CN116560340B - Fault remote session guidance diagnosis system - Google Patents
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- CN116560340B CN116560340B CN202310543167.1A CN202310543167A CN116560340B CN 116560340 B CN116560340 B CN 116560340B CN 202310543167 A CN202310543167 A CN 202310543167A CN 116560340 B CN116560340 B CN 116560340B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24065—Real time diagnostics
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
本发明公开了一种故障远程会话指导诊断系统，包括：故障现场控制单元用于采集故障点数据，对采集的故障点数据进行预处理后向远程指导单元发出请求指导指令；智慧物联云平台用于存储历史数据、故障手册数据，对当前故障点数据进行分析，获取分析报告，为后期故障指导会话室的指导提供技术支持；远程指导单元用于接收请求指导指令，根据请求指导指令与分析报告构建故障指导会话室，基于分析报告为故障指导会话室提供对应的模拟画面数据，在故障指导会话室中专家给运维人员进行故障指导。从而实现对故障消缺现场进行实时沟通指导，及时解决复杂故障问题，进一步强化现场作业安全风险管控。
The invention discloses a fault remote session guidance and diagnosis system, which includes: a fault site control unit for collecting fault point data, preprocessing the collected fault point data and then sending a request guidance instruction to the remote guidance unit; a smart IoT cloud platform It is used to store historical data and fault manual data, analyze current fault point data, obtain analysis reports, and provide technical support for guidance in the later fault guidance session room; the remote guidance unit is used to receive requested guidance instructions and provide guidance and analysis according to the request. The report builds a fault guidance session room, and provides corresponding simulation screen data for the fault guidance session room based on the analysis report. In the fault guidance session room, experts provide fault guidance to operation and maintenance personnel. This enables real-time communication and guidance on fault elimination sites, timely resolution of complex fault issues, and further strengthens on-site operation safety risk management and control.
Description
Technical Field
The invention relates to the technical field of diagnosis, in particular to a fault remote session guidance diagnosis system.
Background
In the fault elimination process, operation and maintenance personnel often encounter various fault problems, common fault problem operation and maintenance personnel can carry out fault elimination processing through a fault manual, but for some problems with higher difficulty or unusual problems, the operation and maintenance personnel do not know how to process, so that the fault elimination process is extremely time-consuming, and the availability of equipment is reduced. For these faults, operators often communicate by telephone or take pictures on site to ask other more experienced operators or manufacturers for the inquiry. Complex fault handling by photographing or telephonic communication, problems exist including: when the network information is not good, the network information cannot be communicated in time, so that the fault cannot be eliminated; the failure phenomenon cannot be accurately described through telephone communication, so that other operation and maintenance personnel cannot accurately guide on-site personnel to perform defect elimination work; the photo is limited by the problems of pixels, definition and transmission, so that the problem that the scene cannot be accurately displayed in time is often caused, and the progress of work for eliminating the defect is delayed.
Accordingly, there is a need to provide a fault remote session guidance diagnostic system.
Disclosure of Invention
The invention provides a fault remote session guidance diagnosis system, which aims to solve the problem that in the fault elimination process in the prior art, operation and maintenance personnel often encounter various fault problems, and the common fault problem operation and maintenance personnel can perform fault elimination processing through a fault manual, but for some problems with higher difficulty or unusual problems, the operation and maintenance personnel do not know how to process, so that the fault elimination process is extremely time-consuming, and the availability of equipment is reduced. For these faults, operators often communicate by telephone or take pictures on site to ask other more experienced operators or manufacturers for the inquiry. Complex fault handling by photographing or telephonic communication, problems exist including: when the network information is not good, the network information cannot be communicated in time, so that the fault cannot be eliminated; the failure phenomenon cannot be accurately described through telephone communication, so that other operation and maintenance personnel cannot accurately guide on-site personnel to perform defect elimination work; the photo is limited by the problems of pixels, definition and transmission, which often results in the problem that the scene cannot be accurately displayed in time, and the problem of delaying the progress of the work of eliminating the defects.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a fault remote session guidance diagnostic system comprising: the intelligent internet of things cloud platform comprises a fault field control unit, an intelligent internet of things cloud platform and a remote guidance unit;
the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit;
the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room;
the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room according to the request guidance instruction and the analysis report, providing corresponding simulation picture data for the fault guidance session room based on the analysis report, and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room.
