CN118297580B - Petroleum equipment maintenance management method, system and storage medium based on big data - Google Patents
Petroleum equipment maintenance management method, system and storage medium based on big data Download PDFInfo
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Abstract
The invention belongs to the technical field of data processing, and particularly relates to a petroleum equipment maintenance management method, a petroleum equipment maintenance management system and a petroleum equipment storage medium based on big data, wherein the petroleum equipment maintenance management method comprises the following steps: acquiring related information of petroleum equipment; establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on each petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result; acquiring theoretical abnormal probability of petroleum equipment, acquiring equipment abnormal frequency stored in a first memory, calculating actual abnormal probability according to the equipment abnormal frequency, acquiring a difference value by subtracting the theoretical abnormal probability from the actual abnormal probability, setting a first threshold value for each petroleum equipment, and setting identification information for the petroleum equipment according to the difference value and the first threshold value; and according to the identification information, the inspection information and the maintenance information, a maintenance scheme is formulated for the petroleum equipment. The invention can reduce the frequency of inspection while improving the operation efficiency of petroleum equipment and make a better maintenance scheme.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a petroleum equipment maintenance management method, system and storage medium based on big data.
Background
Petroleum equipment is typically inspected and maintained at an initial stage of use according to equipment manufacturer recommended inspection cycles, but manufacturer recommended inspection cycles are typically relatively short, resulting in excessive maintenance. The petroleum equipment is aged, worn, rusted or loosened along with time, so that the performance is reduced, even the petroleum equipment cannot be used, the ongoing working progress can be influenced when the petroleum equipment in use is damaged or fails, the loss of manpower, material resources and financial resources is caused, even the safety problem is caused, and therefore, the petroleum equipment is prevented and maintained based on predictability before being damaged or failed, and the damage or failure can be avoided as much as possible. A similar prior art has chinese patent application publication No. CN115867911a, which provides a device maintenance management system including a plurality of devices that send information related to their own operation and the presence or absence of anomalies; and a remote processing device for acquiring and storing information of each of the plurality of devices. The remote processing apparatus restricts communication using at least one type of authentication key having a master-slave relationship, and communicates, as communication targets, a first communication device to which an authentication key to be a master is given in advance with respect to at least a part of the plurality of devices, and a second communication device to which an authentication key to be a slave of the first communication device is given in advance. When communication is performed, the remote processing device determines the range of information to be provided according to the type of authentication key and the master-slave relationship of the communication object. The similar prior art also discloses a China patent application document with a publication number of CN115760065A, and discloses an equipment maintenance management system and a maintenance management method, wherein the equipment maintenance management system comprises an acquisition module, a management module and a sending module, and the acquisition module is used for acquiring the operation parameter information of equipment; the management module is used for carrying out configuration management based on the operation parameter information of the equipment and generating a configuration management result; and the sending module is used for sending the configuration management result to the user equipment so as to enable maintenance personnel corresponding to the user equipment to maintain the equipment. The application automatically acquires the operation parameter information of the equipment, analyzes the operation parameter information, generates a configuration management result suitable for maintenance personnel maintaining the equipment, and contacts corresponding maintenance personnel according to the configuration management result. However, the problem of reducing the maintenance cost by optimizing the maintenance scheme is not considered in both the above two documents, so that the invention provides the petroleum equipment maintenance management method, system and storage medium based on big data.
Disclosure of Invention
The invention obtains the related information of petroleum equipment; establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on each petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result; acquiring theoretical anomaly probability of each petroleum equipment, acquiring equipment anomaly frequency stored in a first memory, calculating actual anomaly probability according to the equipment anomaly frequency, acquiring a difference value by subtracting the theoretical anomaly probability from the actual anomaly probability, setting a first threshold value for each petroleum equipment, and setting identification information for the petroleum equipment according to the difference value and the first threshold value; and according to the identification information, the inspection information and the maintenance information, a maintenance scheme is formulated for the petroleum equipment. The method solves the problem of excessive maintenance, and realizes that the operation efficiency of petroleum equipment is ensured and the maintenance cost is reduced under the condition of not causing excessive maintenance.
In order to achieve the above object, the present invention provides a petroleum equipment maintenance management method, system and storage medium based on big data as described below, which is implemented by executing the following steps:
Acquiring related information of petroleum equipment, wherein the related information comprises equipment information, an anomaly type, anomaly information, inspection information and maintenance information, the equipment information comprises equipment names, equipment models, equipment utilization rates, equipment anomaly frequencies and equipment utilization times, the anomaly information comprises anomaly frequencies of each anomaly type in a unit event and loss costs caused by each anomaly type, the inspection information comprises an inspection period and an inspection time, the maintenance information comprises maintenance time and maintenance cost, and the related information is stored in a first memory;
establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on the petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result;
Obtaining theoretical anomaly probability of petroleum equipment in the anomaly estimation result, obtaining the equipment anomaly frequency stored in the first memory, calculating actual anomaly probability according to the equipment anomaly frequency, subtracting the theoretical anomaly probability from the actual anomaly probability to obtain a difference value, setting a first threshold value for the petroleum equipment, setting a first identifier for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identifier for the petroleum equipment if the difference value is greater than zero and the difference value is less than the first threshold value, and setting a third identifier for the petroleum equipment if the difference value is less than zero;
and according to the identification information, the inspection information and the maintenance information, a maintenance scheme is formulated for the petroleum equipment, wherein the identification information comprises the first identification, the second identification and the third identification, and the maintenance scheme comprises an inspection period and maintenance cost.
