CN107730088A - A kind of controller switching equipment inspection scheme generation method and device based on distribution big data - Google Patents
A kind of controller switching equipment inspection scheme generation method and device based on distribution big data Download PDFInfo
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Abstract
The invention discloses a kind of controller switching equipment inspection scheme generation method and device based on distribution big data, gathers controller switching equipment running state data, running environment data and part throttle characteristics first, and store into device databases；Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, by each controller switching equipment integration requirement value of neural network prediction, and arranged；The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.The present invention carries out the tour of different frequency and the collection of different type parameter to distinct device, improve the accuracy of equipment-patrolling work, fundamentally solve equipment O＆M and make an inspection tour work only in accordance with transformer station's list progress solution formulation, effective lifting means operation management operating efficiency.
Description
Technical field
The present invention relates to a kind of controller switching equipment inspection scheme generation method and device based on distribution big data.
Background technology
Controller switching equipment operation management action includes being responsible for it on 10kV circuits in power supply area, switching station, cable point
The operation of the equipment such as the operational management of branch case and switchgear house, box-type substation, pole type transformer, safeguard.This requires its pair to set
It is standby to carry out periodical inspection inspection.At present, distribution O＆M teams and groups are still arranged switchgear house according to initial ranking method, then are pressed
Tour work is shared into each section according to time slice again to make an inspection tour switchgear house one by one.It is but at full speed due to distribution
Development, distribution network is in large scale, and controller switching equipment species and quantity are various, and most of circuit realizes contact, majority it is newly-built and
Transformation completes cell and realizes dual power supply, and original regular visit method can not meet will to the walkaround inspection of equipment
Ask.Simultaneously as requirement of the user for power supply reliability improves, power network sale of electricity side is decontroled, and has relied solely on passive repairing
Operation demand instantly can not be adapted to.Therefore, a kind of method of controller switching equipment inspection schemes generation how is designed, to improve O＆M
Operating efficiency is maked an inspection tour, becomes passive repairing and is overhauled into active, be still technical problem to be solved.
The content of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the invention provides a kind of controller switching equipment based on distribution big data to patrol
Scheme generation method and device are examined, running environment characteristic is quantified, many influence factors is additionally arranged, avoids regular visit
Excessively mechanical caused by method, inflexible shortcoming, so as to promote the lifting of equipment operation management efficiency in overall terms,
Really realize the discovery timely, as early as possible to " abnormal condition " equipment.
The technical solution adopted in the present invention is：
A kind of controller switching equipment inspection scheme generation method based on distribution big data, comprises the following steps：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through nerve
Each controller switching equipment integration requirement value of neural network forecast, and arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
Further, when the controller switching equipment running state data includes the voltage, electric current, repairing history of controller switching equipment
Between, repairing processing defect rank, record of examination, odd-job and number of operations.
Further, the controller switching equipment running environment data include controller switching equipment operation area, the time limit that puts into operation, model,
Type, assets ownership, maintenance record, secondary use and producer.
Further, the part throttle characteristics includes Seasonal Characteristics and daily part throttle characteristics.
Further, parameter quantization is carried out to data in device databases, by the supplemental characteristic storage after quantization to quantization
In database, including：According to device history data and empirical data, to each controller switching equipment running status number in device databases
Parameter quantization is carried out according to, running environment data and part throttle characteristics, the supplemental characteristic after quantization is stored into quantized data storehouse, its
In, the device history data includes device history fault rate, health state evaluation and device history overhaul data.
Further, multiple parameters data are extracted from quantized data storehouse and obtain neutral net as training sample, training,
By each controller switching equipment integration requirement value of neural network prediction, and arranged, including：
Step 1：Instruction of the multiple parameters data of same station power distribution equipment as neutral net is extracted from quantized data storehouse
Practice sample；
Step 2：It is used for the neutral net of controller switching equipment using training algorithm simulation training；
Step 3：, can using neural network prediction controller switching equipment based on the running state parameter data new by controller switching equipment
Potential safety hazard existing for energy, using the potential safety hazard as controller switching equipment integration requirement value；
Step 4：Repeat step 1-3, until all controller switching equipment integration requirement values are tried to achieve, according to inspection priority, by institute
There is controller switching equipment integration requirement value to be arranged.
