CN114399203A - Transformer substation maintenance task processing method and system, terminal device and storage medium - Google Patents

Transformer substation maintenance task processing method and system, terminal device and storage medium Download PDF

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CN114399203A
CN114399203A CN202210049210.4A CN202210049210A CN114399203A CN 114399203 A CN114399203 A CN 114399203A CN 202210049210 A CN202210049210 A CN 202210049210A CN 114399203 A CN114399203 A CN 114399203A
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CN114399203B (en
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张加涛
王丙东
刘灿
李冬
王圆圆
刘莹
陈霞
王玮
张好勇
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State Grid Corp of China SGCC
Langfang Power Supply Co of State Grid Jibei Electric Power Co Ltd
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Abstract

The application provides a transformer substation maintenance task processing method, a transformer substation maintenance task processing system, terminal equipment and a storage medium, wherein the transformer substation maintenance task processing method comprises the following steps: acquiring defect information, wherein the defect information comprises defect device type information and defect type information; classifying the defect information of the same defect device type to form a plurality of groups of maintenance tasks; calculating the defect degree score of each piece of defect information in each maintenance task; and sequencing the defect information in each group of maintenance tasks according to the defect degree score. The method and the device have the advantages that received defect information is classified according to types of defect devices and defect types to form multiple groups of maintenance tasks, defects in each group of maintenance tasks are sorted according to defect degree scores, the defect elimination sequence is determined, the defects are intelligently sorted, and special responsibility is liberated from miscellaneous statistical work.

Description

Transformer substation maintenance task processing method and system, terminal device and storage medium
Technical Field
The application relates to the technical field of equipment maintenance, in particular to a transformer substation maintenance task processing method and system, terminal equipment and a storage medium.
Background
The equipment management system of present transformer substation can only transmit the defect data that transformer operation and maintenance center reported to transformer maintenance center for transformer maintenance center, but does not gather the analysis to the defect, and the defect data of a plurality of transformer substations, several thousand equipment to defect expression form is various. Only the defects are organized and the defect elimination plan is arranged, so that the special responsibility and the long time of the shift are occupied, and under the limited working time, other works can be completed only by overtime.
With the increase of the number of the processed defects of the equipment, the number of the engineering vehicles is insufficient, so that the vehicle combination problem among different teams and the multi-site operation problem of the same team need to be solved urgently, and currently, the position of each transformer substation can be grasped and the route experience can be determined only by the team.
Disclosure of Invention
In view of the above-mentioned defects or shortcomings in the prior art, the present application aims to provide a transformer substation maintenance task processing method, system, terminal device and storage medium. . .
In a first aspect, the application provides a transformer substation overhaul task processing method, including:
acquiring defect information, wherein the defect information comprises defect device type information and defect type information;
classifying the defect information of the same defect device type to form a plurality of groups of maintenance tasks and acquiring a defect information identification classification table;
calculating the defect degree score of each piece of defect information in each group of maintenance tasks;
Figure BDA0003473886310000011
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score, k, of the nth influencing factor on the ith defectnIs the weight of the nth influence factor and satisfies
Figure BDA0003473886310000012
m is the total number of influencing factors;
and sequencing the defect information in each group of maintenance tasks according to the defect degree score.
According to the technical solution provided by some embodiments of the present application, the defect information further includes defect site information; the method further comprises the following steps:
constructing an incidence matrix of all the defective site information, wherein the incidence matrix is constructed by incidence coefficients among all the sites;
and performing relevance marking on each piece of defect information with the relevance coefficient larger than the set coefficient in the maintenance task.