Wherein the fault site control unit includes: the system comprises a data acquisition module, a data preprocessing module and a first terminal of a session room;
the data acquisition module is used for acquiring data corresponding to a current fault point when an operation and maintenance person encounters a fault problem in the inspection;
the data preprocessing module is used for extracting data corresponding to the current fault point to perform first characteristic data, preprocessing the extracted first characteristic data and transmitting the preprocessed first characteristic data to the intelligent Internet of things cloud platform;
the first terminal of the conversation room is used for displaying the first characteristic data in real time, and an operation and maintenance person obtains a fault defect elimination instruction scheme provided by an expert through the first terminal of the conversation room.
Wherein, wisdom thing allies oneself with management unit includes: the system comprises a database, a fault evaluation module and a remote collaboration management module;
the database is used for storing historical fault point data, fault manual data and analysis report data, and provides corresponding data support for a fault guidance session room;
the fault evaluation module is used for extracting key data corresponding to the first characteristic data and the fault manual data, acquiring second characteristic data, analyzing and evaluating the second characteristic data and acquiring an analysis report;
the remote collaboration management module is used for constructing a matched fault guidance session room for the fault field control unit and the remote guidance unit.
Wherein the remote instruction unit comprises: the second terminal of the conversation room and the remote instruction operation module;
the second terminal of the conversation room is used for displaying analysis report data in real time, and the corresponding conversation room expert provides current fault guidance for operation and maintenance personnel through the second terminal of the conversation room;
the remote guidance operation module is used for operating the second terminal interface of the current session room and the data to be transmitted corresponding to the session room expert.
Wherein, the data acquisition module includes: a fault point pre-judging sub-module;
when operation and maintenance personnel acquire data corresponding to the current fault point, the fault point pre-judging submodule starts a work task, a function map is constructed based on fault manual data in the intelligent Internet of things management unit and the current acquisition data, the position of the current fault point is predicted through the function map, and automatic amplification and ultra-clear shooting is carried out on the position of the current predicted fault point in a shooting process through shooting equipment in the data acquisition module.
Wherein the fault assessment module comprises: a fault assessment model;
the fault evaluation model comprises a key data extraction layer, a fault state identification layer, a fault mode classification layer, a fault maintenance decision layer and a barrier layer to be diagnosed by an expert;
the fault state identification layer carries out data identification processing on the first characteristic data in the key data extraction layer, a mode level to which the current fault belongs is obtained through identification, a decision tree is constructed through the fault mode classification layer, association of the first characteristic data and fault manual data is constructed through the decision tree, second characteristic data is obtained based on an association model, the second characteristic data is analyzed through the fault maintenance decision layer, a corresponding analysis report is obtained, and fault problems to be solved by an expert are extracted through the barrier layer to be diagnosed by the expert.
Wherein constructing the decision tree through the failure mode classification layer comprises:
constructing a machine learning sample data set and an attribute set based on a database, if all samples in the machine learning sample data set belong to equipment fault operation data, a single-node decision tree is formed, and the equipment fault operation data is returned as the category of the machine learning sample data set; if the attribute set is empty or the same value of the machine learning sample data set on the attribute set is obtained, determining that the decision tree is a single-node decision tree, and returning to the most categories in the machine learning sample data set; if the single-node decision tree is not determined, selecting the attribute of the operation fault equipment as the optimal partition; and dividing the machine learning sample data set into a plurality of non-empty machine learning sample data sets according to the corresponding data of any one of the optimal dividing attributes and the corresponding condition of the current acquired data, and finally constructing a decision tree model.
The fault guiding session room is created by remotely connecting a first terminal of the session room and a second terminal of the session room;
the first terminal of the conversation room comprises a working area where operation and maintenance personnel are located and a classification layer where faults are located; the second terminal of the session room comprises a plurality of expert group terminals, and the terminals mark the expert as good as the maintenance fault field, the session guiding task amount, the maintenance success level and the current work arrangement of the expert;
after an operation and maintenance person sends a request instruction through a first terminal of the conversation room, the intelligent Internet of things cloud platform performs intelligent matching of a second terminal of the conversation room according to the current request instruction, acquires an expert terminal with high current maintenance success level, and constructs a fault instruction conversation room.
When the first terminal of the session room and the second terminal of the session room communicate, a format of a communication message is constructed, and corresponding encapsulation and analysis logic is adopted in a communication layer to acquire the encapsulation and the unwrapping of the message; the flow direction of the corresponding data of the conversation room comprises two-way communication of fault point data in a fault field control unit under intelligent guidance and a remote guidance unit, and two-way communication of a conversation room first terminal and a conversation room second terminal under remote guidance, and a specific flow direction of a message is defined by setting a message format, wherein the message format structure comprises a total length, a message type, a request type and a message content;
the total length is the total length of the data of the message, the message type prescribes the flow direction of the message, and the request type determines which logic processing module in the intelligent internet of things cloud platform should process the message content, and the message content is the core data of the message which needs to be processed.
