CN113095050A - Intelligent ticketing method, system, equipment and storage medium - Google Patents
Intelligent ticketing method, system, equipment and storage medium Download PDFInfo
- Publication number
- CN113095050A CN113095050A CN202110419147.4A CN202110419147A CN113095050A CN 113095050 A CN113095050 A CN 113095050A CN 202110419147 A CN202110419147 A CN 202110419147A CN 113095050 A CN113095050 A CN 113095050A
- Authority
- CN
- China
- Prior art keywords
- word segmentation
- overhaul
- content
- application information
- ticketed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 71
- 238000003860 storage Methods 0.000 title claims abstract description 9
- 230000011218 segmentation Effects 0.000 claims abstract description 101
- 238000012545 processing Methods 0.000 claims abstract description 43
- 238000004458 analytical method Methods 0.000 claims abstract description 23
- 238000012423 maintenance Methods 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000004140 cleaning Methods 0.000 claims description 60
- 238000004422 calculation algorithm Methods 0.000 claims description 25
- 230000008094 contradictory effect Effects 0.000 claims description 13
- 238000012937 correction Methods 0.000 claims description 13
- 230000002457 bidirectional effect Effects 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 9
- 238000007689 inspection Methods 0.000 description 8
- 230000014509 gene expression Effects 0.000 description 7
- 238000007796 conventional method Methods 0.000 description 6
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 238000001914 filtration Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000007635 classification algorithm Methods 0.000 description 3
- 238000000354 decomposition reaction Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 239000010410 layer Substances 0.000 description 3
- 238000012706 support-vector machine Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 238000002955 isolation Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000002356 single layer Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/174—Form filling; Merging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
-
- 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
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- 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
- G06Q10/10—Office automation; Time management
-
- 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
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- 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
Abstract
The invention discloses an intelligent ticketing method, an intelligent ticketing system, intelligent ticketing equipment and a storage medium, and relates to the technical field of power systems. The method comprises the following steps: acquiring to-be-ticketed overhaul application information; performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain word segmentation results of overhaul contents; performing label analysis according to the word segmentation result to obtain a structured object associated with the power grid model; and matching an invoicing template according to the structured object to finish invoicing. According to the invention, word segmentation processing and semantic analysis are carried out on the to-be-ticketed overhaul application information, so that the content of the work ticket or the operation ticket needing to be supplemented can be automatically analyzed, and the maintenance and operation processes of the power system are more automatic and intelligent.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to an intelligent ticketing method, an intelligent ticketing system, intelligent ticketing equipment and a storage medium.
Background
A two-ticket (operation ticket and work ticket) system of an electric power enterprise in the safety production process is one of core contents in the electric power safety work regulations, and has very important function and significance for ensuring the safety production of the electric power enterprise. The work ticket is the premise that a power system dispatching department performs switching operation on equipment, the safety of maintenance work is guaranteed, and the maintenance work is normally performed. The invoicing, approval, permission, execution and termination of the work ticket are very important works in the safety production management department of the power enterprise, and the accuracy, integrity and normalization of the safety measures of the work ticket are always the focus of attention.
At present, whether the safety measures of the work ticket are correct or not completely depends on the understanding of the staff to the safety regulations and the working state of the staff, and the traditional mode of manually writing the work ticket wastes a large amount of manpower and material resources and is low in efficiency. Meanwhile, the safety of workers and equipment is threatened all the time by the omission, incompleteness, non-standardization and other problems of safety measures of the work tickets, the development of work such as electric power safety production overhaul, tests and the like is influenced to a certain extent, even safety production accidents can be caused, and the safety and stability of a power grid and the operation of a system are directly influenced.
In the prior art, the application of the work ticket management system can be summarized as follows: setting the template format of the work ticket by using Word or Excel software, and filling the work ticket in a manual input mode by using the template; the work ticket system is developed by applying a database technology, a standard work ticket is established in a database through the system, the ticket is made in a mode of calling the standard ticket, and the management of the historical data of the work ticket is realized.