According to the technical scheme provided by some embodiments of the application, a vehicle closing request is received, and the vehicle closing request is initiated by an administrator terminal of a first maintenance task; the car closing request comprises car closing defect information;
extracting information of requested station closing points from the vehicle closing defect information;
determining station information which is determined from the incidence matrix and has a correlation coefficient with the station combination station greater than a set coefficient;
traversing a defect information identification classification table, wherein the defect information table stores the defect information and the corresponding team name, and searching the defect information containing the determined site information and the corresponding second maintenance task;
sending the vehicle closing request to a manager terminal of a second maintenance task;
and receiving and forwarding the vehicle closing feedback information sent by the administrator of the second overhaul task to the administrator terminal of the first overhaul task.
In a second aspect, the application provides a transformer substation maintenance task processing system, which includes a maintenance terminal configured to input and upload defect information;
an input module configured to receive defect information; the defect information comprises defect device type information and defect type information;
the processing module is configured for classifying the defect information of the same defect device type to form a plurality of groups of maintenance tasks;
calculating the defect degree score of each piece of defect information in each maintenance task;
Figure BDA0003473886310000021
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score, k, of the nth influencing factor on the ith defectnIs the weight of the nth influence factor and satisfies
Figure BDA0003473886310000022
m is the total number of influencing factors;
sorting the defect information in the maintenance task according to the defect degree score;
and the display module is configured for displaying the maintenance tasks which are sequenced according to the defect degree scores.
According to the technical scheme provided by some embodiments of the application, the processing module is further configured to construct an incidence matrix of all station information, and perform incidence marking on each piece of defect information with incidence coefficient larger than a set coefficient in a maintenance task.
According to the technical scheme provided by some embodiments of the application, the system comprises a first class group administrator terminal, a second class group administrator terminal,
the first maintenance task manager terminal is configured to send a vehicle closing request;
the second maintenance task manager terminal is configured to receive the car closing request and send feedback information;
the processing module is configured to extract information of station points requested to be closed from the vehicle closing defect information;
determining station information which is determined from the incidence matrix and has a correlation coefficient with the station combination station greater than a set coefficient;
and traversing a defect information identification classification table, and searching the defect information containing the determined site information and the corresponding second maintenance task.
According to the technical scheme provided by some embodiments of the application, the system further comprises a purchase storage module, wherein the purchase storage module stores equipment name information, equipment holding capacity information and corresponding fault rate information of all equipment in the transformer substation; the fault rate information is obtained by counting the defect information by the processing module within a set period time; and the information of the quantity to be purchased is the product of the information of the reserved quantity of the equipment and the corresponding failure rate information.
In a third aspect, the present application provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the transformer substation overhaul task processing method are implemented.
A fourth aspect the present application provides a computer readable storage medium having a computer program which, when executed by a processor, performs the steps of the above described substation overhaul task processing method.
The method and the device have the advantages that received defect information is classified according to types of defect devices and defect types to form multiple groups of maintenance tasks, defects in each group of maintenance tasks are sorted according to defect degree scores, the defect elimination sequence is determined, the defects are intelligently sorted, and special responsibility is liberated from miscellaneous statistical work.
In conclusion, by constructing the incidence matrix of the defective site information for the site information in the defect information, the intelligent search of the incidence degree among the sites is realized, so that the vehicle combination problem among different teams and the multi-site operation problem in the same team are determined, and the problem that the number of the engineering vehicles is insufficient along with the increase of the number of the equipment defects is solved. In addition, the technical scheme provided by the application can also determine the purchase quantity of spare parts, establish a fault library and share overhaul data by the whole personnel.
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FIG. 1 is a flow chart of embodiment 1 of the present application;
FIG. 2 is a flow chart of embodiment 2 of the present application;
FIG. 3 is a flow chart of embodiment 3 of the present application;
FIG. 4 is a functional block diagram of the 4 th embodiment of the present application;
FIG. 5 is a schematic block diagram of the 5 th embodiment of the present application
The text labels in the figures are represented as:
100. overhauling the terminal; 200. an input module; 300. a processing module; 400. and a display module.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Example 1
Fig. 1 is a flowchart illustrating a first embodiment provided by the present application: the transformer substation maintenance task processing method provided by the embodiment comprises the following steps:
s100, acquiring defect information, wherein the defect information comprises defect device type information and defect type information;
preferably, the defect information includes power station/line, voltage class, discovery date, defect content. The defect content includes a device type field and a defect information field, for example, the following table 1 is defect information input by an inspector, in this embodiment, only the defect content information of the fourth column in the table needs to be obtained, and preferably, the defect content includes the types of the devices of the capacitor, the main transformer, the circuit breaker, the transformer substation and the current transformer, including the defect type information of the switch cabinet protection screen black screen, the electric operation failure, the disconnection signal, the gas alarm, the oil temperature, the switch controller preset failure and the oil leakage.