As a preferable technical scheme of the invention, the method for establishing the abnormal event relation graph comprises the following steps:
Analyzing and identifying a sub-event which causes the occurrence of the root event by taking the petroleum equipment abnormality as the root event, wherein the sub-event refers to an abnormality type which directly causes the occurrence of the root event, the root event corresponds to a plurality of sub-events or one sub-event, the relation between the root event and the plurality of sub-events is defined as a first relation when the root event occurs in all of the plurality of sub-events, the relation between the root event and the plurality of sub-events is defined as a second relation when any one of the plurality of sub-events occurs, and the root event and the sub-events are connected to form an abnormal event relation graph based on the relation between the root event and the plurality of sub-events from the root event.
As a preferable technical scheme of the invention, the method for carrying out anomaly estimation on each petroleum equipment based on the anomaly event relation graph comprises the following steps:
Obtaining the abnormal frequency of the abnormal type according to the related information of the petroleum equipment, calculating the actual abnormal probability of each abnormal type according to the abnormal frequency, obtaining the relation between the petroleum equipment and each abnormal type according to the abnormal event relation diagram, wherein the petroleum equipment corresponds to a root event, the abnormal type corresponds to a sub event, multiplying the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a first relation, adding the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a second relation, and taking the theoretical abnormal probability of the root event as the theoretical abnormal probability of the petroleum equipment.
As a preferred technical solution of the present invention, setting a first threshold for each of the petroleum apparatuses includes the steps of:
Acquiring standard reference information of the petroleum equipment, wherein the standard reference information comprises standard use time and standard abnormal probability, acquiring equipment use rate and equipment use time of the petroleum equipment, acquiring actual use time of the petroleum equipment according to the equipment use rate and the equipment use time, comparing the actual use time with the standard use time, and calculating the first threshold R by a first formula if the actual use time is greater than the standard use time, wherein the first formula is as follows: r= (t 2/t 1-1) p, where t2 is the actual usage time, t1 is the standard usage time, p is the standard anomaly probability, if the actual usage time is less than the standard usage time, calculating the first threshold R with a second formula, where the second formula is: r= (1-t 2/t 1) P, if the actual usage time is equal to the standard usage time, setting the first threshold to zero.
As a preferable technical scheme of the invention, the method for updating the maintenance scheme for the petroleum equipment comprises the following steps:
If the identification information of the petroleum equipment is a first identification, acquiring the inspection information of the petroleum equipment, acquiring an inspection period C in the inspection information, setting the inspection period of the petroleum equipment to be C/2, setting the maintenance cost of the petroleum equipment to be twice as high as the original, if the identification information of the petroleum equipment is a second identification, keeping the inspection period of the petroleum equipment and the maintenance cost unchanged, and if the identification information of the petroleum equipment is a third identification, setting the inspection period of the petroleum equipment to be C x 2, and setting the maintenance cost of the petroleum equipment to be half as high as the original.
As a preferable technical scheme of the invention, after updating the maintenance scheme, the following steps are also executed:
Setting an intelligent sensor for each petroleum equipment, collecting first data of each petroleum equipment at intervals of a preset period by the intelligent sensor, wherein the first data comprise the running state, running parameters and other related data of the petroleum equipment, and making an abnormality mark for the first data acquired at corresponding time under the condition that the petroleum equipment is abnormal.
As a preferred technical solution of the present invention, after the first data acquired at the corresponding time is marked as abnormal, the following steps are executed:
Dividing the first data collected in a history into second data and third data, using a machine learning algorithm to generate a prediction model by taking the second data and the corresponding abnormality marks as learning data, inputting the third data and the corresponding abnormality marks as test data into the prediction model, testing the prediction accuracy of the prediction model, if the prediction accuracy is greater than or equal to a second threshold value, predicting abnormality by using the prediction model, and if the accuracy is less than the second threshold value, continuing training the prediction model by using more history data until the prediction accuracy of the prediction model is greater than or equal to the second threshold value.
As a preferable technical scheme of the invention, after obtaining the prediction model with the prediction accuracy greater than or equal to the second threshold value, the following steps are further executed:
Inputting the acquired first data of the petroleum equipment in the latest period into the prediction model, predicting whether the petroleum equipment is abnormal or not by the prediction model, and if the prediction result is that the petroleum equipment is abnormal, checking and maintaining the petroleum equipment before the abnormality occurs.
The invention also provides a petroleum equipment maintenance management method, a petroleum equipment maintenance management system and a storage medium based on big data, wherein the petroleum equipment maintenance management method comprises the following modules:
A data collection module, configured to obtain related information of a petroleum device, where the related information includes device information, an anomaly type, anomaly information, inspection information and maintenance information, the device information includes a device name, a device model number, a device usage rate, a device anomaly frequency and a device usage time, the anomaly information includes an anomaly frequency of each anomaly type in a unit event and a loss cost caused by each anomaly type, the inspection information includes an inspection period and an inspection time, the maintenance information includes a maintenance time and a maintenance cost, and the related information is stored in a first memory;
the anomaly estimation module is used for establishing an anomaly event relation diagram according to the related information, wherein the anomaly event relation diagram comprises petroleum equipment anomalies and related anomaly types, and carrying out anomaly estimation on the petroleum equipment based on the anomaly event relation diagram to obtain an anomaly estimation result;
The identification setting module is used for acquiring theoretical abnormal probability of the petroleum equipment in the abnormal estimation result, acquiring the equipment abnormal frequency stored in the first memory, calculating actual abnormal probability according to the equipment abnormal frequency, subtracting the theoretical abnormal probability from the actual abnormal probability to acquire a difference value, setting a first threshold value for the petroleum equipment, setting a first identification for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identification for the petroleum equipment if the difference value is greater than zero and the difference value is smaller than the first threshold value, and making a third identification for the petroleum equipment if the difference value is smaller than zero;
And the updating maintenance module is used for making a maintenance scheme for the petroleum equipment according to the identification information, the inspection information and the maintenance information, wherein the identification information comprises the first identification, the second identification and the third identification, and the maintenance scheme comprises an inspection period and maintenance cost.
