the process monitoring functional unit can better adapt to diverse production environments and changing production needs, and improve monitoring efficiency and accuracy. Configuration parameters include at least one of the preset running time, process type identification, and preset stop update time of the process log of the target process.

Taking temporary processes and long-term processes as examples, Table 1 shows configuration information of a process to be monitored:

Table 1

The configuration information of multiple processes to be monitored is stored in the monitoring process set. An optional command line is as follows: SelectMON_PROG,RUNNING_TIME,IF_REF_LOG,LOG_FILE,LOG_STOP_TIMEfromoc_prog_kill_tw hereif_valid=1orderbypk_id.

Put the process ID into the process monitoring queue. An optional command line is as follows: ps-if|grep %V(%MON_PROG%V)%|grep-vgrep|awk ‘{print$2}’.

Exemplarily, obtain the configuration information of 1000 preset processes to be monitored (configuration information index of the process to be monitored, description information of the process to be monitored, valid identifier of the configuration information of the process to be monitored, process identifier of the process to be monitored, preset running time of the process to be monitored, process type identifier of the process to be monitored, process log identifier of the process to be monitored, preset stop updating time of the process log of the process to be monitored), store the configuration information of the 1000 processes to be monitored into the monitoring process set, determine whether the monitoring process set is empty, and if not, obtain the interactive process of controlling the assembly robot from the monitoring process set. The configuration information of the process (configuration information index of the target process, description information of the target process, valid identifier of the configuration information of the target process, process identifier of the target process, preset running time of the target process, process type identifier of the target process, process log identifier of the target process, preset stop updating time of the process log of the target process), and delete the configuration information of the target process in the monitoring process set, parse the configuration information, obtain the process identifier of the target process, preset running time, process type identifier and preset stop updating time of the process log of the target process, and put the process identifier of the target process into the process monitoring queue.

In the embodiments of this specification, through preset configurations and orderly monitoring queues, automatic and efficient management and monitoring of various interactive processes are achieved, ensuring timely detection and handling of anomalies, thereby improving the stability and operation and maintenance efficiency of the production system.

In an optional embodiment of the present specification, after the process identifier is placed into the process monitoring queue, the following specific steps are also included:

From the process monitoring queue, check whether the process ID of the target process is recorded;

Obtaining the start time of the target process includes the following specific steps:

If yes, get the start time of the target process.

It should be noted that before step 102, it is necessary to query whether the process ID of the target process is recorded in the process monitoring queue. If not, it indicates that the target process is not running and does not need to be monitored. Only when the target process is running will steps 102-110 be triggered.

In the embodiments of the present specification, by checking the existence of the process identifier in the process monitoring queue, invalid monitoring of the target process that is not running is effectively avoided, the utilization of system resources is optimized, and the pertinence and efficiency of the monitoring process are improved.

In an optional embodiment of the present specification, after querying whether the process identifier of the target process is recorded in the process monitoring queue, the following specific steps are also included:

If not, update the target process and return to the step of determining whether the monitored process set is empty.

It should be noted that the embodiment of this specification is for processing when the process ID of the target process is not recorded in the query process monitoring queue, the target process is updated, and the execution is returned to determine whether the monitoring process set is empty, and the process monitoring of all processes to be monitored is completed in a loop.

In the embodiments of the present specification, by checking the existence of the process identifier in the process monitoring queue, invalid monitoring of the target process that is not running is effectively avoided. At the same time, process monitoring of all processes to be monitored is executed cyclically, thereby optimizing system resource utilization and improving the pertinence and efficiency of the monitoring process.

In an optional embodiment of the present specification, after step 104, the following specific steps are also included:

If not, update the target process and return to the step of determining whether the monitored process set is empty.

It should be noted that after step 104, if it is determined that the target process has not timed out, the target process is updated, and the process returns to determine whether the monitored process set is empty, and the process monitoring of all processes to be monitored is completed in a loop.

For the specific contents of the embodiments of this specification, please refer to the above embodiments of the specification, which will not be repeated here.

In the embodiment of the present specification, after determining that the target process has not timed out, process monitoring of all processes to be monitored is executed cyclically, thereby improving the automation level of process monitoring and further improving the timeliness of process monitoring.