Figure BDA0003473886310000051
TABLE 1 Defect information
S200, classifying the defect information of the same defect device type to form a plurality of groups of maintenance tasks; the intelligent defect classification step comprises the following steps:
the defect information in table 1 is classified into transformer specialty, switch specialty, and capacitor specialty according to the device type in the defect content;
each specialty comprises a plurality of teams, and defects are assigned to different teams of the same specialty;
and classifying each specialty and each group again according to the defect type information in the defect content to form a plurality of groups of maintenance tasks.
For example, the following table 2 is a processing result after intelligent classification, which is a defect information identification classification table, and a defect task is specifically assigned to different teams and groups in different specialties, so that a basis is provided for defect tracking and implementing special responsibility; in addition, the maintainers can determine the maintenance tool and the maintenance method through the defect type information, and the maintenance efficiency is greatly improved.
Figure BDA0003473886310000052
Figure BDA0003473886310000061
TABLE 2 Defect information identification classification table
S300, calculating the defect degree score of each piece of defect information in each maintenance task; the defect information further includes a defect level and a remaining defect elimination period, and when a plurality of defects are simultaneously allocated to the same group, it is necessary to know a processing sequence of each defect, and perform weighting processing on the defects as follows, for example, as shown in formula (1):
Figure BDA0003473886310000062
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score, k, of the nth influencing factor on the ith defectnIs the weight of the nth influence factor and satisfies
Figure BDA0003473886310000063
m is the total number of influencing factors;
in this embodiment, only three influence factors are considered, and a weight term including the main device, the auxiliary device, and the current-carrying capacity of the device can be added according to actual needs, where m is 3
F(i)≡k1x1(i)+k2x2(i)+k3x3(i)
Wherein x1For defect severity, x2Defining deadline proximity for defect handling distance, x3Is the defective device voltage level.
x1The values for defect severity are for example the corresponding scores shown in table 3 below,
kind of defect Critical condition Severe severity of disease In general
Corresponding score 100 40 25
TABLE 3 x1Defect severity corresponding to score
When the defect information is reported, the reporting personnel and the auditor of the power transformation operation and maintenance center can determine the defect type.
x2The value of the proximity of the defect process distance limit term is calculated by the following formula (2),
Figure BDA0003473886310000071
wherein, tsThe remaining days, t, representing the limit of the defect treatment distancezThe defect is defined to be eliminated for a period of 24 hours for critical defects, 30 days (one month) for serious defects, and 365 days (1 year) for general defects.
x3The values of the defective device voltage levels are selected by the corresponding fractions as shown in table 4 below
Defective device voltage class 220kV 110kV 35kV 10kV
x3Corresponding score 80 50 30 20
TABLE 4 x3Score selection
After the treatment, the defect degree score shown in the sixth column in the table 5 is obtained, the larger the F index is, the higher the defect emergency degree is, the emergency degree of defect treatment can be visually seen through the defect degree score table, the overhaul work can be rapidly arranged, and the working efficiency is improved.
Figure BDA0003473886310000072
TABLE 5 Defect degree score Table
And S400, sorting the defect information in each group of maintenance tasks according to the defect degree score. Through intelligent classification and calculation of defect degree scores, the emergency degree of each defect of each team to be overhauled can be obtained, but the defects of each team are multiple, and it is difficult for an overhaul worker to pick out the defect with the largest numerical value from various F numerical values, so that the defect can be intelligently sorted according to the defect degree, the sorting result is displayed at the terminal, the overhaul worker can visually see the most emergency defect, the overhaul time is shortened, and the work efficiency is improved.