Based on the technical scheme, the safety measure terms of the work tickets are automatically generated by using the text word segmentation device on the basis of the experience knowledge base and the standard ticket knowledge base of the work tickets, and the intelligent ticketing function of the power distribution network dispatching is researched.
Disclosure of Invention
The invention aims to provide an intelligent billing method, an intelligent billing system, intelligent billing equipment and a storage medium.
In order to achieve the above object, an embodiment of the present invention provides an intelligent ticketing method, including: acquiring to-be-ticketed overhaul application information; performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain word segmentation results of overhaul contents; performing label analysis according to the word segmentation result to obtain a structured object associated with the power grid model; and matching an invoicing template according to the structured object to finish invoicing.
Preferably, the performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of overhaul content includes:
carrying out data cleaning according to the to-be-ticketed overhaul application information to obtain correction data;
and performing word segmentation processing according to the correction data to obtain a word segmentation result of the overhaul content.
Preferably, the data cleaning comprises missing value cleaning, format content cleaning, logic error cleaning and non-demand data cleaning; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing content and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory content.
Preferably, the performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of overhaul content includes:
performing word segmentation processing on the to-be-ticketed maintenance application information by adopting a maximum matching algorithm to obtain a word segmentation result of maintenance content; wherein the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
The embodiment of the invention also provides an intelligent ticketing system, which comprises: the application information acquisition module is used for acquiring the to-be-ticketed overhaul application information; the word segmentation processing module is used for carrying out word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of overhaul contents; the label analysis module is used for carrying out label analysis according to the word segmentation result to obtain a structural object associated with the power grid model; and the billing module is used for matching a billing template according to the structured object to complete billing.
Preferably, the word segmentation processing module includes: the data cleaning unit is used for cleaning data according to the to-be-ticketed overhaul application information to obtain correction data; and the word segmentation unit is used for performing word segmentation processing according to the correction data to obtain a word segmentation result of the overhaul content.
Preferably, the data cleaning comprises missing value cleaning, format content cleaning, logic error cleaning and non-demand data cleaning; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing content and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory content.
Preferably, the word segmentation processing module is further configured to perform word segmentation processing on the to-be-ticketed maintenance application information by using a maximum matching algorithm to obtain a word segmentation result of the maintenance content; wherein the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
The embodiment of the invention also provides computer terminal equipment which comprises one or more processors and a memory. A memory coupled to the processor for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement an intelligent ticketing method as described in any of the embodiments above.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the intelligent ticketing method described in any one of the above embodiments is implemented.
Compared with the prior art, the invention has the following beneficial effects:
the intelligent ticketing method provided by the invention comprises the following steps: acquiring to-be-ticketed overhaul application information; performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain word segmentation results of overhaul contents; performing label analysis according to the word segmentation result to obtain a structured object associated with the power grid model; and matching an invoicing template according to the structured object to finish invoicing. According to the invention, word segmentation processing and semantic analysis are carried out on the to-be-ticketed overhaul application information, so that the content of the work ticket or the operation ticket needing to be supplemented can be automatically analyzed, and the maintenance and operation processes of the power system are more automatic and intelligent.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram of an intelligent ticketing method provided by one embodiment of the present invention;
FIG. 2 is a schematic flow chart diagram of an intelligent ticketing method provided by another embodiment of the present invention;
fig. 3 is a schematic flow chart of word segmentation processing in the intelligent ticketing method provided by an embodiment of the present invention;
FIG. 4 is a schematic flow chart diagram of an intelligent ticketing method provided by yet another embodiment of the present invention;
fig. 5 is a schematic structural diagram of an intelligent ticketing system provided by an embodiment of the present invention;
FIG. 6 is a diagram illustrating the results of an intelligent ticketing system provided by yet another embodiment of the present invention;
fig. 7 is a schematic structural diagram of a computer terminal device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart of an intelligent ticketing method according to an embodiment of the present invention. The intelligent ticketing method provided by the embodiment comprises the following steps:
and S110, acquiring the to-be-ticketed overhaul application information.
And S120, performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of the overhaul content.