The present invention also provides a storage medium storing program instructions, wherein the program instructions, when executed, control a device in which the storage medium is located to perform any one of the methods described above.
Compared with the prior art, the invention has the following beneficial effects:
In the invention, the related information of petroleum equipment is firstly obtained, and necessary data support is provided for subsequent abnormal evaluation, data identification and maintenance scheme assignment through the collection of the related data; establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on each petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result; acquiring theoretical abnormal probability of each petroleum equipment, acquiring equipment abnormal frequency stored in a first memory, calculating actual abnormal probability according to the equipment abnormal frequency, acquiring a difference value by subtracting the theoretical abnormal probability from the actual abnormal probability, setting a first threshold value for each petroleum equipment, and setting identification information for the petroleum equipment according to the difference value and the first threshold value, wherein different identification information represents different states of the petroleum equipment; according to the identification information, the inspection information and the maintenance information, the number of inspection and maintenance times is reduced under the condition that the state of the petroleum equipment is good, the number of inspection and maintenance times is increased under the condition that the state of the petroleum equipment is not good, the inspection frequency is reduced while the operation efficiency of the petroleum equipment is improved, and the purpose of making a better maintenance scheme is achieved.
Drawings
FIG. 1 is a flow chart of the steps of the method for maintaining and managing big data of petroleum equipment of the present invention;
FIG. 2 is a schematic illustration of an anomaly event relationship diagram for a petroleum plant of the present invention;
Fig. 3 is a block diagram showing the constitution of the system for maintenance and management of petroleum equipment of big data according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of this disclosure.
The invention provides a petroleum equipment maintenance management method based on big data as shown in figure 1, which is realized by executing the following steps:
Step S1, acquiring related information of petroleum equipment, wherein the related information comprises equipment information, abnormal types, abnormal information, checking information and maintenance information, the equipment information comprises equipment names, equipment models, equipment utilization rates, equipment abnormal frequencies and equipment utilization times, the abnormal information comprises abnormal frequencies of each abnormal type in unit time and loss costs caused by each abnormal type, the checking information comprises checking periods and checking times, the maintenance information comprises maintenance times and maintenance costs, and the related information is stored in a first memory.
Specifically, in order to improve the operation efficiency of the equipment and reduce unnecessary maintenance work, related information of the petroleum equipment is first acquired, the related information including equipment name, equipment model, equipment usage rate, equipment abnormality frequency and equipment usage time, equipment abnormality frequency is the number of times of abnormality of the equipment in unit time, such as abnormality of the equipment in 100 hours, abnormality type is the abnormality type which may occur in each petroleum equipment, such as aging, looseness or rust, abnormality information includes abnormality frequency of each abnormality type in unit time and loss cost caused by each abnormality type, such as normal selling of petroleum may be affected because the equipment is loosened, the inspection information includes an inspection cycle and an inspection time, the inspection cycle is a cycle of the inspection equipment, for example, a half-year inspection or a month inspection, the inspection cycle is generally set according to the proposal of the petroleum equipment manufacturer, but the inspection cycle recommended by the manufacturer is generally shorter, so that a lot of unnecessary inspection and maintenance can be caused, the inspection time is a time for inspecting the petroleum equipment, for example, a time for inspecting a petroleum pipeline is one day, the time for inspecting a certain valve is five minutes, the maintenance information includes a maintenance time and a maintenance cost, the maintenance cost is a sum of a labor cost and a material cost required for maintaining the certain petroleum equipment, the related information is stored in a first memory, the integrity, the accuracy and the accessibility of the data are ensured by storing the related data in the memory, the subsequent abnormal evaluation is realized by the collection of the related data, the specification of data identification and maintenance schemes provides the necessary data support to enable the system to formulate an efficient maintenance scheme.
And S2, establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises the abnormality of the petroleum equipment and the related abnormality type, and carrying out abnormality estimation on the petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result.
Specifically, in order to obtain potential risks of each petroleum device, and formulate a corresponding maintenance scheme according to the potential risks, so as to reduce the risks and improve the operation efficiency of the device, an abnormal event relation diagram is established according to related information, the abnormal event relation diagram comprises the abnormality of the petroleum device and related abnormality types, the abnormality estimation is carried out on each petroleum device based on the abnormal event relation diagram, the abnormality estimation result is obtained, a specific estimation process is explained in detail later, the theoretical abnormality probability of the petroleum device is obtained through abnormality estimation, and the potential risks of the petroleum device are judged through comparing the theoretical abnormality probability with the actual abnormality probability.
And S3, acquiring theoretical anomaly probability of the petroleum equipment in the anomaly estimation result, further acquiring equipment anomaly frequency stored in the first memory, calculating actual anomaly probability according to the equipment anomaly frequency, subtracting the theoretical anomaly probability from the actual anomaly probability to acquire a difference value, setting a first threshold value for the petroleum equipment, setting a first identifier for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identifier for the petroleum equipment if the difference value is greater than zero and smaller than the first threshold value, and setting a third identifier for the petroleum equipment if the difference value is smaller than zero.