Further, the major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme
List, including：Controller switching equipment integration requirement value, which is generated, which influences maximum equipment running status supplemental characteristic, is reversely analyzed,
The origin of potential safety hazard is determined, formulates corresponding control measures, overall inspection scheme list is generated in conjunction with potential safety hazard.
Further, the overall inspection scheme list include controller switching equipment tour order, there may be defect and just
Walk embodiment.
A kind of computer installation, for the controller switching equipment inspection schemes generation based on distribution big data, including memory, place
Reason device and storage on a memory and the computer program that can run on a processor, reality during the computing device described program
Existing following steps, including：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through nerve
Each controller switching equipment integration requirement value of neural network forecast, and arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
A kind of computer-readable recording medium, it is stored thereon with for the controller switching equipment inspection scheme based on distribution big data
The computer program of generation, the program realize following steps when being executed by processor：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through nerve
Each controller switching equipment integration requirement value of neural network forecast, and arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
Compared with prior art, the beneficial effects of the invention are as follows：
(1) present invention collection controller switching equipment running state data, running environment data and part throttle characteristics, as controller switching equipment
Running status historical data；The data of controller switching equipment are collected and arranged, and then establish the big data base of device databases
Plinth, parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse, realization is matched somebody with somebody
The quantization arrangement of electric equipment running status, based on the controller switching equipment running state data, further complete controller switching equipment and patrol
Work requirements list is examined, takes full advantage of the advantage of big data, effectively improves the efficiency of plan that O＆M makes an inspection tour work；
(2) present invention may be deposited based on neutral net using the running state parameter data prediction controller switching equipment of controller switching equipment
Potential safety hazard, using the potential safety hazard as controller switching equipment integration requirement value, and arranged, realize look-ahead distribution
The defects of operation may occur simultaneously carries out inspection according to defect level sequence, and maintenance work efficiency can be substantially improved；
(3) present invention takes full advantage of the advantage of big data, effectively provides the efficiency of plan that O＆M makes an inspection tour work, is generating
During controller switching equipment inspection scheme, take into full account that equipment operating environment, part throttle characteristics and hidden troubles removing etc. influence so that generation
New equipment-patrolling scheme more science, rationally, efficiently, can realize in different environment, load period, distinct device is entered
The tour of row different frequency and the collection of different type parameter, and then the accuracy of equipment-patrolling work is improved, from basic
On solve equipment O＆M and make an inspection tour work and carry out solution formulation, no equipment Selective, no history number only in accordance with transformer station list
According to reference to the defects of property, during solution formulation, it is reference frame to add equipment operating environment with running status action,
Effective lifting means operation management operating efficiency.
Brief description of the drawings
The Figure of description for forming the part of the application is used for providing further understanding of the present application, and the application's shows
Meaning property embodiment and its illustrate be used for explain the application, do not form the improper restriction to the application.
Fig. 1 is the controller switching equipment inspection scheme generation method flow based on distribution big data disclosed in the embodiment of the present invention
Figure；
Fig. 2 is the disclosed overall inspection scheme list flow chart of generation of the embodiment of the present invention；
Fig. 3 is controller switching equipment inspection scheme list schematic diagram disclosed in the embodiment of the present invention.
Embodiment
It is noted that described further below is all exemplary, it is intended to provides further instruction to the application.It is unless another
Indicate, all technologies used herein and scientific terminology are with usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singulative
It is also intended to include plural form, additionally, it should be understood that, when in this manual using term "comprising" and/or " bag
Include " when, it indicates existing characteristics, step, operation, device, component and/or combinations thereof.