And S130, performing label analysis according to the word segmentation result to obtain a structural object associated with the power grid model.
And S140, matching the invoicing template according to the structured object to finish invoicing.
Referring to fig. 2, fig. 2 is a schematic flow chart of an intelligent ticketing method according to another embodiment of the present invention. In the embodiment of the present invention, in step S120, performing word segmentation processing according to the to-be-ticketed inspection application information to obtain a word segmentation result of the inspection content, including the following steps: and S121, cleaning data according to the to-be-ticketed overhaul application information to obtain correction data. And S122, performing word segmentation processing according to the corrected data to obtain a word segmentation result of the overhaul content. The embodiment provides a text filtering method based on topic classification, which screens out an optimal feature item set of text content and filters the text content by using an svm (support Vector machines) classification technology. The SVM (support vector machine) is one of the most robust and accurate methods in all known data mining algorithms, belongs to a binary classification algorithm, and can support linear and nonlinear classification. Further utilizing the text classification system to create domain-specific filters can reduce the amount of training data for manual annotations.
In the embodiment of the invention, the data cleaning comprises missing value cleaning, format content cleaning, logic error cleaning and non-demand data cleaning; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing contents and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory contents.
In the embodiment of the present invention, S120, performing a word segmentation process according to the to-be-ticketed inspection application information to obtain a word segmentation result of the inspection content, further includes: carrying out data cleaning according to the to-be-ticketed overhaul application information to obtain correction data; and performing word segmentation processing according to the correction data to obtain a word segmentation result of the overhaul content.
In the embodiment of the present invention, S120, performing a word segmentation process according to the to-be-ticketed inspection application information to obtain a word segmentation result of the inspection content, further includes:
performing word segmentation processing on the to-be-ticketed maintenance application information by adopting a maximum matching algorithm to obtain a word segmentation result of maintenance content; wherein the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
In one embodiment, word segmentation is carried out according to the to-be-ticketed overhaul application information, a deep network model combining a single-layer neural network and a layered long-short memory network is used for an operation ticket text filtering task, a sentence vector with operation ticket semantics can be obtained by using a word layer LSTM network model, the obtained sentence vector is used as input by depending on a tone expert knowledge base and a sentence layer LSTM network, dependence degrees of operation ticket sentences and various categories can be obtained, dependence relations of various categories in the whole operation ticket are mined through the sentence layer LSTM network, and analysis and processing of operation task texts are effectively improved.
The generation process of the power grid operation ticket is essentially a process of simulating a dispatcher to draft, and relates to a corresponding logical thinking mode and a corresponding logical thinking process. In the system, the expert rule base covers diversified rule base types, and different functions can be realized.
Determining an equipment operation task based on a user interface and an operation type, and selecting a comprehensive order mode, wherein the comprehensive order mode and the order-by-order mode are respectively selected for equipment operation in a single plant station and a plurality of plant stations; the comprehensive order is a scheduling instruction which is made by an order person and used for explaining operation tasks, requirements and starting and ending states of operation objects in the power system scheduling, specific operation steps and operation sequence items are set by the order person, and the comprehensive order can be used only when the operation finished by one unit is involved; the item-by-item command is a comprehensive command or a single command issued in sequence in the power system according to a certain logical relationship.
In the generation process of the scheduling switching operation ticket in the determined rule base, the operation task can involve diversified element actions in actual operation by combining the requirement of the power grid scheduling state. For example, when the switch operation is received by the ticketing system, the decomposition or division of the instruction is realized by the operation task division rule base, and the operation instruction is converted into a basic element decomposition operation instruction.
In the device operation decomposition rule base, the related information content is accurately defined. For the operation process of the equipment, the intelligent judgment rule is applied in the aspects of path judgment, load power loss and the like. The ticket system equipment can self-define the rules, so that the ticket system equipment is suitable for various complex and irregular wiring modes.