In an optional embodiment of the present specification, determining whether a target process has an abnormal operation based on the update time in step 110 includes the following specific steps:

Based on the update time and current time, determine the duration for which the process log will stop updating;

Compare the stop update duration with the preset stop update duration;

When the stop updating time is not greater than the preset stop updating time, the target process is updated, and the process returns to the step of determining whether the monitoring process set is empty.

It should be noted that in step 110, when the stop update time is not greater than the preset stop update time, it is determined that the target process has no operating abnormality, the target process is updated, and the execution is returned to determine whether the monitored process set is empty, and the process monitoring of all processes to be monitored is completed in a loop.

For the specific contents of the embodiments of this specification, please refer to the above embodiments of the specification, which will not be repeated here.

In the embodiment of the present specification, after determining that the target process has not run abnormally, the process monitoring of all processes to be monitored is executed cyclically, thereby improving the automation level of the process monitoring and further improving the timeliness of the process monitoring.

FIG. 2 shows a schematic flow chart of a process monitoring method provided by an embodiment of the present specification, as shown in FIG. 2 :

start;

Collect necessary information (such as current time) CUR_TIME_F1, DATE_STR;

Read the configuration information of multiple preset processes to be monitored, and store the configuration information of multiple processes to be monitored into the monitoring process set: Select MON_PROG,RUNNING_TIME,IF_REF_LOG,LOG_FILE,LOG_STOP_TIME from oc_prog_kill_t where if_valid＝1order by pk_id;

Determine whether the monitoring process set is empty;

If so, end;

If not, obtain the configuration information of the target process from the monitoring process set, put the configuration information of the target process into variable C, and delete the configuration information of the target process in the monitoring process set;

Parse the configuration information from variable C to obtain the process ID, preset running time, process type ID, and preset stop update time of the process log of the target process: MON_PROG, RUNNING_TIME, IF_REF_LOG, LOG_FILE, LOG_STOP_TIME;

Execute the command to obtain the process ID of the target process and put the process ID into the process monitoring queue: ps-if|grep %V(%MON_PROG%V)%|grep-v grep|awk'{print$2}';

From the process monitoring queue, check whether the process ID of the target process is recorded;

There is no record, the target process is not running, and the process returns to the step of determining whether the monitored process set is empty;

Records are, get the start time of the target process, and put the start time into the variable PS_START_TIME: ps -o | start -p %V (%PROG_ID %V | awk '{if (NR == 2) {print $0}}';

Convert the start time to an absolute value and, based on the start time and the current time, determine how long the target process has been running: echo $(($(date+%s-d“%V(CUR_TIME_F1%V)%”)-$(date-d‘%V(%PS_START_TIME%V)%’+%s)));

Compare the running time with the preset running time: PS_RUN_SEC>RUNNING_TIME?;

If it is less, return to the step of determining whether the monitoring process set is empty;

If it is greater, based on the process type identifier, identify the target process as a temporary process or a long-term process: IF_REF_LOG = 1?;

If it is a temporary process, stop running the target process: Kill-9%(%PROG_ID%V)%;

Record abnormal operation information of the target process;

Send the abnormal operation information to the front-end operation and maintenance personnel in the form of an email, and return to execute the step of determining whether the monitoring process set is empty;

If it is a long-term process, query the update time of the process log of the target process and put it into the variable LOG_STILL_TIME: stat %V{%FILE_LOG%V}%|grep^Modify|awk'{printsubstr{$0,9,19}}';

Determine whether the variable LOG_STILL_TIME is empty;

If it is empty, the process log does not exist, it is regarded as not referring to the process log, and the target process is stopped: Kill-9%(%PRO G_ID%V)%;

Record abnormal operation information of the target process;

Send the abnormal operation information to the front-end operation and maintenance personnel in the form of an email, and return to execute the step of determining whether the monitoring process set is empty;

If it is not empty, based on the update time and current time, determine the duration of stopping updating of the process log and save it to the variable LOG_STILL_SEC: echo $(($(date+%s-d“%V(CUR_TIME_F1%V)%”)-$(date-d‘%V(%LOG_STILL_TIME%V)%’+%s)));

Compare the stop update duration with the preset stop update duration: LOG_STILL_SEC>LOG_STOP_TIME?;

If it is less, return to the step of determining whether the monitoring process set is empty;

If it is greater, stop running the target process: Kill-9%(%PROG_ID%V)%;

Record abnormal operation information of the target process;

The abnormal operation information is sent to the front-end operation and maintenance personnel in the form of an email, and the step of determining whether the monitoring process set is empty is returned.