When the first terminal of the session room and the second terminal of the session room communicate, unified authentication is carried out through the service gateway;
when an operation and maintenance person sends a request instruction to a second terminal of the session room through the first terminal of the session room, a layer of filter is added to the service gateway to authenticate the request, the authentication process is to judge whether the request is a request in a white list, if yes, the authentication is not needed, the next filter is directly entered, if not, the authentication is needed, if not, the request is indicated, whether the request carries a login token and the carried token is legal, if the request carries a legal token, the authentication is passed, the request instruction is successfully sent, otherwise, the authentication failure abnormality is directly returned, and the request instruction is sent failure.
Compared with the prior art, the invention has the following advantages:
a fault remote session guidance diagnostic system comprising: the intelligent internet of things cloud platform comprises a fault field control unit, an intelligent internet of things cloud platform and a remote guidance unit; the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit; the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room; the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room according to the request guidance instruction and the analysis report, providing corresponding simulation picture data for the fault guidance session room based on the analysis report, and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room. Therefore, real-time communication guidance is carried out on the fault elimination site, the complex fault problem is solved in time, and the site operation safety risk management and control is further enhanced; through corresponding expert guidance, timeliness and accuracy of fault and other problems in operation and maintenance work are improved, multistage linkage in work is realized, and guarantee is provided for high efficiency of operation and maintenance personnel.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of a fault remote session guidance diagnostic system in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of a fault remote session guidance diagnostic system in accordance with an embodiment of the present invention;
fig. 3 is a block diagram of a fault site control unit in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a fault remote session guidance diagnosis system, which comprises: the intelligent internet of things cloud platform comprises a fault field control unit, an intelligent internet of things cloud platform and a remote guidance unit;
the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit;
the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room;
the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room according to the request guidance instruction and the analysis report, providing corresponding simulation picture data for the fault guidance session room based on the analysis report, and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room.
The working principle of the technical scheme is as follows: the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit; the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room; the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room (referred to as a video session room) according to the request guidance instruction and the analysis report, providing corresponding simulated picture data for the fault guidance session room based on the analysis report (the video session room can display the simulated picture data), and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room.
The beneficial effects of the technical scheme are as follows: the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit; the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room; the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room (referred to as a video session room) according to the request guidance instruction and the analysis report, providing corresponding simulated picture data for the fault guidance session room based on the analysis report (the video session room can display the simulated picture data), and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room. Therefore, real-time communication guidance is carried out on the fault elimination site, the complex fault problem is solved in time, and the site operation safety risk management and control is further enhanced; through corresponding expert guidance, timeliness and accuracy of fault and other problems in operation and maintenance work are improved, multistage linkage in work is realized, and guarantee is provided for high efficiency of operation and maintenance personnel.
In another embodiment, the fail-site control unit includes: the system comprises a data acquisition module, a data preprocessing module and a first terminal of a session room;
the data acquisition module is used for acquiring data corresponding to a current fault point when an operation and maintenance person encounters a fault problem in the inspection;
the data preprocessing module is used for extracting data corresponding to the current fault point to perform first characteristic data, preprocessing the extracted first characteristic data and transmitting the preprocessed first characteristic data to the intelligent Internet of things cloud platform;
the first terminal of the conversation room is used for displaying the first characteristic data in real time, and an operation and maintenance person obtains a fault defect elimination instruction scheme provided by an expert through the first terminal of the conversation room.
The working principle of the technical scheme is as follows: the data acquisition module is used for acquiring data corresponding to a current fault point when an operation and maintenance person encounters a fault problem in inspection (the data comprises video recording of work of the operation equipment through video recording equipment, photographing data of fault sites of the operation equipment through photographing equipment and key operation parameter acquisition data of the operation equipment through a sensor); the data preprocessing module is used for extracting data corresponding to the current fault point to perform first characteristic data (the first characteristic data refers to operation videos, pictures and operation parameters of the fault point, other irrelevant fault data are removed, analysis and processing of the fault point data are facilitated in the later period), and the extracted first characteristic data are preprocessed and then transmitted to the intelligent Internet of things cloud platform; the first terminal of the session room is used for displaying the first characteristic data in real time, and the operation and maintenance personnel obtains a fault defect elimination instruction scheme provided by an expert through the first terminal of the session room (the first terminal of the session room refers to terminal equipment used by the operation and maintenance personnel).
