CN113033195A - Method for generating scheduling operation sequence by intelligently analyzing overhaul application ticket - Google Patents
Method for generating scheduling operation sequence by intelligently analyzing overhaul application ticket Download PDFInfo
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- CN113033195A CN113033195A CN202110275396.0A CN202110275396A CN113033195A CN 113033195 A CN113033195 A CN 113033195A CN 202110275396 A CN202110275396 A CN 202110275396A CN 113033195 A CN113033195 A CN 113033195A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/253—Grammatical analysis; Style critique
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/042—Knowledge-based neural networks; Logical representations of neural networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket, which comprises the following steps: natural language parsing: identifying and analyzing the work task, the work content and the comment information of each room of the overhaul application ticket; word segmentation technology: performing word segmentation processing on the key information identified by analysis, and performing association fusion of IDs on the operating equipment; power rule knowledge base: deep learning is carried out on historical data such as scheduling rules, protection rules, overhaul and operation, and a rule knowledge base is established; the intelligent inference machine: and the intelligent reasoning overhaul application ticket automatically generates a scheduling operation sequence. The invention reduces the working pressure of the regulating and controlling operation personnel and improves the working efficiency of the regulating and controlling operation and the levels of intellectualization and safety.
Description
Technical Field
The invention relates to a method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket.
Background
Under the regulation and control integrated mode, the centralized monitoring unattended mode of the transformer substation is comprehensively implemented, and the decision and operation pressure faced by the regulation and control operators is gradually increased. The existing scheduling technology system is still mainly based on an experience type and manual analysis type scheduling mode, although a regulation and control center concentrates various power grid operation data, regulation specifications, treatment schemes and the like, a computer-recognizable logic model is lacked among the data/schemes, daily treatment mainly comprises manual experience, operators are required to perform a large amount of experience knowledge association, a large amount of repetitive 'human brain work' is needed, and a large amount of manual operation is required to generate a related operation sequence. Under a large amount of manual operation, the inevitable daily operation has the possibility of misoperation. Therefore, the operation sequence is automatically generated through the computerization, systematization and intellectualization of manual experience in the regulation and control operation of the power grid, the combination of network topology, operation experience and scheduling regulation specification, intelligent analysis and maintenance application and verification such as five-prevention logic judgment. The working pressure of regulation and control operators is reduced, and the working efficiency of regulation and control operation and the levels of intellectualization and safety are improved.
Disclosure of Invention
The invention aims to provide a method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket, which can improve the working efficiency of regulation and control operation and the level of intellectualization and safety.
The technical solution of the invention is as follows:
a method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket is characterized by comprising the following steps: the method comprises the following steps:
natural language parsing: identifying and analyzing the work task, the work content and the comment information of each room of the overhaul application ticket;
word segmentation technology: performing word segmentation processing on the key information identified by analysis, and performing association fusion of IDs on the operating equipment;
power rule knowledge base: deep learning is carried out on historical data such as scheduling rules, protection rules, overhaul and operation, and a rule knowledge base is established;
the intelligent inference machine: and the intelligent reasoning overhaul application ticket automatically generates a scheduling operation sequence.
The method comprises the steps of adopting a natural language processing technology to identify keywords in various structured and unstructured electric power information, achieving automatic association matching of the keywords and equipment information through a keyword library and a word segmentation technology, processing and cleaning irregular data into standard data which can be understood by a computer, achieving establishment of a rule knowledge base through a self-learning technology, and carrying out automatic and intelligent standard analysis on the data information according to an intelligent inference machine to generate a scheduling operation sequence.
And establishing an equipment operation data association relation by taking equipment as a center, establishing an association relation between maintenance information and operation information equipment in a mode of positioning main equipment, and associating the maintenance information and the operation information equipment with the equipment according to the analyzed key words and the feature point set, thereby realizing the construction of a maintenance application analysis model and a scheduling operation sequence generation model.
Summarizing and summarizing related power knowledge points based on expert knowledge, and constructing a knowledge rule learning model; and acquiring related professional knowledge of maintenance based on analysis, extracting maintenance information, operation specifications and wiring mode detailed information related to equipment, and finishing a knowledge rule base.
In the analysis process, different writing habits of various characteristic points are adapted. Automatically reducing the range of the matched equipment through a plant station, the type of the equipment and the voltage grade; then, extracting the serial numbers which appear in a certain range before and after the equipment type and accord with a certain characteristic point rule, and automatically associating the serial numbers with the equipment library model; finally, checking through a topological model; in the process of equipment analysis, the situation of incomplete information needs to be considered, and automatic completion through other information needs to be considered.