In the intelligent ticketing method provided by the embodiment of the invention, an expert knowledge base is required to be applied in the participle processing process, the modeling of the expert knowledge base is based on an experience knowledge base and a standard ticket knowledge base of a work ticket, safety measures of the work ticket are combined by unit intervals or line names, voltage levels, equipment types, equipment codes, equipment names and verb phrases of operation in the expert knowledge base, and more critical safety measure terms comprise unit intervals/line names, voltage levels, equipment types and data relation models between the equipment.
Expressions for device type operation terms and permission terms are defined as follows.
(1) Circuit breaker (switch) type.
Breaker (switch) class operating terminology: + [ DYDYDJ _ NAME ] + [ DYJG _ NAME ] + [ SB _ NAME ] should be turned off.
Circuit breaker (switch) class permissive terminology: [ DYDYDJ _ NAME ] + [ DYJG _ NAME ] + [ SB _ NAME ] has been disconnected.
(2) Isolation knife-switch type.
Knife switch operation terminology: + [ DYDYDJ _ NAME ] + [ SB _ NAME ] should be pulled open.
The term knife gate permits: + [ DYDYDJ _ NAME ] + [ SB _ NAME ] has been pulled open.
(3) The grounded knife switch type.
The term of ground knife operation: + [ DYDYDJ _ NAME ] + [ SB _ NAME ] should be closed.
The ground knife permits the term: has been closed + [ DYDYDJ _ NAME ] + [ SB _ NAME ].
(4) Fuse (safety) type.
The operational terms: + [ DYDYDJ _ NAME ] + [ SB _ NAME ] should be removed.
Licensing terms: + [ DYDYDJ _ NAME ] + [ SB _ NAME ] have been removed.
(5) Relay protection/safety automation type.
The operational terms: the [ SB _ NAME ] device should be launched or the [ SB _ NAME ] device should be exited.
Licensing terms: has launched the [ SB _ NAME ] device or has exited the [ SB _ NAME ] device.
The relay protection/safety automation type should match its terminology depending on the equipment state, it is the "on" state that should match the "off" term, and vice versa. This type of device is more specific, its terminology being associated with the state of the device.
(6) Other device types may also define their expressions according to the rules described above.
The meaning of the expression symbol in the work ticket security action term and permission term definition rule is explained as follows: [ DYDYDJ _ NAME ] is the "voltage class" of the device, [ DYJG _ NAME ] is the "cell bay NAME/line NAME" of the device, [ SBLX _ NAME ] is the "device type" of the device (breaker or switch type, isolation switch type, ground switch type, etc. as described above), [ SB _ NAME ] is the "device NAME" of the device. The 'open', 'close', 'take down', 'throw in', 'exit', etc. are all verbs of the inherent operations in the device type, and can be directly defined in the expression.
The expression of the operation term and the permission term of the equipment type, the user can freely combine and define according to the voltage grade, the unit interval/line name, the equipment type and the double name of the equipment (equipment code + equipment name, such as 113 circuit breakers), and the requirement of actual business work can be met. The operation terms and permission terms of the equipment are mainly aimed at some relatively special equipment, the terms of which are different from the terms of the corresponding equipment type, and the expression rules of the equipment terms are required to be solidified on the operation terms and permission terms of the equipment knowledge base and only used on the equipment without influencing other equipment.
With the increasing of the scale of the power grid, the number of power grid devices is increased continuously, a large number of device maintenance plans are provided every year, and a large number of operation tickets need to be manually compiled and checked by a dispatcher according to a maintenance application form, so that the workload is extremely large. The embodiment of the invention aims to ensure the safe and stable operation of the power system, adapt to the situation of rapid development of the power grid and improve the efficiency of a dispatcher for commanding the operation of the power grid.
Firstly, extracting overhaul work content and performing model association through a Chinese word segmentation method based on maximum rule matching, and then generating an operation order intelligently by an operation order system according to modeled overhaul equipment information and overhaul state information. The overhaul work content is extracted, the most important link is word segmentation processing, and the word segmentation processing link relates to application of a maximum matching algorithm.
The maximum matching algorithm mainly comprises a forward maximum matching algorithm, a reverse maximum matching algorithm and a two-way matching algorithm.