Example 2
As shown in the flowchart of fig. 2, on the basis of embodiment 1, the defect information further includes defect site information; the method further comprises the following steps:
s500, constructing an incidence matrix of all the defective site information, wherein the incidence matrix is constructed by incidence coefficients among all the sites; due to the fact that the number of defects in the team is large, the situation of multiple tasks occurs, the number of engineering vehicles is limited, and the problem of arranging maintenance vehicles can be solved by building a management matrix.
And s600, performing relevance marking on each piece of defect information with the relevance coefficient larger than the set coefficient in the maintenance task. After the incidence matrix is established, the defect information is received, the incidence degree between every two defects can be displayed on the terminal, the problem of how to arrange the overhaul vehicle is comprehensively judged according to the incidence degree and the defect degree score, the visual display is realized, the clearness and the understandability are realized, and the working efficiency is improved.
The correlation matrix is for example shown as the following matrix,
Figure BDA0003473886310000081
wherein N is the total number of the substation, G11、GMM、GNN、GLLThe correlation degree of the substation is 1, so the correlation matrix is a symmetric matrix, and the diagonal value is 1. GLMRepresenting the degree of association between the substation L and the substation M, wherein L is less than or equal to N, M is less than or equal to N, and G is more than 0LM≤1.0。
GLMThe method can be determined by adopting an expert decision method, namely, two transformer substations are respectively scored by experienced maintainers and drivers, the average value is taken, the distance between the two transformer substations is taken as a factor considered during scoring, if the distance between the two transformer substations is lower, the closing of the vehicle can be considered, and whether a route from the two transformer substations to an operation and maintenance center appears or not is consideredIf the two routes are basically overlapped, the vehicle can be combined.
In practical application, G can be consideredLMAnd when the voltage is more than 0.8, the two substations meet the requirements of vehicle combination or multi-site operation. Meanwhile, considering the change of factors such as road repair, row restriction, height restriction and the like, the transformer substation incidence matrix is usually corrected in spring and autumn each year.
By the method, the problem that the same team combined vehicle performs multi-site operation under the condition of insufficient engineering vehicles is solved, and the utilization rate of the engineering vehicles is improved.
Example 3
As shown in the flowchart of fig. 3, on the basis of embodiment 2, for dealing with the problem of combining cars between different teams, the present application proposes a processing method:
s700, receiving a closing request, wherein the closing request is initiated by a manager terminal of the first maintenance task; the car closing request comprises car closing defect information; when the maintenance task is received, if the team does not meet the defect of car combination and the cars are in shortage, car combination requests can be sent to other teams, a manager of the first maintenance task sends the car combination requests to the server through the terminal, and the server receives the car combination requests.
S800, extracting information of requesting station closing points from the vehicle closing defect information; the information sent to the server together with the car closing request also comprises defect information, and the defect information comprises stations/lines, so that the server can extract the information of the requested station closing points.
s900, determining station information with the station combination point relevance coefficient larger than a set coefficient from the relevance matrix; the association degree of all stations can be obtained through the association matrix in embodiment 2, and optionally, the set coefficient is 0.8, and when the association degree is greater than 0.8, the station is a station capable of combining vehicles.
S1000, traversing a defect information identification classification table, wherein the defect information table stores the defect information and the corresponding team names, and searching the defect information containing the determined site information and the corresponding second maintenance task; the team of each maintenance task at each station is obtained through the defect information identification classification result table in the embodiment 1, so that all maintenance teams corresponding to the station requesting to close the car sent by the administrator terminal of the first maintenance task can be searched.