The following is a further description of the process monitoring method provided in this specification, taking the application of the process monitoring method in a complete vehicle and powertrain production system as an example in conjunction with FIG3. Among them, FIG3 shows a processing flow chart of a process monitoring method applied to a complete vehicle and powertrain production system provided by an embodiment of this specification, including the following specific steps:

Step 302: Obtain preset configuration information of multiple processes to be monitored in the vehicle and powertrain production system.

Step 304: Store the configuration information of the multiple processes to be monitored into the monitoring process set.

Step 306: Determine whether the monitoring process set is empty.

Step 308: If not, obtain the configuration information of the target process from the monitoring process set, and delete the configuration information of the target process in the monitoring process set.

Step 310: Parse the configuration information to obtain the process identifier and configuration parameters of the target process.

Step 312: Put the process ID into the process monitoring queue.

Step 314: Query the process monitoring queue to see whether the process ID of the target process is recorded.

Step 316: If not, update the target process and return to the step of determining whether the monitoring process set is empty.

Step 318: If yes, obtain the start time of the target process.

Step 320: Based on the start time and the current time, determine the running time of the target process, compare the running time with the preset running time, and determine whether the target process has timed out.

Step 322: If not, update the target process and return to the step of determining whether the monitoring process set is empty.

Step 324: If yes, identify the target process as a temporary process or a long-term process based on the process type identifier.

Step 326: When the target process is a temporary process, determine that the target process has an operational abnormality, stop the target process, record the operational information of the target process, and feed the operational information back to the front end.

Step 328: When the target process is a long-term process, query the update time of the process log of the target process.

Step 330: Based on the update time and the current time, determine the duration for stopping updating of the process log.

Step 332: Compare the stop-update duration with the preset stop-update duration.

Step 334: When the stop-update duration is not greater than the preset stop-update duration, the target process is updated, and the process returns to the step of determining whether the monitoring process set is empty.

Step 336: When the stop-update duration is longer than the preset stop-update duration, it is determined that the target process has an operational abnormality, the target process is stopped, and the operational information of the target process is recorded and fed back to the front end.

In the embodiments of this specification, the interactive processes in the vehicle and powertrain production system are monitored, and the entire process monitoring follows specific monitoring rules to achieve automated process monitoring. By monitoring the start time of the target process and the update time of the process log, it is possible to identify whether the target interactive process is running abnormally, thereby improving the timeliness of process monitoring. By distinguishing between temporary processes and long-term processes, more refined monitoring is achieved, reducing the possibility of misjudgment and improving the effectiveness and accuracy of process monitoring.

Corresponding to the above method embodiment, this specification also provides a process monitoring device embodiment. FIG4 shows a schematic diagram of the structure of a process monitoring device provided by an embodiment of this specification. As shown in FIG4, the device includes:

A first acquisition module 402 is configured to acquire the start time of the target process;

The operation timeout determination module 404 is configured to determine whether the target process has timed out based on the start time;

The classification identification module 406 is configured to, if yes, identify the target process as a temporary process or a long-term process;

The first determination module 408 is configured to determine that the target process has an abnormal operation when the target process is a temporary process;

The second determination module 410 is configured to query the update time of the process log of the target process when the target process is a long-term process, and determine whether the target process has an operational abnormality based on the update time.

Optionally, the device further comprises:

A second acquisition module is configured to acquire a preset running time of a target process;

Correspondingly, the operation timeout determination module 404 is further configured as follows:

Based on the start time and the current time, determine the running time of the target process; compare the running time with the preset running time to determine whether the target process has timed out.

Optionally, the device further comprises:

A third acquisition module is configured to obtain a process type identifier of a target process;

Correspondingly, the classification identification module 406 is further configured to:

If so, based on the process type identifier, identify the target process as a temporary process or a long-term process.

Optionally, the device further comprises:

A fourth acquisition module is configured to acquire a preset stop update duration of a process log of a target process;

Correspondingly, the second determining module 410 is further configured to:

Based on the update time and the current time, determine the stop update duration of the process log; compare the stop update duration with the preset stop update duration; when the stop update duration is greater than the preset stop update duration, determine that the target process has an abnormal operation.

Optionally, the device further comprises:

The first feedback module is configured to stop the target process and record the running information of the target process; and feed back the running information to the front end.

Optionally, the device further comprises:

The second feedback module is configured to stop the target process and record the running information of the target process; and feed back the running information to the front end.