The beneficial effects of the technical scheme are as follows: the data acquisition module is used for acquiring data corresponding to the current fault point when operation and maintenance personnel encounters a fault problem in the inspection process, so that the accuracy of the acquired data and the definition of pixels are ensured; the data preprocessing module is used for extracting data corresponding to the current fault point to perform first characteristic data, preprocessing the extracted first characteristic data and transmitting the preprocessed first characteristic data to the intelligent Internet of things cloud platform, guaranteeing the accuracy of data to be transmitted and improving the progress of defect elimination work; the first terminal of the session room is used for displaying the first characteristic data in real time, an operation and maintenance person obtains a fault defect elimination guiding scheme provided by an expert through the first terminal of the session room, and the expert guides the fault point to point, so that scene requirements such as accident tracing are effectively met, and field operation safety risk management and control is further strengthened.
In another embodiment, the intelligent thing networking management unit includes: the system comprises a database, a fault evaluation module and a remote collaboration management module;
the database is used for storing historical fault point data, fault manual data and analysis report data, and provides corresponding data support for a fault guidance session room;
the fault evaluation module is used for extracting key data corresponding to the first characteristic data and the fault manual data, acquiring second characteristic data, analyzing and evaluating the second characteristic data and acquiring an analysis report;
the remote collaboration management module is used for constructing a matched fault guidance session room for the fault field control unit and the remote guidance unit.
The working principle of the technical scheme is as follows: the database is used for storing historical fault point data, fault manual data and analysis report data, and provides corresponding data support for a fault guidance session room; the fault evaluation module is used for extracting key data corresponding to the first characteristic data and the fault manual data (carrying out data analysis on the first characteristic data, matching an analysis result with the fault manual data, determining a fault type), acquiring second characteristic data (referring to the fault type), carrying out analysis and evaluation on the second characteristic data (analyzing the type of the fault, analyzing different points in the fault manual data and analyzing the different points) and acquiring an analysis report; the remote collaboration management module is used for constructing a matched fault guidance session room for the fault field control unit and the remote guidance unit (the session room second terminal in the remote guidance unit comprises a plurality of second terminals which are intelligently matched by expert according to the fault type, difficulty and current working state of the expert).
The beneficial effects of the technical scheme are as follows: the database is used for storing historical fault point data, fault manual data and analysis report data, and provides corresponding data support for a fault guidance session room; the fault evaluation module is used for extracting key data corresponding to the first characteristic data and the fault manual data, acquiring second characteristic data, analyzing and evaluating the second characteristic data and acquiring an analysis report; the remote collaboration management module is used for constructing a matched fault guidance session room for the fault field control unit and the remote guidance unit. The method has the advantages of effectively meeting scene requirements such as accident tracing and the like and further strengthening field operation safety risk management and control.
In another embodiment, the remote instruction unit includes: the second terminal of the conversation room and the remote instruction operation module;
the second terminal of the conversation room is used for displaying analysis report data in real time, and the corresponding conversation room expert provides current fault guidance for operation and maintenance personnel through the second terminal of the conversation room;
the remote guidance operation module is used for operating the second terminal interface of the current session room and the data to be transmitted corresponding to the session room expert.
The working principle of the technical scheme is as follows: the second terminal of the conversation room is used for displaying analysis report data in real time, and the corresponding conversation room expert provides current fault guidance for operation and maintenance personnel through the second terminal of the conversation room; the remote guidance operation module is used for operating the second terminal interface of the current session room and the data to be transmitted corresponding to the session room expert.
The beneficial effects of the technical scheme are as follows: the second terminal of the conversation room is used for displaying analysis report data in real time, and the corresponding conversation room expert provides current fault guidance for operation and maintenance personnel through the second terminal of the conversation room; the remote guidance operation module is used for operating the second terminal interface of the current session room and the data to be transmitted corresponding to the session room expert. The method has the advantages of effectively meeting scene requirements such as accident tracing and the like and further strengthening field operation safety risk management and control.
In another embodiment, the data acquisition module comprises: a fault point pre-judging sub-module;
when operation and maintenance personnel acquire data corresponding to the current fault point, the fault point pre-judging submodule starts a work task, a function map is constructed based on fault manual data in the intelligent Internet of things management unit and the current acquisition data, the position of the current fault point is predicted through the function map, and automatic amplification and ultra-clear shooting is carried out on the position of the current predicted fault point in a shooting process through shooting equipment in the data acquisition module.
The working principle of the technical scheme is as follows: when operation and maintenance personnel acquire data corresponding to the current fault point, the fault point pre-judging submodule starts a work task, a function map is constructed based on fault manual data in the intelligent Internet of things management unit and the current acquisition data, the position of the current fault point is predicted through the function map, and automatic amplification and ultra-clear shooting is carried out on the position of the current predicted fault point in a shooting process through shooting equipment in the data acquisition module.