S1100, sending the vehicle closing request to a manager terminal of a second overhaul task;
and s1200, receiving and forwarding the vehicle closing feedback information sent by the administrator of the second overhaul task to the administrator terminal of the first overhaul task. And traversing all maintenance teams meeting the requirements, sending request car closing requirements in sequence, and after receiving the car closing requests, the administrator of the second maintenance task sends feedback information to the server and forwards the feedback information to the administrator terminal of the first maintenance task. And if the vehicles are not agreed, the server sends vehicle combination requests to other teams again.
By the method, the problems that the number of engineering vehicles is insufficient, and different teams and combination vehicles perform multi-site operation are solved, so that the engineering vehicles reach a great utilization rate.
Example 4
As shown in fig. 4, this embodiment provides a substation maintenance task processing system for implementing the substation maintenance task processing method described in embodiment 1, and the substation maintenance task processing system includes:
a maintenance terminal 100 configured to input and upload defect information; optionally, the overhaul terminal is a PC of the operation and maintenance center, a PMS system is installed on the PC, the PMS is an abbreviation of a power production management system (power production management system), and the overhaul personnel enters the defect information through the PMS system.
An input module 200 configured to receive defect information; the defect information comprises defect device type information and defect type information; the defect management method specifically comprises the steps of site/line, voltage level, discovery date, defect content, defect level and residual defect elimination period, wherein the defect content comprises defect device type information and defect type information.
The processing module 300 is configured to classify the defect information of the same defect device type to form a plurality of groups of maintenance tasks;
calculating the defect degree score of each piece of defect information in each maintenance task;
Figure BDA0003473886310000101
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score, k, of the nth influencing factor on the ith defectnIs the weight of the nth influence factor and satisfies
Figure BDA0003473886310000102
m is the total number of influencing factors;
sorting the defect information in the maintenance task according to the defect degree score;
the processing module comprises a defect information identification and classification module and a defect weighting and sorting module, wherein the defect information identification and classification module is used for intelligently identifying and classifying the defect information received by the input module to obtain a defect information identification and classification table and form a plurality of groups of maintenance tasks, and the specialty, the team and the defect type of each defect information can be determined in the defect information identification and classification table; the defect weighted sorting module is used for calculating the defect degree score of each defect, recording the defect degree score in the defect degree score table, intelligently sorting the defects according to the defect degree scores and determining the sequence of repairing the defects.
And the display module 400 is configured to display the overhaul tasks sorted according to the defect degree scores. And the sequencing result is displayed and displayed at the terminal, so that the maintainers can conveniently check the sequencing result of the defect degree scores and visually acquire the sequence of processing the defects.
The transformer substation maintenance task processing system also comprises a first class group administrator terminal and a second class group administrator terminal,
the first maintenance task manager terminal is configured to send a vehicle closing request; the first task manager terminal sends the closing request and the defect information to the input module 200, and the input module receives the closing request and the defect information and sends the closing request and the defect information to the processing module 300.
The second maintenance task manager terminal is configured to receive the car closing request and send feedback information; the processing module 300 sends the closing request to a second maintenance task manager terminal meeting the requirement;
the processing module 300 is configured to extract information of a requested closing station point from the closing defect information; determining station information which is determined from the incidence matrix and has a correlation coefficient with the station combination station greater than a set coefficient; determining a station which can be combined through the incidence matrix;
and traversing a defect information identification classification table, and searching the defect information containing the determined site information and the corresponding second maintenance task. And identifying the station information containing the defects and the team information for distributing and repairing the defects in the defect information identification classification table, sending the closing information to a second repairing task manager terminal meeting the conditions, and waiting for the feedback of the closing information.