The basic principle is that a general dictionary is set as D, and the number of words contained in the longest entry is marked as MaxLen. And recording the Chinese character string to be divided with the length M as s1, s2, … and sm. In order to cut out entries from a sentence, the forward maximum matching algorithm is to take candidate strings of the sentence to be cut out from left to right, and the expression is as follows:
k＝max{hI((s1，s2，......，sh)∈D)}(1)
in the formula:
if s is1，s2，…，shSuccessful matching of the general dictionary, s1, s2, …, shIf matching of +1 with the general dictionary is not successful, s1, s2, …, s will be selectedhSegmenting out as a word; then, the Chinese character string s is continuedh+1，sh+2, …, sm are matched and split according to equation (1) until all words are split, typically h > 1. When h is 1, namely s1 belongs to E D, the word of the segmentation is taken as an entry; when h is 0, i.e., s1 ∈ D, it indicates that the word of the split is an unknown word. The reverse maximum matching algorithm has the same basic principle as the forward maximum matching algorithm, and only has reverse segmentation.
Referring to fig. 3, fig. 3 is a schematic flow chart illustrating word segmentation processing in an intelligent ticketing method according to an embodiment of the present invention. Firstly, acquiring a maintenance application document, and then performing data cleaning, wherein the data cleaning comprises the following steps: missing value cleaning, format content cleaning, logic error cleaning and non-demand data cleaning, wherein the missing value cleaning comprises the following steps: determining a missing value range, removing unnecessary fields, filling missing contents and re-fetching numbers; format content cleaning: the display formats of time, date, numerical value, full half angle and the like are inconsistent, characters which do not exist in the content, and the content is inconsistent with the content of the field; logic error cleaning: removing duplication, removing unreasonable values and correcting contradictory contents, wherein data cleaning is to improve accuracy, then performing word segmentation processing on overhaul contents, and finally storing word segmentation results. The text description characteristics of the work content in the overhaul application form are analyzed, and the word segmentation algorithm based on the combination of Forward Maximum Matching (FMM) and Reverse Maximum Matching (RMM) is selected and realized in the embodiment. Because the text format of the overhaul content is relatively fixed, the self-defined dictionary can effectively improve the word segmentation accuracy.
Referring to fig. 4, fig. 4 is a schematic flow chart of an intelligent ticketing method according to another embodiment of the present invention. The work content of the overhaul ticket is subjected to word segmentation, semantic analysis processing and the like through a word segmenter to generate a structured object which can be identified by an operation ticket system; then, the operation order system calls an expert knowledge base and an order-forming inference machine to intelligently generate an operation order. The specific process comprises the following steps: a. a service application documentation file is obtained. b. And the word segmentation device stores the word segmentation result of the overhaul content through data cleaning and screening. c. The semantic analysis module is used for carrying out annotation analysis on the word segmentation structure of the warehousing overhaul content to obtain a structural object associated with the power grid model; and when the analysis fails, returning to the step b for algorithm adjustment. d. And interacting the analysis result with an operation ticket system ticket forming module according to an operation ticket system interface format. e. And the operation ticket system calls the ticket forming module to generate a corresponding operation ticket according to the equipment to be formed and the action state.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an intelligent ticketing system according to an embodiment of the present invention. The same portions of this embodiment as those of the above embodiments will not be described herein again. The intelligent ticketing system provided by the embodiment comprises:
and an application information obtaining module 210, configured to obtain pending ticket overhaul application information.
And the word segmentation processing module 220 is configured to perform word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of the overhaul content.
And the label analysis module 230 is configured to perform label analysis according to the word segmentation result to obtain a structured object associated with the power grid model.
And the invoicing module 240 is used for matching the invoicing template according to the structured object to finish invoicing.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an intelligent ticketing system according to another embodiment of the present invention. In the embodiment of the present invention, the word segmentation processing module 220 includes a data cleaning unit 221 and a word segmentation unit 222, where the data cleaning unit 221 is configured to perform data cleaning according to the to-be-ticketed maintenance application information to obtain correction data, and the word segmentation unit 222 is configured to perform word segmentation according to the correction data to obtain a word segmentation result of the maintenance content.