As background technology is introduced, equipment O＆M in the prior art be present and make an inspection tour work only in accordance with transformer station's list
Progress solution formulation, no equipment Selective, the deficiency of no historical data reference property, in order to solve technical problem as above, this Shen
A kind of controller switching equipment inspection scheme generation method and device based on distribution big data please be propose, running environment characteristic is carried out
Quantify, be additionally arranged many influence factors, avoid excessively mechanical, inflexible shortcoming caused by regular visit method, so as to
Promote the lifting of equipment operation management efficiency in overall terms, really realize to the timely, as early as possible of " abnormal condition " equipment
Discovery.
Embodiment one
As shown in Figure 1-2, the purpose of the present embodiment is to provide a kind of controller switching equipment inspection scheme based on distribution big data
Generation method, this method comprise the following steps：
Step 1：Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and stores and arrives number of devices
According in storehouse.
Wherein, the voltage of the controller switching equipment running state data including controller switching equipment, electric current, repairing historical time, rob
Repair processing defect rank, record of examination, odd-job and number of operations；The controller switching equipment running environment data are set including distribution
Standby operation area, the time limit that puts into operation, model, type, assets ownership, maintenance record, secondary use and producer；The part throttle characteristics is
Meet the change of current curve, including Seasonal Characteristics and daily part throttle characteristics.
The application has taken into full account the influence of equipment operating environment and part throttle characteristics so that the new equipment-patrolling side of generation
Case more science, rationally, efficiently, can realize in different environment, load period, to distinct device carry out different frequency patrol
Depending on and different type parameter collection.
Step 2：Parameter quantization is carried out to data in device databases, quantized data is arrived into the supplemental characteristic storage after quantization
In storehouse.
To in device databases data carry out parameter quantization specific method be：
According to device history data and empirical data, to each controller switching equipment running state data, fortune in device databases
Row environmental data and part throttle characteristics carry out parameter quantization, and the supplemental characteristic after quantization is stored into quantized data storehouse.Wherein, institute
Stating device history data includes device history fault rate, health state evaluation and device history overhaul data.
Present invention collection controller switching equipment running state data, running environment data and part throttle characteristics, are transported as controller switching equipment
Row status history data；The data of controller switching equipment are collected and arranged, and then establish the big data basis of device databases,
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse, realizes distribution
The quantization arrangement of equipment running status, based on the controller switching equipment running state data, further completes controller switching equipment inspection
Work requirements list.The present invention takes full advantage of the advantage of big data, effectively improves the efficiency of plan that O＆M makes an inspection tour work.
Step 3：Multiple parameters data are extracted from quantized data storehouse and obtain neutral net as training sample, training, are led to
Each controller switching equipment integration requirement value of neural network prediction is crossed, and is arranged；
The specific method for predicting each controller switching equipment integration requirement value is：
Step 31：Instruction of 15 supplemental characteristics of same station power distribution equipment as neutral net is extracted from quantized data storehouse
Practice sample；
Step 32：It is used for the neutral net of controller switching equipment using training algorithm simulation training；
Step 33：Based on the running state parameter data new by controller switching equipment, neural network prediction controller switching equipment is utilized
Potential safety hazard that may be present, using the potential safety hazard as controller switching equipment integration requirement value；
Step 34：Repeat step 31-33,, will according to inspection priority up to trying to achieve all controller switching equipment integration requirement values
All controller switching equipment integration requirement values are arranged.
In the present invention, the running state parameter data of same station power distribution equipment in training sample are imported as neutral net
Input layer, output layer of the potential safety hazard as neutral net of controller switching equipment in training sample is imported, using BP algorithm to god
Simulation training is carried out through network, training, which finishes to obtain one, can predict that the nerve net of potential safety hazard may occur for controller switching equipment
Network, neutral net, will using the new running state parameter data prediction controller switching equipment potential safety hazard that may be present of controller switching equipment
The potential safety hazard is arranged as controller switching equipment integration requirement value.The present invention realizes look-ahead may with network operation
The defects of generation, simultaneously carries out inspection according to defect level sequence, and maintenance work efficiency can be substantially improved.