In some embodiments, the system further includes a purchase storage module, where the purchase storage module stores device name information, device holding amount information, and corresponding failure rate information of all devices in the substation; the fault rate information is obtained by counting the defect information by the processing module within a set period time; and the information of the quantity to be purchased is the product of the information of the reserved quantity of the equipment and the corresponding failure rate information. The maintenance personnel periodically count a fault information table, preferably, the period is one month, the fault information table includes device name information, device holding capacity information and fault rate information of the device, and the fault rate is obtained by dividing the number of times of faults of the device by the total number of faults in the month. And obtaining the number of the equipment to be purchased through the purchase storage module, and preferably, finally determining the number of the equipment to be purchased by matching with the voltage grade and the capacity parameter of the equipment.
The purchase of spare parts is assisted by the purchase storage module, the power failure caused by the lack of spare parts due to equipment faults is reduced by using limited expenses, and the stable operation of a transformer substation is ensured; in addition, during a large load period and a major social event period every year, a substation maintenance center needs to organize teams to carry out equipment inspection, and power substation maintenance personnel can be guided to carry out key inspection on equipment with high failure rate and common failure parts of the equipment through data provided by a failure information table; in addition, an expert experience base can be formed through the fault information table, a processing method is provided for inexperienced maintainers, and the overhauling efficiency is improved;
the transformer substation maintenance task processing system further comprises an equipment data storage module, and the equipment data storage module stores data information of all equipment in the transformer substation. Preferably, for example, as shown in table 6, a short circuit resistance dynamic calculation report, a transformer overall factory test report, a factory monitoring report, a three-dimensional impact recorder chart and escort record, an installation inspection and installation process record, an installation quality inspection and evaluation report, an equipment defect notice in the installation process, an equipment defect processing record and a handover test report are also preferably included.
Figure BDA0003473886310000121
TABLE 6 Transformer substation Equipment data information
The information of the power transformation equipment mainly comprises information related to equipment operation or technical improvement overhaul, all the information needs to be uploaded and recorded during the equipment operation, and the information is modified and supplemented during the technical improvement overhaul. The unit is responsible for uploading and modifying authority, and other unit employees can only access.
Example 5
Referring now to FIG. 5, shown is a block diagram of a computer system 700 suitable for use in implementing a terminal device or server of an embodiment of the present application.
As shown in fig. 5, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, the process described above with reference to fig. 1 may be implemented as a computer software program, according to an embodiment of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method of fig. 1. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The 5 th embodiment of the present application further provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs, which are used by one or more processors to execute the steps of the entity relationship query method of the logistics industry in the first embodiment.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims (10)

1. A transformer substation maintenance task processing method is characterized by comprising the following steps:
acquiring defect information, wherein the defect information comprises defect device type information and defect type information;
classifying defect information of the same defect device type to form a plurality of groups of maintenance tasks, and acquiring a defect information identification classification table;
calculating the defect degree score of each piece of defect information in each group of maintenance tasks;
Figure FDA0003473886300000011
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score of the nth influence factor on the ith defect，knIs the weight of the nth influence factor and satisfies
Figure FDA0003473886300000012
m is the total number of influencing factors;
and sequencing the defect information in each group of maintenance tasks according to the defect degree score.
2. The substation overhaul task processing method according to claim 1, wherein:
the defect information further includes defect site information; the method further comprises the following steps:
constructing an incidence matrix of all the defective site information, wherein the incidence matrix is constructed by incidence coefficients among all the sites;
and performing relevance marking on each piece of defect information with the relevance coefficient larger than the set coefficient in the maintenance task.
3. The substation overhaul task processing method of claim 2:
receiving a closing request initiated by a manager terminal of a first maintenance task; the car closing request comprises car closing defect information;
extracting information of requested station closing points from the vehicle closing defect information;
determining station information which is determined from the incidence matrix and has a correlation coefficient with the station combination station greater than a set coefficient;
traversing a defect information identification classification table, wherein the defect information table stores the defect information and the corresponding team name, and searching the defect information containing the determined site information and the corresponding second maintenance task;
sending the vehicle closing request to a manager terminal of a second maintenance task;
and receiving and forwarding the vehicle closing feedback information sent by the administrator of the second overhaul task to the administrator terminal of the first overhaul task.