The beneficial effects of the technical scheme are as follows: when operation and maintenance personnel acquire data corresponding to the current fault point, the fault point pre-judging submodule starts a work task, a function map is constructed based on fault manual data in the intelligent Internet of things management unit and the current acquisition data, the position of the current fault point is predicted through the function map, and automatic amplification and ultra-clear shooting is carried out on the position of the current predicted fault point in a shooting process through shooting equipment in the data acquisition module. Therefore, the problem of definition of the fault photo is effectively solved, the problem of site accurate display is effectively solved, and the progress of defect elimination work is improved.
In another embodiment, the fault assessment module includes: a fault assessment model;
the fault evaluation model comprises a key data extraction layer, a fault state identification layer, a fault mode classification layer, a fault maintenance decision layer and a barrier layer to be diagnosed by an expert;
the fault state identification layer carries out data identification processing on the first characteristic data in the key data extraction layer, a mode level to which the current fault belongs is obtained through identification, a decision tree is constructed through the fault mode classification layer, association of the first characteristic data and fault manual data is constructed through the decision tree, second characteristic data is obtained based on an association model, the second characteristic data is analyzed through the fault maintenance decision layer, a corresponding analysis report is obtained, and fault problems to be solved by an expert are extracted through the barrier layer to be diagnosed by the expert.
The working principle of the technical scheme is as follows: the fault state identification layer carries out data identification processing on the first characteristic data in the key data extraction layer, a mode level to which the current fault belongs is obtained through identification, a decision tree is constructed through the fault mode classification layer, association of the first characteristic data and fault manual data is constructed through the decision tree, second characteristic data is obtained based on an association model, the second characteristic data is analyzed through the fault maintenance decision layer, a corresponding analysis report is obtained, and fault problems to be solved by an expert are extracted through the barrier layer to be diagnosed by the expert.
The beneficial effects of the technical scheme are as follows: the fault state identification layer carries out data identification processing on the first characteristic data in the key data extraction layer, a mode level to which the current fault belongs is obtained through identification, a decision tree is constructed through the fault mode classification layer, association of the first characteristic data and fault manual data is constructed through the decision tree, second characteristic data is obtained based on an association model, the second characteristic data is analyzed through the fault maintenance decision layer, a corresponding analysis report is obtained, and fault problems to be solved by an expert are extracted through the barrier layer to be diagnosed by the expert. And convenience is provided for an expert to analyze fault reasons and provide fault solutions, and the progress of defect elimination work is improved.
In another embodiment, building a decision tree through a failure mode classification layer includes:
constructing a machine learning sample data set and an attribute set based on a database, if all samples in the machine learning sample data set belong to equipment fault operation data, a single-node decision tree is formed, and the equipment fault operation data is returned as the category of the machine learning sample data set; if the attribute set is empty or the same value of the machine learning sample data set on the attribute set is obtained, determining that the decision tree is a single-node decision tree, and returning to the most categories in the machine learning sample data set; if the single-node decision tree is not determined, selecting the attribute of the operation fault equipment as the optimal partition; and dividing the machine learning sample data set into a plurality of non-empty machine learning sample data sets according to the corresponding data of any one of the optimal dividing attributes and the corresponding condition of the current acquired data, and finally constructing a decision tree model.
The working principle of the technical scheme is as follows: constructing a machine learning sample data set and an attribute set based on a database, if all samples in the machine learning sample data set belong to equipment fault operation data, a single-node decision tree is formed, and the equipment fault operation data is returned as the category of the machine learning sample data set; if the attribute set is empty or the same value of the machine learning sample data set on the attribute set is obtained, determining that the decision tree is a single-node decision tree, and returning to the most categories in the machine learning sample data set; if the single-node decision tree is not determined, selecting the attribute of the operation fault equipment as the optimal partition; and dividing the machine learning sample data set into a plurality of non-empty machine learning sample data sets according to the corresponding data of any one of the optimal dividing attributes and the corresponding condition of the current acquired data, and finally constructing a decision tree model.
The beneficial effects of the technical scheme are as follows: constructing a machine learning sample data set and an attribute set based on a database, if all samples in the machine learning sample data set belong to equipment fault operation data, a single-node decision tree is formed, and the equipment fault operation data is returned as the category of the machine learning sample data set; if the attribute set is empty or the same value of the machine learning sample data set on the attribute set is obtained, determining that the decision tree is a single-node decision tree, and returning to the most categories in the machine learning sample data set; if the single-node decision tree is not determined, selecting the attribute of the operation fault equipment as the optimal partition; and dividing the machine learning sample data set into a plurality of non-empty machine learning sample data sets according to the corresponding data of any one of the optimal dividing attributes and the corresponding condition of the current acquired data, and finally constructing a decision tree model. And convenience is provided for an expert to analyze fault reasons and provide fault solutions, and the progress of defect elimination work is improved.