The method comprises the steps of obtaining theoretical anomaly probabilities of all petroleum equipment in an anomaly estimation result, wherein the theoretical anomaly probabilities are theoretical values calculated according to a relation between all the petroleum equipment and related anomaly types, explaining the theoretical anomaly probabilities in detail later, obtaining anomaly frequencies of all the petroleum equipment stored in a first memory, calculating the actual anomaly probabilities according to the anomaly frequencies according to actual occurrence frequencies of the petroleum equipment in a preset time, if the actual anomaly probabilities of the petroleum equipment occur 1 time in 100 hours of operation, obtaining a difference value by subtracting the theoretical anomaly probabilities from the actual anomaly probabilities, setting a first threshold value for all the petroleum equipment, if the difference value is larger than the theoretical anomaly frequencies, comparing the difference value with the first threshold value, if the difference value is larger than the first threshold value, indicating that the actual anomaly probabilities of the petroleum equipment are not in a normal range, possibly rusting or aging the petroleum equipment, setting a first mark for the petroleum equipment at the moment, providing a basis for a subsequent maintenance scheme, if the difference value is smaller than the first threshold value, indicating that the petroleum equipment is still in a controllable range, setting a second mark for the petroleum equipment is smaller than the first threshold value, and if the difference value is smaller than the actual anomaly probabilities of the petroleum equipment are smaller than the first threshold value, and the actual anomaly probabilities of the petroleum equipment are smaller than the actual anomaly probabilities of the actual anomaly probabilities, and the petroleum equipment are more than the actual anomaly probabilities of the actual anomaly probabilities, and the petroleum equipment is smaller than the actual anomaly probabilities of the first threshold value, and the petroleum equipment is more than the actual anomaly probabilities and the actual anomaly probability is smaller than the first threshold value, and the actual anomaly probability is smaller than the petroleum equipment.
And S4, formulating a maintenance scheme for the petroleum equipment according to the identification information, the inspection information and the maintenance information, wherein the identification information comprises a first identification, a second identification and a third identification, and the maintenance scheme comprises an inspection period and maintenance cost.
Specifically, different identifications, inspection information and maintenance information of the petroleum equipment are set according to the conditions of the petroleum equipment, a subsequent maintenance scheme is formulated for the petroleum equipment, the maintenance scheme comprises an inspection period and maintenance cost, a better maintenance scheme can be set for the petroleum equipment, for example, under the condition that the petroleum equipment is good, the inspection frequency is reduced, less maintenance cost is prepared, unnecessary inspection and maintenance can be reduced, the cost is reduced, under the condition that the petroleum equipment is bad, the inspection frequency is increased, more maintenance cost is prepared, and the operation efficiency of the petroleum equipment is improved.
The technical proposal is explained in detail by taking a pressure instrument as an example of petroleum equipment, according to the related information of the pressure instrument, the abnormal frequency of the pressure instrument in one month is counted to be 6, the abnormal types causing the abnormality of the pressure instrument are also obtained, namely, the sensor aging, the corrosion at the joint and the mechanical abrasion of the parts are respectively obtained, the abnormal frequencies of the three abnormal types in one month are counted to be 1,3 and 1 respectively, the total abnormal frequency of the three abnormal types is 5 and the abnormal frequency of the pressure instrument is 6 different, because the reasons that the abnormality of the pressure instrument possibly exists are not caused by the three abnormal types, such as the abnormal operation or the external environment factors, the sensor aging, the corrosion at the joint and the mechanical abrasion are all found to cause the abnormality of the pressure instrument through analysis, that is, as long as any occurrence thereof may cause abnormality of the pressure meter, the relationship between the abnormality of the pressure meter and the three types of abnormality is a first relationship, the actual abnormality probability of the abnormality of the pressure meter is calculated according to the first relationship in statistical units of days as 6/30=0.2, the theoretical abnormality probability of the abnormality of the pressure meter is calculated according to the first relationship as (1+3+1)/30=0.17, the difference between the theoretical abnormality probability and the actual abnormality probability is obtained as 0.03, the equipment usage time of the pressure meter is obtained as 60 days and the equipment usage rate is 80%, the actual usage time of the pressure meter is obtained as 48 days by calculation, the standard usage time of the pressure meter is obtained as 60 days and the standard abnormality probability of 0.02 are calculated according to the second formula (1-48/60) ×0.02 as a first threshold value of the pressure meter is 0.016, the difference value of 0.03 is larger than the first threshold value of 0.016 by comparison, the actual abnormal probability is larger than the theoretical abnormal frequency, the abnormal probability of the pressure instrument is not in the normal range, the maintenance period of the pressure instrument is shortened at the moment, and a more optimized maintenance scheme can be formulated for the pressure instrument through the scheme in order to ensure that the petroleum equipment can normally run.
According to the technical scheme, related information of the petroleum equipment is firstly obtained, theoretical abnormal probability of the petroleum equipment is calculated according to the related information, actual abnormal probability of the petroleum equipment is also obtained, the condition of the petroleum equipment is judged by comparing the theoretical abnormal probability with the actual abnormal probability, if the condition is good, the frequency of inspection is reduced, and if the condition is bad, the frequency of inspection is increased, the operation efficiency of the petroleum equipment is improved, meanwhile, the frequency of inspection is reduced, and the purpose of formulating a better maintenance scheme is achieved.
Further, an abnormal event relation diagram is established, which comprises the following steps:
Analyzing and identifying sub-events which cause occurrence of the root event by using the petroleum equipment abnormality as the root event, wherein the sub-events refer to abnormality types which directly cause occurrence of the root event, the root event corresponds to a plurality of sub-events or one sub-event, the relationship between the root event and the plurality of sub-events is defined as a first relationship under the condition that all the plurality of sub-events occur, the relationship between the root event and the plurality of sub-events is defined as a second relationship under the condition that any one of the plurality of sub-events occurs, and the root event and the sub-events are connected to form an abnormal event relationship graph based on the relationship between the root event and the plurality of sub-events from the root event.