4. The utility model provides a transformer substation overhauls task processing system which characterized in that: comprises that
The maintenance terminal is configured for inputting and uploading defect information;
an input module configured to receive defect information; the defect information comprises defect device type information and defect type information;
the processing module is configured for classifying the defect information of the same defect device type to form a plurality of groups of maintenance tasks;
calculating the defect degree score of each piece of defect information in each maintenance task;
Figure FDA0003473886300000021
f (i) is the defect degree score of the ith piece of defect information, i represents the ith equipment defect, and xn(i) The influence score, k, of the nth influencing factor on the ith defectnIs the weight of the nth influence factor and satisfies
Figure FDA0003473886300000022
m is the total number of influencing factors;
sorting the defect information in the maintenance task according to the defect degree score;
and the display module is configured for displaying the maintenance tasks which are sequenced according to the defect degree scores.
5. The substation overhaul task processing system of claim 4, wherein: the processing module is also configured with an incidence matrix for constructing all station information, and carries out incidence marking on each piece of defect information with incidence coefficient larger than a set coefficient in the maintenance task.
6. The substation overhaul task processing system of claim 4, wherein: also comprises a first class group administrator terminal and a second class group administrator terminal,
the first maintenance task manager terminal is configured to send a vehicle closing request;
the second maintenance task manager terminal is configured to receive the car closing request and send feedback information;
the processing module is configured to extract information of station points requested to be closed from the vehicle closing defect information;
determining station information which is determined from the incidence matrix and has a correlation coefficient with the station combination station greater than a set coefficient;
and traversing a defect information identification classification table, and searching the defect information containing the determined site information and the corresponding second maintenance task.
7. The substation overhaul task processing system of claim 4, wherein: the system also comprises a purchase storage module, wherein the purchase storage module stores equipment name information, equipment holding amount information and corresponding fault rate information of all equipment in the transformer substation; the fault rate information is obtained by counting the defect information by the processing module within a set period time; and the information of the quantity to be purchased is the product of the information of the reserved quantity of the equipment and the corresponding failure rate information.
8. The substation overhaul task processing system of claim 4, wherein: the transformer substation data storage system further comprises an equipment data storage module, and data information of all equipment in the transformer substation is stored in the equipment data storage module.
9. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: the processor, when executing the computer program, realizes the steps of the substation servicing task processing method according to any of claims 1 to 3.
10. A computer-readable storage medium having a computer program, wherein the computer program, when executed by a processor, implements the steps of the substation overhaul task processing method according to any one of claims 1 to 3.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106408439A (en) * 2015-11-18 2017-02-15 国家电网公司 Line inspection grade comprehensive evaluation method
CN109840711A (en) * 2019-02-14 2019-06-04 国网山东省电力公司菏泽供电公司 A kind of attached ancillary equipment defect analysis of substation and closed loop management system
CN110688389A (en) * 2019-08-30 2020-01-14 国网重庆市电力公司璧山供电分公司 Transformer substation secondary equipment defect cloud management system
CN113435652A (en) * 2021-07-01 2021-09-24 贵州电网有限责任公司 Primary equipment defect diagnosis and prediction method

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113935960A (en) * 2021-09-28 2022-01-14 景旺电子科技(珠海)有限公司 Defect overhauling method, device and equipment

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106408439A (en) * 2015-11-18 2017-02-15 国家电网公司 Line inspection grade comprehensive evaluation method
CN109840711A (en) * 2019-02-14 2019-06-04 国网山东省电力公司菏泽供电公司 A kind of attached ancillary equipment defect analysis of substation and closed loop management system
CN110688389A (en) * 2019-08-30 2020-01-14 国网重庆市电力公司璧山供电分公司 Transformer substation secondary equipment defect cloud management system
CN113435652A (en) * 2021-07-01 2021-09-24 贵州电网有限责任公司 Primary equipment defect diagnosis and prediction method

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