Optionally, the device further comprises:

The third feedback module is configured to stop running the target process if the query is not found, and record the running information of the target process; and feed back the running information to the front end.

Optionally, the device further comprises:

The configuration module is configured to obtain configuration information of multiple preset processes to be monitored; store the configuration information of multiple processes to be monitored into a monitoring process set; determine whether the monitoring process set is empty; if not, obtain the configuration information of the target process from the monitoring process set, and delete the configuration information of the target process in the monitoring process set; parse the configuration information to obtain the process identifier and configuration parameters of the target process, wherein the configuration parameters include at least one of a preset running time, a process type identifier, and a preset stop update time of the process log of the target process; and put the process identifier into a process monitoring queue.

Optionally, the device further comprises:

The query module is configured to query whether the process identifier of the target process is recorded in the process monitoring queue;

Correspondingly, the first acquisition module 402 is further configured to:

If yes, get the start time of the target process.

Optionally, the device further comprises:

The first return module is configured to update the target process and return to execute the step of determining whether the monitoring process set is empty.

Optionally, the device further comprises:

The second return module is configured to update the target process if not, and return to execute the step of determining whether the monitoring process set is empty.

Optionally, the second determining module 410 is further configured to:

Based on the update time and the current time, determine the stop update duration of the process log; compare the stop update duration with the preset stop update duration; if the stop update duration is not greater than the preset stop update duration, update the target process and return to execute the step of determining whether the monitoring process set is empty.

In the embodiments of this specification, the entire process monitoring follows specific monitoring rules to achieve automated process monitoring. By monitoring the start time of the target process and the update time of the process log, it is possible to identify whether the target interactive process is running abnormally, thereby improving the timeliness of process monitoring. By distinguishing between temporary processes and long-term processes, more refined monitoring is achieved, reducing the possibility of misjudgment and improving the effectiveness and accuracy of process monitoring.

The above is a schematic scheme of a process monitoring device of this embodiment. It should be noted that the technical scheme of the process monitoring device and the technical scheme of the process monitoring method described above are of the same concept, and the details not described in detail in the technical scheme of the process monitoring device can be referred to the description of the technical scheme of the process monitoring method described above.

Fig. 5 shows a block diagram of a computing device provided in one embodiment of the present specification. The components of the computing device 500 include but are not limited to a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and the database 550 is used to store data.

The computing device 500 also includes an access device 540 that enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of network interface (e.g., a Network Interface Controller (NIC)) of wired or wireless, such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, and a Near Field Communication (NFC).

In one embodiment of the present specification, the above components of the computing device 500 and other components not shown in FIG. 5 may also be connected to each other, for example, through a bus. It should be understood that the computing device structure block diagram shown in FIG. 5 is only for illustrative purposes and is not intended to limit the scope of the present specification. Those skilled in the art may add or replace other components as needed.

The computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 500 may also be a mobile or stationary server.

The processor 520 is used to execute the following computer program/instructions, which implement the steps of the above-mentioned process monitoring method when executed by the processor.

The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the process monitoring method described above are of the same concept, and the details not described in detail in the technical scheme of the computing device can be found in the description of the technical scheme of the process monitoring method described above.

An embodiment of the present specification also provides a computer-readable storage medium storing a computer program/instruction, which implements the steps of the above-mentioned process monitoring method when executed by a processor.

The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the process monitoring method described above are of the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the process monitoring method described above.

An embodiment of the present specification also provides a computer program product, including a computer program/instruction, which implements the steps of the above-mentioned process monitoring method when executed by a processor.

The above is a schematic scheme of a computer program product of this embodiment. It should be noted that the technical scheme of the computer program product and the technical scheme of the process monitoring method described above are of the same concept, and the details not described in detail in the technical scheme of the computer program product can be found in the description of the technical scheme of the process monitoring method described above.

The above is a description of a specific embodiment of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can understand and use this specification well. This specification is only limited by the claims and their full scope and equivalents.

Claims (16)

1. A process monitoring method, comprising:

Acquiring the starting time of a target process;

judging whether the target process runs overtime or not based on the starting time;

if yes, identifying the target process as a temporary process or a long-acting process;

Determining that the target process is abnormal in operation under the condition that the target process is a temporary process;

And under the condition that the target process is a long-acting process, inquiring the update time of a process log of the target process, and determining whether the target process is abnormal in operation or not based on the update time.