Specifically, an abnormal event relation diagram is established, a more accurate theoretical abnormal probability of the petroleum equipment can be obtained through the abnormal event relation diagram, the petroleum equipment abnormality is taken as a root event, such as the occurrence of the petroleum pipeline abnormality, the sub-event which causes the occurrence of the root event is analyzed and identified, the sub-event is the abnormal type which directly causes the occurrence of the root event, the root event corresponds to a plurality of sub-events or one sub-event, the relation between the root event and the plurality of sub-events is defined as a first relation when the plurality of sub-events occur only, for example, two sub-events are respectively pipeline breakage and pipeline blockage, the relation between the root event and the plurality of sub-events is defined as a second relation when any one of the plurality of sub-events occurs, for example, the root event is the equipment is not pneumatic, the corresponding two sub-events are respectively a switch damage and a standby switch damage, the root event is connected to form the abnormal event relation diagram based on the relation between the root event and the plurality of sub-events, for example, the root event is a pipeline breakage and the pipeline blockage in fig. 2, and the first relation is a pipeline blockage in the case of the abnormal event relation diagram of a petroleum equipment.
Further, the method for carrying out anomaly estimation on each petroleum equipment based on the anomaly event relation graph comprises the following steps:
Obtaining the abnormal frequency of each abnormal type according to the related information of the petroleum equipment, calculating the actual abnormal probability of each abnormal type according to the abnormal frequency, obtaining the relation between the petroleum equipment and each abnormal type according to an abnormal event relation diagram, wherein the petroleum equipment corresponds to a root event, the abnormal type corresponds to a sub event, the actual abnormal probability of a plurality of sub events corresponding to the root event is multiplied to obtain the theoretical abnormal probability of the root event under the condition that the root event and the sub event are in a first relation, the actual abnormal probability of a plurality of sub events corresponding to the root event is added to obtain the theoretical abnormal probability of the root event under the condition that the root event and the sub event are in a second relation, and the theoretical abnormal probability of the root event is used as the theoretical abnormal probability of the corresponding petroleum equipment.
Specifically, in order to calculate the theoretical anomaly probability of the petroleum equipment, collect the anomaly frequency of each anomaly type, calculate the actual anomaly probability of each anomaly type according to the anomaly frequency, the specific calculation method is that the anomaly frequency of each anomaly type is divided by a predetermined time, for example, if a certain switch has 1 anomaly in 100 hours of operation, the actual anomaly probability is 1/100=0.01, after calculating the actual anomaly probability, the relationship between each petroleum equipment and the related anomaly type is obtained according to the anomaly event relationship graph, calculate the theoretical anomaly probability, and compare the calculated theoretical anomaly probability with the actual anomaly probability obtained by statistics to obtain the anomaly estimation result of the petroleum equipment.
Further, setting a first threshold for the petroleum equipment, comprising the steps of:
The method comprises the steps of obtaining standard reference information of petroleum equipment, wherein the standard reference information comprises standard use time and standard abnormal probability, obtaining equipment use rate and equipment use time of the petroleum equipment, obtaining actual use time of the petroleum equipment according to the equipment use rate and the equipment use time, comparing the actual use time with the standard use time, and if the actual use time is larger than the standard use time, calculating a first threshold value R by a first formula, wherein the first formula is as follows: r= (t 2/t 1-1) p, where t2 is the actual usage time, t1 is the standard usage time, p is the standard anomaly probability, if the actual usage time is less than the standard usage time, the first threshold R is calculated by a second formula, where: r= (1-t 2/t 1) P, if the actual usage time is equal to the standard usage time, the first threshold is set to zero.
Specifically, in order to set a corresponding first threshold value for each petroleum device, standard reference information of the petroleum device is obtained, the standard reference information comprises standard use time and standard abnormal probability, the standard use time refers to the longest time that the petroleum device can normally work, the device use rate and the device use time of the petroleum device are obtained according to the device use rate and the device use time, the actual use time and the standard use time are compared, if the actual use time is greater than the standard use time, the actual use time of the petroleum device is too long, and the standard use time of the petroleum device is exceeded, the actual abnormal probability is greater than the theoretical abnormal probability under normal conditions, and the difference value between the two should be the proportion occupied by exceeding the standard use time, so the first threshold value R is calculated by using a first formula, and similarly, if the actual use time is less than the standard use time, the actual abnormal probability is smaller than the theoretical abnormal probability, and the actual use time is smaller than the proportion occupied by the standard use time, the first threshold value R is calculated by using a second formula, if the actual use time is greater than the standard use time, the actual use time is equal to the actual use time is not longer than the standard use time, the actual use event is not equal to the actual use time, but the actual use time is just equal to the actual use time is not equal to the normal condition, and the normal condition is guaranteed to be normal, if the actual use condition is not equal to the normal condition is checked, and is normal, and is guaranteed, if the normal condition is normal, and is set.
Further, updating a maintenance scheme for the petroleum equipment, comprising the steps of:
If the identification information of the petroleum equipment is the first identification, acquiring the inspection information of the petroleum equipment, acquiring the inspection period C in the inspection information, setting the inspection period of the petroleum equipment to be C/2, setting the maintenance cost of the petroleum equipment to be twice as high as the original, if the identification information of the petroleum equipment is the second identification, keeping the inspection period and the maintenance cost of the petroleum equipment unchanged, and if the identification information of the petroleum equipment is the third identification, setting the inspection period of the petroleum equipment to be C.times.2, and setting the maintenance cost of the petroleum equipment to be half as high as the original.