In the embodiment of the invention, the data cleaning comprises missing value cleaning, format content cleaning, logic error cleaning and non-demand data cleaning; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing contents and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory contents.
In the embodiment of the present invention, the word segmentation processing module 220 is further configured to perform word segmentation processing on the pending ticket inspection application information by using a maximum matching algorithm, so as to obtain a word segmentation result of the inspection content; the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
The intelligent ticketing system provided by the embodiment of the invention can automatically acquire the published maintenance application document text file in real time and perform word segmentation analysis, the result shows that the analysis accuracy is higher than 90%, and the accurately analyzed maintenance ticket can intelligently generate an operation ticket meeting the scheduling specification, thereby greatly improving the working efficiency of a dispatcher.
In order to verify the technical effect adopted in the embodiment of the invention, the text filtering method based on the k nearest neighbor classification algorithm and the manual work ticket writing method selected in the embodiment are compared and tested with the method, and the experimental results are compared by means of scientific demonstration to verify the real effect of the method.
In order to verify that the method has higher efficiency and classification accuracy compared with the traditional method, the method respectively measures and compares the accuracy and efficiency of the work ticket forming by adopting the traditional method and the method in real time. The first traditional method comprises the following steps: a text filtering method based on a k nearest neighbor classification algorithm comprises the following steps of: a method for manually operating a handwritten work ticket. And (3) testing environment: and (4) simulating a power system dispatching department on the simulation platform to perform switching operation on the equipment, and performing work ticket billing by respectively using a traditional method II.
By adopting the method and the traditional method I, the automatic test equipment is started, MATLB software programming is used for realizing simulation test of the two methods, and simulation data are obtained according to an experimental result. In each method, 50 groups of data are tested, working ticket forming data of each group of data are obtained through calculation, comparison calculation errors are carried out on the working ticket forming data and actual ticket forming data input through simulation, and the results are shown in tables 1-4.
TABLE 1 conventional method-Experimental results Table
TABLE 2 Experimental results of the conventional method II
Table 3 table of experimental results of this example
Table 4 comparative table of experimental results
| Experimental sample | Conventional method 1 | Conventional method two | This example |
| Efficiency/%) | 93.5 | 72.6 | 98.7 |
| Rate of accuracy/%) | 96.5 | 87.4 | 96.7 |
From tables 1-4, it can be seen that the method of the present invention is far more efficient than the first conventional method, and the efficiency and accuracy of the method of the present invention are far greater than the second conventional method, although the accuracy of the method is very close to that of the first conventional method.
Aiming at the practical problems that the overhaul application form is large in text quantity, is not associated with an operation ticket system and does not have an intelligent ticket forming function, the embodiment of the invention designs a word segmentation device based on FMM and RMM by researching a text word segmentation technology based on a maximum rule matching algorithm, constructs an overhaul content text word segmentation device and a semantic analysis module, designs and realizes an automatic interaction mode with the intelligent operation ticket system, finally realizes the intelligent ticket forming of the overhaul application form, and lightens the working intensity of a regulator. In subsequent work, research needs to be carried out on equipment name fuzzy word segmentation analysis and unknown word recognition algorithms, and a method is provided for analyzing scheduling service related texts and operation order instructions. The neural network models for natural language processing are mainly RNN and LSTM, where RNN can take into account the context information of the sequence, but the components of the gradient vector of RNN may grow exponentially or disappear on long sequences during training. The LSTM can solve the RNN gradient problem and introduce a caching mechanism to capture the overall semantic information in the operation ticket text.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a computer terminal device according to an embodiment of the present invention. An embodiment of the present invention provides a computer terminal device, including one or more processors and a memory. The memory is coupled to the processor for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the intelligent ticketing method as in any of the above embodiments.
The processor is used for controlling the overall operation of the computer terminal equipment so as to complete all or part of the steps of the intelligent ticketing method. The memory is used to store various types of data to support the operation at the computer terminal device, which data may include, for example, instructions for any application or method operating on the computer terminal device, as well as application-related data. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
In an exemplary embodiment, the computer terminal Device may be implemented by one or more Application Specific 1 integrated circuits (AS 1C), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, for performing the above-mentioned intelligent ticketing method, and achieving technical effects consistent with the above-mentioned method.