In another embodiment, the fault guiding session room is created by remotely connecting the session room first terminal and the session room second terminal;
the first terminal of the conversation room comprises a working area where operation and maintenance personnel are located and a classification layer where faults are located; the second terminal of the session room comprises a plurality of expert group terminals, and the terminals mark the expert as good as the maintenance fault field, the session guiding task amount, the maintenance success level and the current work arrangement of the expert;
after an operation and maintenance person sends a request instruction through a first terminal of the conversation room, the intelligent Internet of things cloud platform performs intelligent matching of a second terminal of the conversation room according to the current request instruction, acquires an expert terminal with high current maintenance success level, and constructs a fault instruction conversation room.
The working principle of the technical scheme is as follows: the first terminal of the conversation room comprises a working area where operation and maintenance personnel are located and a classification layer where faults are located; the second terminal of the session room comprises a plurality of expert group terminals, and the terminals mark the expert as good as the maintenance fault field, the session guiding task amount, the maintenance success level and the current work arrangement of the expert; after an operation and maintenance person sends a request instruction through a first terminal of the conversation room, the intelligent Internet of things cloud platform performs intelligent matching of a second terminal of the conversation room according to the current request instruction, acquires an expert terminal with high current maintenance success level, and constructs a fault instruction conversation room. And convenience is provided for an expert to analyze fault reasons and provide fault solutions, and the progress of defect elimination work is improved.
The beneficial effects of the technical scheme are as follows: the first terminal of the conversation room comprises a working area where operation and maintenance personnel are located and a classification layer where faults are located; the second terminal of the session room comprises a plurality of expert group terminals, and the terminals mark the expert as good as the maintenance fault field, the session guiding task amount, the maintenance success level and the current work arrangement of the expert; after an operation and maintenance person sends a request instruction through a first terminal of the conversation room, the intelligent Internet of things cloud platform performs intelligent matching of a second terminal of the conversation room according to the current request instruction, acquires an expert terminal with high current maintenance success level, and constructs a fault instruction conversation room. And convenience is provided for an expert to analyze fault reasons and provide fault solutions, and the progress of defect elimination work is improved.
In another embodiment, when the first terminal of the session room and the second terminal of the session room communicate, a format of a communication message is constructed, and corresponding encapsulation and analysis logic is adopted in a communication layer to obtain the encapsulation and the unwrapping of the message; the flow direction of the corresponding data of the conversation room comprises two-way communication of fault point data in a fault field control unit under intelligent guidance and a remote guidance unit, and two-way communication of a conversation room first terminal and a conversation room second terminal under remote guidance, and a specific flow direction of a message is defined by setting a message format, wherein the message format structure comprises a total length, a message type, a request type and a message content;
the total length is the total length of the data of the message, the message type prescribes the flow direction of the message, and the request type determines which logic processing module in the intelligent internet of things cloud platform should process the message content, and the message content is the core data of the message which needs to be processed.
The working principle of the technical scheme is as follows: adopting corresponding encapsulation and analysis logic in a communication layer to obtain the encapsulation and the unwrapping of the message; the flow direction of the corresponding data of the conversation room comprises two-way communication of fault point data in a fault field control unit under intelligent guidance and a remote guidance unit, and two-way communication of a conversation room first terminal and a conversation room second terminal under remote guidance, and a specific flow direction of a message is defined by setting a message format, wherein the message format structure comprises a total length, a message type, a request type and a message content; the total length is the total length of the data of the message, the message type prescribes the flow direction of the message, and the request type determines which logic processing module in the intelligent internet of things cloud platform should process the message content, and the message content is the core data of the message which needs to be processed.
In order to increase the speed of communication transmission data, a CRC algorithm structure table is adopted for checking, the data stream arranged according to bytes is expressed as a mathematical polynomial in the CRC algorithm structure table, and the data stream is B n B n-1 B n-2 ......B 1 B 0 The CRC algorithm expression is:
H＝B n *256 n +B n-1 *256 n-1 +B n-2 *256 n-2 +...+B 1 *256+B 0
where H represents the CRC algorithm expression, "+" represents the exclusive OR symbol, 256 represents 8 bits to the left, 256 n The power n of 256 is represented.
And CRC redundant bits of data bytes or data blocks transmitted and received in communication are calculated through a CRC table look-up function, so that the data transmission speed is effectively improved.