2. The method of claim 1, further comprising, prior to said determining whether said target process is running over time based on said start-up time:

Acquiring a preset running time of the target process;

the step of judging whether the target process runs overtime based on the starting time comprises the following steps:

determining the running time of the target process based on the starting time and the current time;

Comparing the operation time length with the preset operation time length, and judging whether the target process is overtime.

3. The method of claim 1, further comprising, prior to said if, identifying the target process as a temporary process or a long-acting process:

acquiring a process type identifier of a target process;

if yes, identifying the target process as a temporary process or a long-acting process, including:

If yes, based on the process type identification, identifying the target process as a temporary process or a long-acting process.

4. The method of claim 1, wherein prior to the determining whether the target process is experiencing an operational anomaly based on the update time, further comprising:

acquiring a preset stop updating time length of a process log of the target process;

The determining whether the target process has abnormal operation based on the update time comprises the following steps:

Determining the update stopping time length of the process log based on the update time and the current time;

Comparing the stop updating time length with the preset stop updating time length;

And determining that the target process is abnormal in operation under the condition that the update stopping time is longer than the preset update stopping time.

5. The method according to claim 4, wherein, in the case where the update stop time period is longer than the preset update stop time period, after determining that the target process has an abnormal operation, further comprising:

stopping running the target process and recording the running information of the target process;

And feeding back the operation information to the front end.

6. The method of claim 1, wherein, in the case where the target process is a temporary process, after determining that the target process has an abnormal operation, further comprising:

stopping running the target process and recording the running information of the target process;

And feeding back the operation information to the front end.

7. The method of claim 1, further comprising, after the querying the update time of the process log of the target process:

if not, stopping running the target process, and recording the running information of the target process;

And feeding back the operation information to the front end.

8. The method of claim 1, further comprising, prior to the start time of the acquisition target process:

Acquiring preset configuration information of a plurality of processes to be monitored;

storing configuration information of the multiple processes to be monitored into a monitoring process set;

judging whether the monitoring process set is empty or not;

If not, acquiring the configuration information of the target process from the monitoring process set, and deleting the configuration information of the target process in the monitoring process set;

Analyzing the configuration information to obtain a process identifier and a configuration parameter of the target process, wherein the configuration parameter comprises at least one of a preset operation duration, a process type identifier and a preset stop update duration of a process log of the target process;

And placing the process identifier into a process monitoring queue.

9. The method of claim 8, further comprising, after said placing said process identification in a process monitor queue:

Inquiring whether a process identifier of a target process is recorded from a process monitoring queue;

The obtaining the starting time of the target process includes:

if yes, acquiring the starting time of the target process.

10. The method of claim 9, further comprising, after querying the slave process monitor queue for a process identifier of a target process recorded therein:

if not, updating the target process, and returning to execute the step of judging whether the monitoring process set is empty.

11. The method of claim 8, further comprising, after said determining whether said target process is running over time based on said start-up time:

if not, updating the target process, and returning to execute the step of judging whether the monitoring process set is empty.

12. The method of claim 8, wherein the determining whether the target process is experiencing an operational anomaly based on the update time comprises:

Determining the update stopping time length of the process log based on the update time and the current time;

Comparing the stop updating time length with the preset stop updating time length;

And under the condition that the stop updating time is not longer than the preset stop updating time, updating the target process, and returning to execute the step of judging whether the monitoring process set is empty.

13. A process monitoring device, comprising:

the first acquisition module is configured to acquire the starting time of the target process;

an operation timeout judging module configured to judge whether the target process is operation timeout based on the start-up time;

the classification identification module is configured to identify the target process as a temporary process or a long-acting process if the target process is a temporary process or a long-acting process;

The first determining module is configured to determine that the target process is abnormal in operation when the target process is a temporary process;

And the second determining module is configured to query the update time of the process log of the target process and determine whether the target process is abnormal in operation or not based on the update time when the target process is a long-acting process.

14. A computing device, comprising:

A memory and a processor;

The memory is adapted to store a computer program/instruction, the processor being adapted to execute the computer program/instruction, which when executed by the processor performs the steps of the method of any of claims 1 to 12.

15. A computer-readable storage medium, characterized in that it stores a computer program/instruction which, when executed by a processor, implements the steps of the method of any one of claims 1 to 12.

16. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method of any of claims 1 to 12.