Specifically, in order to set a more reasonable maintenance scheme, the identification information of the petroleum equipment is obtained, if the identification information is a first identification, the actual anomaly probability of the petroleum equipment is larger than the theoretical anomaly probability, and the difference value between the identification information and the first identification exceeds a set threshold value, the frequency of the anomaly occurrence of the petroleum equipment is indicated to be obviously increased, in order to ensure that the petroleum equipment can normally operate, the inspection information of the petroleum equipment is obtained, the inspection period in the inspection information is set shorter, for example, if the original inspection period is one month and is inspected, the maintenance cost of the petroleum equipment is shortened and responded because the inspection period is increased, the maintenance cost is set to be twice the original maintenance cost, if the identification information of the petroleum equipment is a second identification, the actual anomaly probability of the petroleum equipment is indicated to be larger than the theoretical anomaly probability, but the difference value between the two identification information does not exceed the set threshold value, the frequency of the anomaly occurrence of the petroleum equipment is indicated to be slightly increased or not increased, in order to keep the original inspection period and the maintenance cost, if the identification information of the petroleum equipment is a third identification is set to be the third identification, the actual anomaly probability of the petroleum equipment is smaller than the theoretical anomaly probability, the petroleum equipment is good, the petroleum equipment is generally not reduced, the maintenance cost is set to be the corresponding to be set to be the optimal, and the maintenance cost can be set to be more than the original maintenance cost is optimized.
Further, after updating the maintenance scheme, the following steps are also performed:
Setting an intelligent sensor for each petroleum equipment, collecting first data of each petroleum equipment at intervals of a preset period by the intelligent sensor, wherein the first data comprise the running state, the running parameters and other related data of the petroleum equipment, and making an abnormality mark for the first data acquired at corresponding time under the condition that the petroleum equipment is abnormal.
Dividing the first data collected in the history into second data and third data, using a machine learning algorithm to generate a prediction model by taking the second data and the corresponding abnormal marks as learning data, inputting the third data and the corresponding abnormal marks as test data into the prediction model, testing the prediction accuracy of the prediction model, if the prediction accuracy is greater than or equal to a second threshold value, predicting the abnormality by using the prediction model, and if the accuracy is less than the second threshold value, continuing to train the prediction model by using more historical data until the prediction accuracy of the prediction model is greater than or equal to the second threshold value.
Inputting the acquired first data of the petroleum equipment in the latest period into a prediction model, predicting whether the petroleum equipment is abnormal or not by the prediction model, and if the prediction result is that the petroleum equipment is abnormal, checking and maintaining the petroleum equipment before the abnormality occurs.
Specifically, other relevant parameters include data such as temperature of the petroleum equipment, and the like, by the method, the anomaly of each petroleum equipment is predicted, and the anomaly of the petroleum equipment is found in advance, so that the inspection and maintenance can be performed in time, the operation efficiency of the petroleum equipment can be improved, and the occurrence of the anomaly is reduced.
According to another aspect of the embodiment of the present invention, referring to fig. 3, there is further provided a big data based petroleum equipment maintenance management system, including a data collection module, an anomaly estimation module, an identification setting module, and an update maintenance module, for implementing the big data based petroleum equipment maintenance management method as described above, the specific functions of each module are as follows:
The data collection module is used for acquiring related information of the petroleum equipment, wherein the related information comprises equipment information, abnormal types, abnormal information, inspection information and maintenance information, the equipment information comprises equipment names, equipment models, equipment use rates, equipment abnormal frequencies and equipment use time, the abnormal information comprises abnormal frequencies of each abnormal type in a unit event and loss costs caused by each abnormal type, the inspection information comprises an inspection period and an inspection time, the maintenance information comprises maintenance time and maintenance cost, and the related information is stored in the first memory;
the abnormal estimation module is used for establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises the abnormality of the petroleum equipment and the related abnormality type, and carrying out abnormal estimation on the petroleum equipment based on the abnormal event relation diagram to obtain an abnormal estimation result;
The device comprises an identification setting module, a first identification setting module, a second identification setting module and a third identification setting module, wherein the identification setting module is used for acquiring theoretical anomaly probability of petroleum equipment in an anomaly estimation result, acquiring equipment anomaly frequency stored in a first memory, calculating actual anomaly probability according to the equipment anomaly frequency, subtracting the theoretical anomaly probability from the actual anomaly probability to acquire a difference value, setting a first threshold value for the petroleum equipment, setting a first identification for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identification for the petroleum equipment if the difference value is greater than zero and the difference value is smaller than the first threshold value, and setting a third identification for the petroleum equipment if the difference value is smaller than zero;
And the updating maintenance module is used for making a maintenance scheme for the petroleum equipment according to the identification information, the inspection information and the maintenance information, wherein the identification information comprises a first identification, a second identification and a third identification, and the maintenance scheme comprises an inspection period and maintenance cost.
According to another aspect of the embodiment of the present invention, there is also provided a storage medium storing program instructions, where the program instructions, when executed, control a device in which the storage medium is located to perform the method of any one of the above.