The beneficial effects of the technical scheme are as follows: adopting corresponding encapsulation and analysis logic in a communication layer to obtain the encapsulation and the unwrapping of the message; the flow direction of the corresponding data of the conversation room comprises two-way communication of fault point data in a fault field control unit under intelligent guidance and a remote guidance unit, and two-way communication of a conversation room first terminal and a conversation room second terminal under remote guidance, and a specific flow direction of a message is defined by setting a message format, wherein the message format structure comprises a total length, a message type, a request type and a message content; the total length is the total length of the data of the message, the message type prescribes the flow direction of the message, and the request type determines which logic processing module in the intelligent internet of things cloud platform should process the message content, and the message content is the core data of the message which needs to be processed. The stability of remote communication is ensured.
In another embodiment, when the first terminal of the session room and the second terminal of the session room communicate, unified authentication is performed through the service gateway;
when an operation and maintenance person sends a request instruction to a second terminal of the session room through the first terminal of the session room, a layer of filter is added to the service gateway to authenticate the request, the authentication process is to judge whether the request is a request in a white list, if yes, the authentication is not needed, the next filter is directly entered, if not, the authentication is needed, if not, the request is indicated, whether the request carries a login token and the carried token is legal, if the request carries a legal token, the authentication is passed, the request instruction is successfully sent, otherwise, the authentication failure abnormality is directly returned, and the request instruction is sent failure.
The working principle of the technical scheme is as follows: when an operation and maintenance person sends a request instruction to a second terminal of the session room through the first terminal of the session room, a layer of filter is added to the service gateway to authenticate the request, the authentication process is to judge whether the request is a request in a white list, if yes, the authentication is not needed, the next filter is directly entered, if not, the authentication is needed, if not, the request is indicated, whether the request carries a login token and the carried token is legal, if the request carries a legal token, the authentication is passed, the request instruction is successfully sent, otherwise, the authentication failure abnormality is directly returned, and the request instruction is sent failure.
The beneficial effects of the technical scheme are as follows: when an operation and maintenance person sends a request instruction to a second terminal of the session room through the first terminal of the session room, a layer of filter is added to the service gateway to authenticate the request, the authentication process is to judge whether the request is a request in a white list, if yes, the authentication is not needed, the next filter is directly entered, if not, the authentication is needed, if not, the request is indicated, whether the request carries a login token and the carried token is legal, if the request carries a legal token, the authentication is passed, the request instruction is successfully sent, otherwise, the authentication failure abnormality is directly returned, and the request instruction is sent failure. The safety of communication is ensured.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. A fault remote session guidance diagnostic system, comprising: the intelligent internet of things cloud platform comprises a fault field control unit, an intelligent internet of things cloud platform and a remote guidance unit;
the fault site control unit is used for collecting fault point data, preprocessing the collected fault point data and then sending a request instruction to the remote instruction unit;
the intelligent internet of things cloud platform is used for storing historical data and fault manual data, analyzing the current fault point data, acquiring an analysis report and providing technical support for guidance of a later fault guidance session room;
the remote guidance unit is used for receiving the request guidance instruction, constructing a fault guidance session room according to the request guidance instruction and the analysis report, providing corresponding simulated picture data for the fault guidance session room based on the analysis report, and performing fault guidance on operation and maintenance personnel by a special person in the fault guidance session room;
the fault site control unit includes: the system comprises a data acquisition module, a data preprocessing module and a first terminal of a session room;
the data acquisition module is used for acquiring data corresponding to a current fault point when an operation and maintenance person encounters a fault problem in the inspection;
the data preprocessing module is used for extracting first characteristic data of data corresponding to the current fault point, preprocessing the extracted first characteristic data and transmitting the preprocessed first characteristic data to the intelligent Internet of things cloud platform, wherein the first characteristic data refer to operation videos, pictures and operation parameters of the fault point;
the first terminal of the conversation room is used for displaying the first characteristic data in real time, and an operation and maintenance person obtains a fault defect elimination instruction scheme provided by an expert through the first terminal of the conversation room;
the data acquisition module comprises: a fault point pre-judging sub-module;
when operation and maintenance personnel acquire data corresponding to the current fault point, the fault point pre-judging submodule starts a work task, a function map is constructed based on fault manual data in the intelligent Internet of things cloud platform and the current acquisition data, the position of the current fault point is predicted through the function map, and automatic amplification ultra-clear shooting is carried out on the position of the current predicted fault point in a shooting process through shooting equipment in the data acquisition module.