In another exemplary embodiment, there is also provided a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the intelligent ticketing method in any of the above-mentioned embodiments. For example, the computer readable storage medium may be the above-mentioned memory including program instructions executable by a processor of a computer terminal device to perform the above-mentioned intelligent ticketing method, and to achieve the technical effects consistent with the above-mentioned method.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. An intelligent ticketing method, comprising:
acquiring to-be-ticketed overhaul application information;
performing word segmentation processing according to the to-be-ticketed overhaul application information to obtain word segmentation results of overhaul contents;
performing label analysis according to the word segmentation result to obtain a structured object associated with the power grid model;
and matching an invoicing template according to the structured object to finish invoicing.
2. The intelligent ticketing method of claim 1, wherein the performing a word segmentation process according to the to-be-ticketed service application information to obtain a word segmentation result of service content comprises:
carrying out data cleaning according to the to-be-ticketed overhaul application information to obtain correction data;
and performing word segmentation processing according to the correction data to obtain a word segmentation result of the overhaul content.
3. The intelligent ticketing method of claim 2, wherein said data cleansing comprises missing value cleansing, format content cleansing, logical error cleansing, and non-demand data cleansing; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing content and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory content.
4. The intelligent ticketing method of claim 1, wherein the performing a word segmentation process according to the to-be-ticketed service application information to obtain a word segmentation result of service content comprises:
performing word segmentation processing on the to-be-ticketed maintenance application information by adopting a maximum matching algorithm to obtain a word segmentation result of maintenance content; wherein the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
5. An intelligent ticketing system, comprising:
the application information acquisition module is used for acquiring the to-be-ticketed overhaul application information;
the word segmentation processing module is used for carrying out word segmentation processing according to the to-be-ticketed overhaul application information to obtain a word segmentation result of overhaul contents;
the label analysis module is used for carrying out label analysis according to the word segmentation result to obtain a structural object associated with the power grid model;
and the billing module is used for matching a billing template according to the structured object to complete billing.
6. The intelligent ticketing system of claim 5, wherein said segmentation processing module comprises:
the data cleaning unit is used for cleaning data according to the to-be-ticketed overhaul application information to obtain correction data;
and the word segmentation unit is used for performing word segmentation processing according to the correction data to obtain a word segmentation result of the overhaul content.
7. The intelligent ticketing system of claim 6, wherein said data cleansing comprises missing value cleansing, format content cleansing, logical error cleansing, and non-demand data cleansing; the missing value cleaning comprises determining a missing value range, removing unnecessary fields, filling missing content and re-fetching, the format content cleaning comprises removing numerical values and redundant characters which are inconsistent in digital format display, and the logic error cleaning comprises removing contradictory numerical values and correcting contradictory content.
8. The intelligent ticketing system of claim 5, wherein the word segmentation processing module is further configured to perform word segmentation processing on the to-be-ticketed overhaul application information by using a maximum matching algorithm to obtain a word segmentation result of overhaul content; wherein the maximum matching algorithm comprises forward maximum matching, reverse maximum matching and bidirectional matching.