Based on the constructed neural network analysis model and the expert rule knowledge base, on the basis of the power grid topology, the power failure range and safety measures are analyzed according to the actual wiring mode and the operation mode of equipment in the power grid, five-prevention logic error-prevention verification is carried out, and possible danger point prompts, cautions and related notification and annotation commands are given.
The invention realizes the fast and accurate identification of the equipment to be subjected to the operations such as maintenance and the like in the maintenance application by taking the model data maintenance application data, the electric power rule information and other basic data as analysis bases, and ensures the accuracy and the uniqueness of the identification through the equipment ID. Meanwhile, information such as work content, range and the like of maintenance application can be automatically and intelligently analyzed through a natural language analysis technology, and an operation command sequence is automatically analyzed and generated by combining equipment topology information.
The invention establishes an operation task inference machine, automatically analyzes the content obtained by analyzing the maintenance application by combining various wiring modes and operation modes suitable for a power grid, and automatically generates an operation sequence conforming to the operation standard rule by combining an operation ticket forming rule base established by a system.
By the method and the system, operators can generate a complete operation sequence based on maintenance application intelligent analysis, the workload of manual operation is greatly reduced, the working efficiency of the operators and the intelligent level of power grid operation are improved, the operation sequence is generated, meanwhile, syntax verification and safety verification of topology five-prevention and intelligent error-proof verification such as power flow verification and stable calculation are combined, and the safe operation level of the power grid is greatly improved.
Drawings
The invention is further illustrated by the following figures and examples.
FIG. 1 is a schematic flow diagram of one embodiment of the present invention.
Detailed Description
A method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket comprises the following contents:
natural language parsing: identifying and analyzing the work task, the work content and the comment information of each room of the overhaul application ticket;
word segmentation technology: performing word segmentation processing on the key information identified by analysis, and performing association fusion of IDs on the operating equipment;
power rule knowledge base: deep learning is carried out on historical data such as scheduling rules, protection rules, overhaul and operation, and a rule knowledge base is established;
the intelligent inference machine: and the intelligent reasoning overhaul application ticket automatically generates a scheduling operation sequence.
The method comprises the steps of adopting a natural language processing technology to identify keywords in various structured and unstructured electric power information, achieving automatic association matching of the keywords and equipment information through a keyword library and a word segmentation technology, processing and cleaning irregular data into standard data which can be understood by a computer, achieving establishment of a rule knowledge base through a self-learning technology, and carrying out automatic and intelligent standard analysis on the data information according to an intelligent inference machine to generate a scheduling operation sequence.
And establishing an equipment operation data association relation by taking equipment as a center, establishing an association relation between maintenance information and operation information equipment in a mode of positioning main equipment, and associating the maintenance information and the operation information equipment with the equipment according to the analyzed key words and the feature point set, thereby realizing the construction of a maintenance application analysis model and a scheduling operation sequence generation model.
Summarizing and summarizing related power knowledge points based on expert knowledge, and constructing a knowledge rule learning model; and acquiring related professional knowledge of maintenance based on analysis, extracting maintenance information, operation specifications and wiring mode detailed information related to equipment, and finishing a knowledge rule base.
For example, the overhaul information relates to the analysis work of several types of basic characteristic points such as plant stations, voltage levels, equipment types and the like. In the analysis process, different writing habits of various characteristic points are adapted. Automatically reducing the range of the matched equipment through a plant station, the type of the equipment and the voltage grade; then, extracting the serial numbers which appear in a certain range before and after the equipment type and accord with a certain characteristic point rule, and automatically associating the serial numbers with the equipment library model; finally, checking through a topological model; in the process of equipment analysis, the situation of incomplete information needs to be considered, and automatic completion through other information needs to be considered.
Based on the constructed neural network analysis model and the expert rule knowledge base, on the basis of the power grid topology, the power failure range and safety measures are analyzed according to the actual wiring mode and the operation mode of equipment in the power grid, five-prevention logic error-prevention verification is carried out, and possible danger point prompts, cautions and related notification and annotation commands are given.