2. The fault remote session guidance diagnostic system of claim 1, wherein the intelligent thing networking cloud platform comprises: the system comprises a database, a fault evaluation module and a remote collaboration management module;
the database is used for storing historical fault point data, fault manual data and analysis report data, and provides corresponding data support for a fault guidance session room;
the fault evaluation module is used for extracting key data corresponding to the first characteristic data and the fault manual data, acquiring second characteristic data, analyzing and evaluating the second characteristic data and acquiring an analysis report;
the remote collaboration management module is used for constructing a matched fault guidance session room for the fault field control unit and the remote guidance unit.
3. The fault remote session guidance diagnostic system of claim 1, wherein the remote guidance unit comprises: the second terminal of the conversation room and the remote instruction operation module;
the second terminal of the conversation room is used for displaying analysis report data in real time, and the corresponding conversation room expert provides current fault guidance for operation and maintenance personnel through the second terminal of the conversation room;
the remote guidance operation module is used for operating the second terminal interface of the current session room and the data to be transmitted corresponding to the session room expert.
4. The fault remote session guidance diagnostic system of claim 2, wherein the fault assessment module comprises: a fault assessment model;
the fault evaluation model comprises a key data extraction layer, a fault state identification layer, a fault mode classification layer, a fault maintenance decision layer and a barrier layer to be diagnosed by an expert;
the fault state identification layer carries out data identification processing on the first characteristic data in the key data extraction layer, a mode level to which the current fault belongs is obtained through identification, a decision tree is constructed through the fault mode classification layer, association of the first characteristic data and fault manual data is constructed through the decision tree, second characteristic data is obtained based on an association model, the second characteristic data is analyzed through the fault maintenance decision layer, a corresponding analysis report is obtained, and fault problems to be solved by an expert are extracted through the barrier layer to be diagnosed by the expert.
5. The fault remote session guidance diagnostic system of claim 4, wherein constructing a decision tree through a fault mode classification layer comprises:
constructing a machine learning sample data set and an attribute set based on a database, if all samples in the machine learning sample data set belong to equipment fault operation data, a single-node decision tree is formed, and the equipment fault operation data is returned as the category of the machine learning sample data set; if the attribute set is empty or the same value of the machine learning sample data set on the attribute set is obtained, determining that the decision tree is a single-node decision tree, and returning to the most categories in the machine learning sample data set; if the single-node decision tree is not determined, selecting the attribute of the operation fault equipment as the optimal partition; and dividing the machine learning sample data set into a plurality of non-empty machine learning sample data sets according to the corresponding data of any one of the optimal dividing attributes and the corresponding condition of the current acquired data, and finally constructing a decision tree model.
6. The fault remote session guidance diagnostic system of claim 2, wherein the fault guidance session room is created by remotely connecting a session room first terminal, a session room second terminal;
the first terminal of the conversation room comprises a working area where operation and maintenance personnel are located and a classification layer where faults are located; the second terminal of the session room comprises a plurality of expert group terminals, and the terminals mark the expert as good as the maintenance fault field, the session guiding task amount, the maintenance success level and the current work arrangement of the expert;
after an operation and maintenance person sends a request instruction through a first terminal of the conversation room, the intelligent Internet of things cloud platform performs intelligent matching of a second terminal of the conversation room according to the current request instruction, acquires an expert terminal with high current maintenance success level, and constructs a fault instruction conversation room.
7. The fault remote session guidance diagnosis system according to claim 6, wherein when the first terminal of the session room and the second terminal of the session room communicate, a format of a communication message is constructed, and corresponding encapsulation and parsing logic is adopted in the communication layer to obtain the encapsulation and unpacking of the message; the flow direction of the corresponding data of the conversation room comprises two-way communication of fault point data in a fault field control unit under intelligent guidance and a remote guidance unit, and two-way communication of a conversation room first terminal and a conversation room second terminal under remote guidance, and a specific flow direction of a message is defined by setting a message format, wherein the message format structure comprises a total length, a message type, a request type and a message content;
the total length is the total length of the data of the message, the message type prescribes the flow direction of the message, and the request type determines which logic processing module in the intelligent internet of things cloud platform should process the message content, and the message content is the core data of the message which needs to be processed.
8. The fault remote session guidance diagnostic system of claim 7, wherein the unified authentication is performed by the service gateway while the first session room terminal and the second session room terminal are in communication;
when an operation and maintenance person sends a request instruction to a second terminal of the session room through the first terminal of the session room, a layer of filter is added to the service gateway to authenticate the request, the authentication process is to judge whether the request is a request in a white list, if yes, the authentication is not needed, the next filter is directly entered, if not, the authentication is needed, if not, the request is indicated, whether the request carries a login token and the carried token is legal, if the request carries a legal token, the authentication is passed, the request instruction is successfully sent, otherwise, the authentication failure abnormality is directly returned, and the request instruction is sent failure.
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