In summary, the method, the system and the storage medium for maintaining and managing petroleum equipment based on big data comprise the steps of obtaining relevant information of petroleum equipment; establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on each petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result; acquiring theoretical anomaly probability of each petroleum equipment, acquiring equipment anomaly frequency stored in a first memory, calculating actual anomaly probability according to the equipment anomaly frequency, acquiring a difference value by subtracting the theoretical anomaly probability from the actual anomaly probability, setting a first threshold value for each petroleum equipment, and setting identification information for the petroleum equipment according to the difference value and the first threshold value; and according to the identification information, the inspection information and the maintenance information, a maintenance scheme is formulated for the petroleum equipment. The invention can reduce the frequency of inspection while improving the operation efficiency of petroleum equipment and make a better maintenance scheme.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of computer programs, which may be stored on a non-transitory computer readable storage medium, and which, when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and for brevity, all of the possible combinations of the technical features of the above embodiments are not described, however, they should be considered as the scope of the description of the present specification as long as there is no contradiction between the combinations of the technical features.
The foregoing examples have been presented to illustrate only a few embodiments of the invention and are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (6)
1. The petroleum equipment maintenance management method based on big data is characterized by comprising the following steps:
Acquiring related information of petroleum equipment, wherein the related information comprises equipment information, abnormal types, abnormal information, checking information and maintenance information, the equipment information comprises equipment names, equipment models, equipment utilization rates, equipment abnormal frequencies and equipment utilization time, the abnormal information comprises abnormal frequencies of each abnormal type in unit time and loss costs caused by each abnormal type, the checking information comprises checking periods and checking time, the maintenance information comprises maintenance time and maintenance cost, and the related information is stored in a first memory;
establishing an abnormal event relation diagram according to the related information, wherein the abnormal event relation diagram comprises petroleum equipment abnormality and related abnormality types, and performing abnormality estimation on the petroleum equipment based on the abnormal event relation diagram to obtain an abnormality estimation result;
Obtaining theoretical anomaly probability of petroleum equipment in the anomaly estimation result, obtaining the equipment anomaly frequency stored in the first memory, calculating actual anomaly probability according to the equipment anomaly frequency, subtracting the theoretical anomaly probability from the actual anomaly probability to obtain a difference value, setting a first threshold value for the petroleum equipment, setting a first identifier for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identifier for the petroleum equipment if the difference value is greater than zero and the difference value is less than the first threshold value, and setting a third identifier for the petroleum equipment if the difference value is less than zero;
Establishing a maintenance scheme for the petroleum equipment according to the identification information, the inspection information and the maintenance information, wherein the identification information comprises the first identification, the second identification and the third identification, and the maintenance scheme comprises an inspection period and maintenance cost;
The method for establishing the abnormal event relation graph comprises the following steps:
Analyzing and identifying a sub-event which causes the occurrence of the root event by taking the petroleum equipment abnormality as the root event, wherein the sub-event refers to an abnormality type which directly causes the occurrence of the root event, the root event corresponds to a plurality of sub-events or one sub-event, the relationship between the root event and the plurality of sub-events is defined as a first relationship when the root event occurs in all of the plurality of sub-events, the relationship between the root event and the plurality of sub-events is defined as a second relationship when any one of the plurality of sub-events occurs, and an abnormal event relationship graph is formed by connecting the root event and the sub-events based on the relationship between the root event and the plurality of sub-events from the root event;
the method for carrying out anomaly estimation on the petroleum equipment based on the anomaly event relation graph comprises the following steps:
Acquiring the abnormal frequency of the abnormal type according to the related information of the petroleum equipment, calculating the actual abnormal probability of each abnormal type according to the abnormal frequency, acquiring the relation between the petroleum equipment and each abnormal type according to the abnormal event relation diagram, wherein the petroleum equipment corresponds to a root event, the abnormal type corresponds to a sub event, multiplying the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a first relation, adding the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a second relation, and taking the theoretical abnormal probability of the root event as the theoretical abnormal probability of the petroleum equipment;
Wherein, set up the first threshold value for each said petroleum apparatus, including the following step:
Acquiring standard reference information of the petroleum equipment, wherein the standard reference information comprises standard use time and standard abnormal probability, acquiring equipment use rate and equipment use time of the petroleum equipment, acquiring actual use time of the petroleum equipment according to the equipment use rate and the equipment use time, comparing the actual use time with the standard use time, and calculating the first threshold R by a first formula if the actual use time is greater than the standard use time, wherein the first formula is as follows: r= (t 2/t 1-1) p, where t2 is the actual usage time, t1 is the standard usage time, p is the standard anomaly probability, if the actual usage time is less than the standard usage time, calculating the first threshold R with a second formula, where the second formula is: r= (1-t 2/t 1) P, if the actual usage time is equal to the standard usage time, setting the first threshold to zero;
Wherein, for the petroleum equipment update maintenance scheme, include the following step:
If the identification information of the petroleum equipment is a first identification, acquiring the inspection information of the petroleum equipment, acquiring an inspection period C in the inspection information, setting the inspection period of the petroleum equipment to be C/2, setting the maintenance cost of the petroleum equipment to be twice as high as the original, if the identification information of the petroleum equipment is a second identification, keeping the inspection period of the petroleum equipment and the maintenance cost unchanged, and if the identification information of the petroleum equipment is a third identification, setting the inspection period of the petroleum equipment to be C x 2, and setting the maintenance cost of the petroleum equipment to be half as high as the original.
2. The method of claim 1, wherein after updating the maintenance schedule, further comprising the steps of:
Setting an intelligent sensor for each petroleum equipment, collecting first data of each petroleum equipment at intervals of a preset period by the intelligent sensor, wherein the first data comprise the running state, running parameters and other related data of the petroleum equipment, and making an abnormality mark for the first data acquired at corresponding time under the condition that the petroleum equipment is abnormal.