Claims (7)
1. A method for generating a scheduling operation sequence by intelligently analyzing an overhaul application ticket is characterized by comprising the following steps: the method comprises the following steps:
natural language parsing: identifying and analyzing the work task, the work content and the comment information of each room of the overhaul application ticket;
word segmentation technology: performing word segmentation processing on the key information identified by analysis, and performing association fusion of IDs on the operating equipment;
power rule knowledge base: deep learning is carried out on historical data such as scheduling rules, protection rules, overhaul and operation, and a rule knowledge base is established;
the intelligent inference machine: and the intelligent reasoning overhaul application ticket automatically generates a scheduling operation sequence.
2. The method of intelligently parsing a service application ticket generating and scheduling operation sequence of claim 1, wherein: the method comprises the steps of adopting a natural language processing technology to identify keywords in various structured and unstructured electric power information, achieving automatic association matching of the keywords and equipment information through a keyword library and a word segmentation technology, processing and cleaning irregular data into standard data which can be understood by a computer, achieving establishment of a rule knowledge base through a self-learning technology, and carrying out automatic and intelligent standard analysis on the data information according to an intelligent inference machine to generate a scheduling operation sequence.
3. The method of intelligently parsing a service application ticket generating and scheduling operation sequence of claim 1, wherein: and establishing an equipment operation data association relation by taking equipment as a center, establishing an association relation between maintenance information and operation information equipment in a mode of positioning main equipment, and associating the maintenance information and the operation information equipment with the equipment according to the analyzed key words and the feature point set, thereby realizing the construction of a maintenance application analysis model and a scheduling operation sequence generation model.
4. The method of intelligently parsing a service application ticket generating and scheduling operation sequence of claim 1, wherein: summarizing and summarizing related power knowledge points based on expert knowledge, and constructing a knowledge rule learning model; and acquiring related professional knowledge of maintenance based on analysis, extracting maintenance information, operation specifications and wiring mode detailed information related to equipment, and finishing a knowledge rule base.
5. The method of intelligently parsing a service application ticket generating and scheduling operation sequence of claim 1, wherein: in the analysis process, different writing habits of various characteristic points are adapted.
6. Automatically reducing the range of the matched equipment through a plant station, the type of the equipment and the voltage grade; then, extracting the serial numbers which appear in a certain range before and after the equipment type and accord with a certain characteristic point rule, and automatically associating the serial numbers with the equipment library model; finally, checking through a topological model; in the process of equipment analysis, the situation of incomplete information needs to be considered, and automatic completion through other information needs to be considered.
7. The method of intelligently parsing a service application ticket generating and scheduling operation sequence of claim 1, wherein: based on the constructed neural network analysis model and the expert rule knowledge base, on the basis of the power grid topology, the power failure range and safety measures are analyzed according to the actual wiring mode and the operation mode of equipment in the power grid, five-prevention logic error-prevention verification is carried out, and possible danger point prompts, cautions and related notification and annotation commands are given.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113792548A (en) * | 2021-08-30 | 2021-12-14 | 国网天津市电力公司 | Automatic cover generation system and method based on text word segmentation and statistical verification |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761624A (en) * | 2014-01-28 | 2014-04-30 | 国网安徽省电力公司 | Implementing method of integrated power grid dispatching operation intelligent mistaken-early-warning preventing system |
| US20150095331A1 (en) * | 2012-12-21 | 2015-04-02 | Cloud Computing Center Chinese Academy Of Sciences | Establishing and querying methods of knowledge library engine based on emergency management |
| CN111832977A (en) * | 2020-07-30 | 2020-10-27 | 广东电网有限责任公司 | Maintenance application automatic ticketing method based on natural language parsing |
| CN112134310A (en) * | 2020-09-18 | 2020-12-25 | 贵州电网有限责任公司 | Big data-based artificial intelligent power grid regulation and control operation method and system |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150095331A1 (en) * | 2012-12-21 | 2015-04-02 | Cloud Computing Center Chinese Academy Of Sciences | Establishing and querying methods of knowledge library engine based on emergency management |
| CN103761624A (en) * | 2014-01-28 | 2014-04-30 | 国网安徽省电力公司 | Implementing method of integrated power grid dispatching operation intelligent mistaken-early-warning preventing system |
| CN111832977A (en) * | 2020-07-30 | 2020-10-27 | 广东电网有限责任公司 | Maintenance application automatic ticketing method based on natural language parsing |
| CN112134310A (en) * | 2020-09-18 | 2020-12-25 | 贵州电网有限责任公司 | Big data-based artificial intelligent power grid regulation and control operation method and system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113792548A (en) * | 2021-08-30 | 2021-12-14 | 国网天津市电力公司 | Automatic cover generation system and method based on text word segmentation and statistical verification |
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