Step 4：Analyze the major influence factors of each controller switching equipment integration requirement value, generation controller switching equipment inspection scheme row
Table.
Generation controller switching equipment inspection scheme list specific method be：
Controller switching equipment integration requirement value, which is generated, which influences maximum equipment running status supplemental characteristic, is reversely analyzed, really
Determine the origin of potential safety hazard, formulate corresponding control measures as work particular content is maked an inspection tour, in conjunction with potential safety hazard in itself
Description generates transformer patrol plan to generate overall inspection scheme list.Wherein, as shown in figure 3, the overall inspection scheme
List includes controller switching equipment tour order, there may be defect and preliminary embodiment.
The present invention enters row major for line facility to be maked an inspection tour and makes an inspection tour sequence, and the inspection scheme with priority of generation is to patrolling
Examining work has preferably directiveness, fundamentally solves a series of problems for perplexing maintenance work always, is maintenance work
New Thoughts are brought, improve the accuracy of equipment-patrolling work, O＆M is greatly improved and makes an inspection tour efficiency, by limited manpower
Resource more fully plays, and is solved using big data generation controller switching equipment inspection scheme between shortage of manpower and distribution development
Contradiction.The controller switching equipment inspection scheme list that the present invention ultimately generates can reflect the urgent degree of the tour of equipment to be maked an inspection tour, and refer to
Lead teams and groups of basic unit and rationally carry out walkaround inspection work, and then the purpose of defect hidden danger " early to find early processing " can be reached, have
It is predictable, repairing workload will be greatly reduced, reduce frequency of power cut and time, and reduce the complaint triggered by fault outage.
Compared to used equipment periodical inspection Design Method, the present invention is by by controller switching equipment running status, operation
Environment and part throttle characteristics are quantified, and are remained in original tour scheme and are differentiated the excellent of tour priority according to practical production experience
Gesture, simultaneously as being additionally arranged many other influence factors, it is thus also avoided that excessively mechanical, ineffective caused by periodical inspection method
The shortcomings that living, so as to promote the lifting of equipment operation management efficiency in overall terms, really realize and " abnormal condition " is set
Standby discovery timely, as early as possible.
The present invention takes full advantage of the advantage of big data, effectively provides the efficiency of plan that O＆M makes an inspection tour work.Match somebody with somebody in generation
No longer it is to carry out equipment-patrolling solution formulation only by transformer station, but taken into full account equipment during electric equipment inspection scheme
Running environment, part throttle characteristics and hidden troubles removing etc. influence so that the new equipment-patrolling scheme of generation more science, reasonable, height
Effect, can be realized in different environment, load period, and tour and the different type parameter of different frequency are carried out to distinct device
Collection, and then improve equipment-patrolling work accuracy, fundamentally solve equipment O＆M make an inspection tour work only in accordance with
Transformer station's list carries out solution formulation, and no equipment Selective, no historical data is with reference to the defects of property, during solution formulation,
It is reference frame to add equipment operating environment and running status action, can effective lifting means operation management operating efficiency.
Embodiment two
The purpose of the present embodiment is to provide a kind of computer installation, for the controller switching equipment inspection side based on distribution big data
Case generates, including memory, processor and storage are on a memory and the computer program that can run on a processor, its feature
It is, realizes following steps during the computing device described program, including：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through nerve
Each controller switching equipment integration requirement value of neural network forecast, and arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
Embodiment three
The purpose of the present embodiment is to provide a kind of computer-readable recording medium, is stored thereon with for being based on the big number of distribution
According to controller switching equipment inspection schemes generation computer program, it is characterised in that realized when the program is executed by processor following
Step：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through nerve
Each controller switching equipment integration requirement value of neural network forecast, and arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
Although above-mentioned the embodiment of the present invention is described with reference to accompanying drawing, model not is protected to the present invention
The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not
Need to pay various modifications or deformation that creative work can make still within protection scope of the present invention.
Claims (10)
1. a kind of controller switching equipment inspection scheme generation method based on distribution big data, it is characterized in that, comprise the following steps：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through neutral net
Each controller switching equipment integration requirement value is predicted, and is arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
2. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, institute
State the voltage of controller switching equipment running state data including controller switching equipment, electric current, repairing historical time, repairing processing defect rank,
Record of examination, odd-job and number of operations.
3. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, institute
Stating controller switching equipment running environment data includes controller switching equipment operation area, the time limit that puts into operation, model, type, assets ownership, maintenance note
Record, secondary use and producer.
4. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, institute
Stating part throttle characteristics includes Seasonal Characteristics and daily part throttle characteristics.
5. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, it is right
Data carry out parameter quantization in device databases, and the supplemental characteristic after quantization is stored into quantized data storehouse, including：According to setting
Standby historical data and empirical data, to each controller switching equipment running state data, running environment data in device databases and bear
Lotus characteristic carries out parameter quantization, and the supplemental characteristic after quantization is stored into quantized data storehouse, wherein, the device history data
Including device history fault rate, health state evaluation and device history overhaul data.
6. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, from
Multiple parameters data are extracted in quantized data storehouse as training sample, training obtains neutral net, each by neural network prediction
Controller switching equipment integration requirement value, and arranged, including：
Step 1：Training sample of the multiple parameters data as neutral net of same station power distribution equipment is extracted from quantized data storehouse
This；
Step 2：It is used for the neutral net of controller switching equipment using training algorithm simulation training；
Step 3：Based on the running state parameter data new by controller switching equipment, it may be deposited using neural network prediction controller switching equipment
Potential safety hazard, using the potential safety hazard as controller switching equipment integration requirement value；
Step 4：Repeat step 1-3, until trying to achieve all controller switching equipment integration requirement values, according to inspection priority, match somebody with somebody all
Electric equipment integration requirement value is arranged.
7. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, point
The major influence factors of each controller switching equipment integration requirement value are analysed, generate controller switching equipment inspection scheme list, including：To controller switching equipment
The generation of integration requirement value influences maximum equipment running status supplemental characteristic and reversely analyzed, and determines the origin of potential safety hazard,
Corresponding control measures are formulated, overall inspection scheme list is generated in conjunction with potential safety hazard.
8. the controller switching equipment inspection scheme generation method according to claim 1 based on distribution big data, it is characterized in that, institute
Stating overall inspection scheme list includes controller switching equipment tour order, there may be defect and preliminary embodiment.
A kind of 9. computer installation, for the controller switching equipment inspection schemes generation based on distribution big data, including memory, processing
Device and storage on a memory and the computer program that can run on a processor, it is characterized in that, described in the computing device
Following steps are realized during program, including：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through neutral net
Each controller switching equipment integration requirement value is predicted, and is arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
10. a kind of computer-readable recording medium, it is stored thereon with for the controller switching equipment inspection scheme based on distribution big data
The computer program of generation, it is characterized in that, the program realizes following steps when being executed by processor：
Controller switching equipment running state data, running environment data and part throttle characteristics are gathered, and is stored into device databases；
Parameter quantization is carried out to data in device databases, the supplemental characteristic after quantization is stored into quantized data storehouse；
Multiple parameters data are extracted from quantized data storehouse to obtain neutral net as training sample, training, pass through neutral net
Each controller switching equipment integration requirement value is predicted, and is arranged；
The major influence factors of each controller switching equipment integration requirement value are analyzed, generate controller switching equipment inspection scheme list.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109816308A (en) * | 2019-01-18 | 2019-05-28 | 广东电网有限责任公司 | A kind of equipment routing inspection householder method, apparatus and system |
| CN109905885A (en) * | 2018-04-12 | 2019-06-18 | 华为技术有限公司 | A kind of method and inspection device of determining inspection station list |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400224A (en) * | 2013-07-25 | 2013-11-20 | 广州供电局有限公司 | GIS equipment maintenance method and GIS equipment maintenance aid decision system |
| US20150127277A1 (en) * | 2013-11-06 | 2015-05-07 | Electric Power Research Institute, Inc. | System and method for assessing power transformers |
| CN105225020A (en) * | 2015-11-11 | 2016-01-06 | 国家电网公司 | A kind of running status Forecasting Methodology based on BP neural network algorithm and system |
| CN106204330A (en) * | 2016-07-18 | 2016-12-07 | 国网山东省电力公司济南市历城区供电公司 | A kind of power distribution network intelligent diagnosis system |
-
2017
- 2017-09-20 CN CN201710854453.4A patent/CN107730088A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103400224A (en) * | 2013-07-25 | 2013-11-20 | 广州供电局有限公司 | GIS equipment maintenance method and GIS equipment maintenance aid decision system |
| US20150127277A1 (en) * | 2013-11-06 | 2015-05-07 | Electric Power Research Institute, Inc. | System and method for assessing power transformers |
| CN105225020A (en) * | 2015-11-11 | 2016-01-06 | 国家电网公司 | A kind of running status Forecasting Methodology based on BP neural network algorithm and system |
| CN106204330A (en) * | 2016-07-18 | 2016-12-07 | 国网山东省电力公司济南市历城区供电公司 | A kind of power distribution network intelligent diagnosis system |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109905885A (en) * | 2018-04-12 | 2019-06-18 | 华为技术有限公司 | A kind of method and inspection device of determining inspection station list |
| CN109905885B (en) * | 2018-04-12 | 2021-02-12 | 华为技术有限公司 | Method for determining polling base station list and polling device |
| CN111277427A (en) * | 2018-12-05 | 2020-06-12 | ***通信集团河南有限公司 | Data center network equipment inspection method and system |
| CN109816308A (en) * | 2019-01-18 | 2019-05-28 | 广东电网有限责任公司 | A kind of equipment routing inspection householder method, apparatus and system |
| CN110189575A (en) * | 2019-06-27 | 2019-08-30 | 广东电网有限责任公司肇庆供电局 | A kind of distribution O&M simulation training system based on big data |
| CN110189575B (en) * | 2019-06-27 | 2021-01-05 | 广东电网有限责任公司肇庆供电局 | Big data-based distribution network operation and maintenance simulation training system |
| CN111047703A (en) * | 2019-12-23 | 2020-04-21 | 杭州电力设备制造有限公司 | User high-voltage distribution equipment identification and space reconstruction method |
| CN111047703B (en) * | 2019-12-23 | 2023-09-26 | 杭州电力设备制造有限公司 | User high-voltage distribution equipment identification and space reconstruction method |
| CN111443091B (en) * | 2020-04-08 | 2023-07-25 | 中国电力科学研究院有限公司 | Cable line tunnel engineering defect judging method |
| CN111443091A (en) * | 2020-04-08 | 2020-07-24 | 中国电力科学研究院有限公司 | Cable line tunnel engineering defect judgment method |
| CN112862249A (en) * | 2021-01-12 | 2021-05-28 | 广州市锐赛科技有限公司 | Lean management method and system for intelligent power distribution equipment |
| CN112862249B (en) * | 2021-01-12 | 2022-01-25 | 广州市锐赛科技有限公司 | Lean management method and system for intelligent power distribution equipment |
| CN113837403A (en) * | 2021-08-27 | 2021-12-24 | 深圳市飞思捷跃科技有限公司 | Self-learning Internet of things maintenance plan generation system |
| CN113780427A (en) * | 2021-09-14 | 2021-12-10 | 国网江苏省电力有限公司电力科学研究院 | Medium-voltage distribution network patrol period automation method and system based on machine learning |
| CN115221851A (en) * | 2022-06-23 | 2022-10-21 | 武汉胜天地消防工程有限公司 | Analysis processing method and analysis processing system for operation and maintenance inspection form data of power station |
| CN115221851B (en) * | 2022-06-23 | 2023-08-29 | 智瞻科技股份有限公司 | Analysis processing method and analysis processing system for operation and maintenance inspection form data of electric power station |
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