3. The method according to claim 2, wherein after the first data acquired at the corresponding time is marked for abnormality, the following steps are performed:
Dividing the first data collected in a history into second data and third data, using a machine learning algorithm to generate a prediction model by taking the second data and the corresponding abnormality marks as learning data, inputting the third data and the corresponding abnormality marks as test data into the prediction model, testing the prediction accuracy of the prediction model, if the prediction accuracy is greater than or equal to a second threshold value, predicting abnormality by using the prediction model, and if the accuracy is less than the second threshold value, continuing training the prediction model by using more history data until the prediction accuracy of the prediction model is greater than or equal to the second threshold value.
4. A method according to claim 3, wherein after obtaining a prediction model with a prediction accuracy equal to or greater than the second threshold value, the following steps are further performed:
Inputting the acquired first data of the petroleum equipment in the latest period into the prediction model, predicting whether the petroleum equipment is abnormal or not by the prediction model, and if the prediction result is that the petroleum equipment is abnormal, checking and maintaining the petroleum equipment before the abnormality occurs.
5. A big data based petroleum equipment maintenance management system for implementing the method according to any one of claims 1-4, comprising the following modules:
A data collection module, configured to obtain related information of a petroleum device, where the related information includes device information, an anomaly type, anomaly information, inspection information and maintenance information, the device information includes a device name, a device model number, a device usage rate, a device anomaly frequency, and a device usage time, the anomaly information includes an anomaly frequency of each anomaly type in a unit time and a loss cost caused by each anomaly type, the inspection information includes an inspection period and an inspection time, the maintenance information includes a maintenance time and a maintenance cost, and the related information is stored in a first memory;
the anomaly estimation module is used for establishing an anomaly event relation diagram according to the related information, wherein the anomaly event relation diagram comprises petroleum equipment anomalies and related anomaly types, and carrying out anomaly estimation on the petroleum equipment based on the anomaly event relation diagram to obtain an anomaly estimation result;
The method for establishing the abnormal event relation graph comprises the following steps:
Analyzing and identifying a sub-event which causes the occurrence of the root event by taking the petroleum equipment abnormality as the root event, wherein the sub-event refers to an abnormality type which directly causes the occurrence of the root event, the root event corresponds to a plurality of sub-events or one sub-event, the relationship between the root event and the plurality of sub-events is defined as a first relationship when the root event occurs in all of the plurality of sub-events, the relationship between the root event and the plurality of sub-events is defined as a second relationship when any one of the plurality of sub-events occurs, and an abnormal event relationship graph is formed by connecting the root event and the sub-events based on the relationship between the root event and the plurality of sub-events from the root event;
the method for carrying out anomaly estimation on the petroleum equipment based on the anomaly event relation graph comprises the following steps:
Acquiring the abnormal frequency of the abnormal type according to the related information of the petroleum equipment, calculating the actual abnormal probability of each abnormal type according to the abnormal frequency, acquiring the relation between the petroleum equipment and each abnormal type according to the abnormal event relation diagram, wherein the petroleum equipment corresponds to a root event, the abnormal type corresponds to a sub event, multiplying the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a first relation, adding the actual abnormal probabilities of a plurality of sub events corresponding to the root event to obtain the theoretical abnormal probability of the root event when the root event and the sub event are in a second relation, and taking the theoretical abnormal probability of the root event as the theoretical abnormal probability of the petroleum equipment;
The identification setting module is used for acquiring theoretical abnormal probability of the petroleum equipment in the abnormal estimation result, acquiring the equipment abnormal frequency stored in the first memory, calculating actual abnormal probability according to the equipment abnormal frequency, subtracting the theoretical abnormal probability from the actual abnormal probability to acquire a difference value, setting a first threshold value for the petroleum equipment, setting a first identification for the petroleum equipment if the difference value is greater than or equal to the first threshold value, setting a second identification for the petroleum equipment if the difference value is greater than zero and the difference value is smaller than the first threshold value, and making a third identification for the petroleum equipment if the difference value is smaller than zero;
Wherein, set up the first threshold value for each said petroleum apparatus, including the following step:
Acquiring standard reference information of the petroleum equipment, wherein the standard reference information comprises standard use time and standard abnormal probability, acquiring equipment use rate and equipment use time of the petroleum equipment, acquiring actual use time of the petroleum equipment according to the equipment use rate and the equipment use time, comparing the actual use time with the standard use time, and calculating the first threshold R by a first formula if the actual use time is greater than the standard use time, wherein the first formula is as follows: r= (t 2/t 1-1) p, where t2 is the actual usage time, t1 is the standard usage time, p is the standard anomaly probability, if the actual usage time is less than the standard usage time, calculating the first threshold R with a second formula, where the second formula is: r= (1-t 2/t 1) P, if the actual usage time is equal to the standard usage time, setting the first threshold to zero;
The updating maintenance module is used for making a maintenance scheme for the petroleum equipment according to the identification information, the inspection information and the maintenance information, wherein the identification information comprises the first identification, the second identification and the third identification, and the maintenance scheme comprises an inspection period and maintenance cost;
Wherein, for the petroleum equipment update maintenance scheme, include the following step:
If the identification information of the petroleum equipment is a first identification, acquiring the inspection information of the petroleum equipment, acquiring an inspection period C in the inspection information, setting the inspection period of the petroleum equipment to be C/2, setting the maintenance cost of the petroleum equipment to be twice as high as the original, if the identification information of the petroleum equipment is a second identification, keeping the inspection period of the petroleum equipment and the maintenance cost unchanged, and if the identification information of the petroleum equipment is a third identification, setting the inspection period of the petroleum equipment to be C x 2, and setting the maintenance cost of the petroleum equipment to be half as high as the original.
6. A storage medium storing program instructions, wherein the program instructions, when executed, control a device in which the storage medium is located to perform the method of any one of claims 1-4.
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