9. A computer terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the intelligent ticketing method of any of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the intelligent ticketing method of any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110419147.4A CN113095050A (en) | 2021-04-19 | 2021-04-19 | Intelligent ticketing method, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110419147.4A CN113095050A (en) | 2021-04-19 | 2021-04-19 | Intelligent ticketing method, system, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113095050A true CN113095050A (en) | 2021-07-09 |
Family
ID=76678653
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110419147.4A Pending CN113095050A (en) | 2021-04-19 | 2021-04-19 | Intelligent ticketing method, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113095050A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114154663A (en) * | 2021-12-14 | 2022-03-08 | 深圳供电局有限公司 | Main network overhauls single flow intelligence processing system |
| CN114237106A (en) * | 2021-12-07 | 2022-03-25 | 南方电网海南数字电网研究院有限公司 | Five-prevention operation control method and device based on switching operation ticket |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376353A (en) * | 2018-09-04 | 2019-02-22 | 国家电网公司华东分部 | A kind of power grid start-up operation ticket generating means and method based on natural language processing |
| CN110991188A (en) * | 2019-09-17 | 2020-04-10 | 国网浙江省电力有限公司杭州供电公司 | Ticket forming method applied to distribution network scheduling intelligent ticket forming system |
| CN111104801A (en) * | 2019-12-26 | 2020-05-05 | 济南大学 | Text word segmentation method, system, device and medium based on website domain name |
-
2021
- 2021-04-19 CN CN202110419147.4A patent/CN113095050A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376353A (en) * | 2018-09-04 | 2019-02-22 | 国家电网公司华东分部 | A kind of power grid start-up operation ticket generating means and method based on natural language processing |
| CN110991188A (en) * | 2019-09-17 | 2020-04-10 | 国网浙江省电力有限公司杭州供电公司 | Ticket forming method applied to distribution network scheduling intelligent ticket forming system |
| CN111104801A (en) * | 2019-12-26 | 2020-05-05 | 济南大学 | Text word segmentation method, system, device and medium based on website domain name |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114237106A (en) * | 2021-12-07 | 2022-03-25 | 南方电网海南数字电网研究院有限公司 | Five-prevention operation control method and device based on switching operation ticket |
| CN114237106B (en) * | 2021-12-07 | 2024-04-05 | 南方电网海南数字电网研究院有限公司 | Five-prevention operation control method and device based on switching operation ticket |
| CN114154663A (en) * | 2021-12-14 | 2022-03-08 | 深圳供电局有限公司 | Main network overhauls single flow intelligence processing system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107861942B (en) | Suspected power complaint work order identification method based on deep learning | |
| CN114168716B (en) | Deep learning-based automatic engineering cost extraction and analysis method and device | |
| CN110175324B (en) | Power grid operation instruction verification method and system based on data mining | |
| CN110188345B (en) | Intelligent identification method and device for electric operation ticket | |
| CN107103363A (en) | A kind of construction method of the software fault expert system based on LDA | |
| CN113204967B (en) | Resume named entity identification method and system | |
| CN112560486A (en) | Power entity identification method based on multilayer neural network, storage medium and equipment | |
| CN111309910A (en) | Text information mining method and device | |
| CN112100397A (en) | Electric power plan knowledge graph construction method and system based on bidirectional gating circulation unit | |
| CN115357726A (en) | Fault disposal plan digital model establishing method based on knowledge graph | |
| CN113095050A (en) | Intelligent ticketing method, system, equipment and storage medium | |
| CN110110095A (en) | A kind of power command text matching technique based on shot and long term memory Recognition with Recurrent Neural Network | |
| CN113468317B (en) | Resume screening method, system, equipment and storage medium | |
| CN115357719A (en) | Power audit text classification method and device based on improved BERT model | |
| CN113449753B (en) | Service risk prediction method, device and system | |
| CN112232078A (en) | Scheduling operation ticket auditing method based on bidirectional GRU and attention mechanism | |
| CN115687563A (en) | Interpretable intelligent judgment method and device, electronic equipment and storage medium | |
| CN111178080A (en) | Named entity identification method and system based on structured information | |
| CN114282010A (en) | Power grid operation fault identification method and system based on knowledge graph and storage medium | |
| CN112036179B (en) | Electric power plan information extraction method based on text classification and semantic frame | |
| CN112541070A (en) | Method and device for excavating slot position updating corpus, electronic equipment and storage medium | |
| CN114722159B (en) | Multi-source heterogeneous data processing method and system for numerical control machine tool manufacturing resources | |
| CN113642835B (en) | Work ticket generation method based on data similarity and terminal | |
| Wang et al. | Research and Exploration on The Application of RPA and Artificial Intelligence Technology in The Field of Electric Power Marketing | |
| CN113792538A (en) | Method and device for quickly generating operation ticket of power distribution network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |