CN117335577A - Method and system for monitoring state of pole-mounted switch and controller - Google Patents
Method and system for monitoring state of pole-mounted switch and controller Download PDFInfo
- Publication number
- CN117335577A CN117335577A CN202311628822.XA CN202311628822A CN117335577A CN 117335577 A CN117335577 A CN 117335577A CN 202311628822 A CN202311628822 A CN 202311628822A CN 117335577 A CN117335577 A CN 117335577A
- Authority
- CN
- China
- Prior art keywords
- controller
- switch
- index
- fuzzy
- matrix
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 82
- 238000000034 method Methods 0.000 title claims abstract description 48
- 239000011159 matrix material Substances 0.000 claims abstract description 81
- 238000011156 evaluation Methods 0.000 claims abstract description 71
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 58
- 230000002068 genetic effect Effects 0.000 claims abstract description 45
- 238000000137 annealing Methods 0.000 claims abstract description 29
- 230000006870 function Effects 0.000 claims description 17
- 238000012423 maintenance Methods 0.000 claims description 16
- 238000004146 energy storage Methods 0.000 claims description 10
- 238000001816 cooling Methods 0.000 claims description 9
- 238000007689 inspection Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 238000010606 normalization Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 206010064571 Gene mutation Diseases 0.000 claims description 3
- 210000000349 chromosome Anatomy 0.000 claims description 3
- 230000035772 mutation Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 108090000623 proteins and genes Proteins 0.000 claims description 3
- 238000013077 scoring method Methods 0.000 claims description 3
- 238000010353 genetic engineering Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 13
- 238000002922 simulated annealing Methods 0.000 abstract description 12
- 238000004891 communication Methods 0.000 description 10
- 238000012806 monitoring device Methods 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 6
- 230000007547 defect Effects 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 5
- 230000007246 mechanism Effects 0.000 description 5
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 4
- 238000013528 artificial neural network Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000004587 chromatography analysis Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 229910001220 stainless steel Inorganic materials 0.000 description 3
- 239000010935 stainless steel Substances 0.000 description 3
- 230000001174 ascending effect Effects 0.000 description 2
- 230000001351 cycling effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 229910052742 iron Inorganic materials 0.000 description 2
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 description 2
- 230000009191 jumping Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 235000005770 birds nest Nutrition 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 235000005765 wild carrot Nutrition 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
Abstract
The invention belongs to the technical field of state monitoring, and provides a state monitoring method and a state monitoring system for a pole-mounted switch and a controller, wherein a fuzzy judgment matrix is solved by using a genetic annealing algorithm to obtain each index weight; multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix; according to the index layer comprehensive evaluation matrix, calculating by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix for representing the states of the on-column switch and the controller; on the basis of the fuzzy analytic hierarchy process, the advantages of a genetic algorithm and a simulated annealing algorithm are combined, the genetic annealing algorithm is utilized, the evolution mode of selecting crossover variation in the genetic algorithm is reserved, and the simulated annealing algorithm is utilized to jump out a local optimal solution, so that the algorithm can be quickly converged to a global optimal solution; the genetic annealing algorithm is applied to solving of the fuzzy judgment matrix, so that the problem that the fuzzy judgment matrix is difficult to meet the complete consistency condition due to index diversity and subjectivity can be effectively solved.
Description
Technical Field
The invention belongs to the technical field of state monitoring, and particularly relates to a state monitoring method and system of a pole-mounted switch and a controller.
Background
The pole-mounted switch and the controller have fault current action protection functions, the controller judges a fault area through protection logic, and the pole-mounted switch is controlled to perform switching-on and switching-off operation, so that the accident power failure range can be effectively reduced, and the power supply reliability is improved. However, as the operation period increases, the on-column switch can have the problems of mechanism jamming failure, switching indication failure and the like, and the phenomenon of protection misoperation and refusal operation occurs, meanwhile, the controller can not accurately operate the on-column switch due to more electronic components, so that the failure can not be accurately isolated, and the power failure range is enlarged. At present, the number of the on-column switches and controllers is huge, the positions are scattered, the running state and the running environment are lack of real-time monitoring means, and the on-column switches and controllers cannot be managed in a lean way and accurately operated and maintained, so that the on-column switches and controllers are in a blind pipe state; therefore, state monitoring of the on-column switches and controllers is required to discover and solve the failure problem in time.
The inventor finds that a state monitoring method suitable for a pole switch and a controller does not exist at present; in the state monitoring methods of other targets, a neural network method and a fuzzy comprehensive evaluation method are commonly used; the neural network method has great requirements on the data volume, and the accuracy of the evaluation result can be reduced due to the small data volume; according to the fuzzy comprehensive evaluation method, subjective indexes such as equipment appearance and the like exist in the information quantity acquired by the state acquisition device, so that a fuzzy judgment matrix in the fuzzy comprehensive evaluation method is difficult to meet the consistency requirement, and the accuracy of a final evaluation result is influenced. In addition, the constant index weight in the existing method cannot meet the requirement that the degree of influence of indexes on the state of equipment in the running process of a switch and a controller needs to be dynamically adjusted.
Disclosure of Invention
The invention provides a method and a system for monitoring the state of a switch and a controller on a column, which are used for solving the problems, and combines the advantages of a genetic algorithm and a simulated annealing algorithm on the basis of a fuzzy analytic hierarchy process, and the genetic annealing algorithm is utilized to not only keep the evolution mode of selecting crossover variation in the genetic algorithm, but also jump out of a local optimal solution by adopting the simulated annealing algorithm, so that the algorithm can be quickly converged to a global optimal solution; the genetic annealing algorithm is applied to solving of the fuzzy judgment matrix, the problem that the fuzzy judgment matrix is difficult to meet the complete consistency condition due to index diversity and subjectivity can be effectively solved, the condition that the influence degree of indexes on the state of equipment in the running process of a switch and a controller needs to be dynamically adjusted is met, and the accuracy of state evaluation is improved.
In order to achieve the above object, the present invention is realized by the following technical scheme:
in a first aspect, the present invention provides a method for monitoring a state of a pole-mounted switch and a controller, including:
acquiring relevant monitoring information of a switch and a controller on a column;
constructing a hierarchical structure model of the on-column switch and the controller, wherein the hierarchical structure model comprises a target layer, a factor layer and an index layer, according to the relevant monitoring information;
constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller;
solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight;
multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix;
and calculating according to the index layer comprehensive evaluation matrix by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix representing the states of the on-column switch and the controller.
Further, the relevant monitoring information comprises one or more of an ambient temperature signal, an ambient humidity signal, an on-pole switch shell image, a controller shell image, a vacuum tube vacuum degree signal of a vacuum circuit breaker, an SF6 circuit breaker pressure signal, a contact temperature signal, an opening and closing coil state signal, an energy storage state signal, a closing time signal and a fault-free working time signal.
Further, the target layer is a column switch and a controller running state; the factor layer is divided into an on-line monitoring state quantity, a mechanical test state quantity and an operation and maintenance inspection state quantity; the index layer is used for each index in the related monitoring information.
Further, carrying out normalization processing on quantitative indexes in the related monitoring information according to specific numerical values; and carrying out normalization processing on the qualitative indexes in the related monitoring information according to a section scoring method.
Further, the genetic annealing algorithm solves the weights of all indexes as follows:
wherein,i，j=1，2，...，n，nis the number of elements;is the difference of importance degree among elements, wherein +.>The weight value of the element; />Matrix elements are judged for the paste.
Further, the genetic annealing algorithm includes: determining the form of the chromosome according to the actual problem codes; initializing an initial temperature, a termination temperature and a cooling coefficient; initializing a population, determining the population scale and genetic algebra, and randomly generating individuals with a given population scale; calculating the fitness of each individual according to the fitness function; selecting a parent for genetic manipulation by selecting a function and individual fitness; performing cross operation on the genes of the parent individuals according to a certain mode, then performing gene mutation operation according to the mutation rate, finally generating new individuals, and calculating the adaptability of the new individuals; comparing the fitness of the parent and the offspring, and judging whether to accept the offspring as the individuals of the new population according to the Metropolis acceptance criterion; circularly calculating the fitness of each individual until judging whether to accept the offspring as the individual content of the new population until the genetic algebra is reached; cooling operation is carried out; and initializing the population to the cooling operation content in a circulating way until reaching the end temperature.
Further, on-column switch and controller status includes normal, attention, abnormal and emergency.
In a second aspect, the present invention also provides a status monitoring system for a pole-mounted switch and a controller, including:
a data acquisition module configured to: acquiring relevant monitoring information of a switch and a controller on a column;
a layering module configured to: constructing a hierarchical structure model of the on-column switch and the controller, wherein the hierarchical structure model comprises a target layer, a factor layer and an index layer, according to the relevant monitoring information;
a matrix construction module configured to: constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller;
the index weight solving module is configured to: solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight;
the comprehensive evaluation matrix construction module is configured to: multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix;
a state evaluation module configured to: and calculating according to the index layer comprehensive evaluation matrix by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix representing the states of the on-column switch and the controller.
In a third aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the method for monitoring the status of a pole switch and controller of the first aspect.
In a fourth aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for monitoring the status of the on-column switch and the controller according to the first aspect when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
firstly, constructing a hierarchical structure model of a switch and a controller on a building column comprising a target layer, a factor layer and an index layer according to related monitoring information; constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller; then, solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight; multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix; finally, according to the index layer comprehensive evaluation matrix, calculating by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix for representing the states of the on-column switch and the controller; on the basis of the fuzzy analytic hierarchy process, the advantages of a genetic algorithm and a simulated annealing algorithm are combined, the genetic annealing algorithm is utilized, the evolution mode of selecting crossover variation in the genetic algorithm is reserved, and the simulated annealing algorithm is utilized to jump out a local optimal solution, so that the algorithm can be quickly converged to a global optimal solution; the genetic annealing algorithm is applied to solving of the fuzzy judgment matrix, the problem that the fuzzy judgment matrix is difficult to meet the complete consistency condition due to index diversity and subjectivity can be effectively solved, the condition that the influence degree of indexes on the state of equipment in the running process of a switch and a controller needs to be dynamically adjusted is met, and the accuracy of state evaluation is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification, illustrate and explain the embodiments and together with the description serve to explain the embodiments.
FIG. 1 is a schematic diagram of the installation of a monitoring device according to embodiment 1 of the present invention;
FIG. 2 is an on-line monitoring system according to embodiment 1 of the present invention;
fig. 3 is a state monitoring device for an opening/closing coil according to embodiment 1 of the present invention;
fig. 4 is a current state monitoring device of an energy storage motor according to embodiment 1 of the present invention;
FIG. 5 is a state monitoring system according to embodiment 1 of the present invention;
FIG. 6 is a flowchart of the genetic annealing algorithm according to embodiment 1 of the present invention;
FIG. 7 is a flow chart of a fuzzy chromatography method based on the improvement of the genetic annealing algorithm in the embodiment 1 of the present invention;
1, video monitoring front-end equipment; 11. a camera; 111. a camera bracket; 12. a power module; 121. a voltage transformer; 122. a storage battery; 123. a battery holder; 13. a video server; 2. communication equipment.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
Example 1:
along with the continuous promotion of the power load, the requirements of people on the quality of electric energy and the reliability of power supply are higher and higher, and the power failure in a short time can have great influence on society and economy. The pole-mounted switch and the controller have fault current action protection functions, the controller judges a fault area through protection logic, and the pole-mounted switch is controlled to perform switching-on and switching-off operation, so that the accident power failure range can be effectively reduced, and the power supply reliability is improved. However, as the operation period increases, the on-column switch can have the problems of mechanism jamming failure, switching indication failure and the like, and the phenomenon of protection misoperation and refusal operation occurs, meanwhile, the controller can not accurately operate the on-column switch due to more electronic components, so that the failure can not be accurately isolated, and the power failure range is enlarged. At present, the number of the on-column switches and controllers is huge, the positions are scattered, the running state and the running environment are lack of real-time monitoring means, and the on-column switches and controllers cannot be managed in a lean way and accurately operated and maintained, so that the on-column switches and controllers are in a blind pipe state; only when the line fails and cannot be isolated correctly, operation and maintenance personnel can passively conduct on-site investigation and maintenance, so that the power failure range is enlarged, and the execution efficiency is low. Therefore, the method changes the passive defect elimination into the active operation and maintenance, realizes the considerable controllability of the on-column switch and the controller, monitors the running state of the on-column switch and the controller by monitoring the on-site condition, judges the health state of the on-column switch and the controller by using a state evaluation model, discovers hidden danger in advance, reasonably plans the maintenance period, maintains the health state of equipment and has important significance for improving the power supply reliability.
At present, the collected state quantity is calculated through a state evaluation algorithm, so that the current state of the equipment can be evaluated, and the equipment has certain reference for the operation and maintenance of the equipment. In the state evaluation method, a neural network method and a fuzzy comprehensive evaluation method are commonly used. The neural network method has great requirements on the data volume, and the accuracy of the evaluation result can be reduced due to the small data volume. If the fuzzy comprehensive evaluation method is adopted, subjective indexes such as equipment appearance and the like exist in the information quantity acquired by the state acquisition device, so that a fuzzy judgment matrix in the fuzzy comprehensive evaluation method is difficult to meet the consistency requirement, and the accuracy of a final evaluation result is influenced. In addition, in the running process of the switch and the controller, the influence degree of the index on the state of the equipment needs to be dynamically adjusted, so that the weight of each index is not constant and needs to be optimized.
In view of the above problems, the present embodiment provides a method for monitoring a state of a switch and a controller on a column, firstly, constructing a hierarchical structure model of the switch and the controller on the column including a target layer, a factor layer and an index layer according to relevant monitoring information; constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller; then, solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight; multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix; finally, according to the index layer comprehensive evaluation matrix, calculating by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix for representing the states of the on-column switch and the controller; on the basis of the fuzzy analytic hierarchy process, the advantages of a genetic algorithm and a simulated annealing algorithm are combined, the genetic annealing algorithm is utilized, the evolution mode of selecting crossover variation in the genetic algorithm is reserved, and the simulated annealing algorithm is utilized to jump out a local optimal solution, so that the algorithm can be quickly converged to a global optimal solution; the genetic annealing algorithm is applied to solving of the fuzzy judgment matrix, the problem that the fuzzy judgment matrix is difficult to meet the complete consistency condition due to index diversity and subjectivity can be effectively solved, the condition that the influence degree of indexes on the state of equipment in the running process of a switch and a controller needs to be dynamically adjusted is met, and the accuracy of state evaluation is improved.
The on-pole switch is arranged outdoors, and the problems of mechanism jamming failure, switching indication failure and the like exist in long-term operation, and as the switching position and the switching position of the on-pole switch cannot be displayed in a master station system, operation and maintenance personnel are required to arrive at the site to conduct hidden trouble investigation. The number of the switches on the column is large, the positions are dispersed, a great deal of manpower and material resources are wasted in on-site inspection, and the working efficiency is low. The pole-mounted switch is arranged outdoors, and foreign matters such as bird nest, iron wire, small animals and the like can not fall on the wire outlet of the pole-mounted switch, and short circuit, grounding faults and the like can not exist. In order to eliminate hidden danger, regular patrol, special patrol and other works are required to be carried out, and the workload of operation and maintenance personnel is increased; meanwhile, short faults caused by foreign matters, such as iron wires held by birds, fall on the switch access lines on the posts, and the fault causes are not easy to find because of the lack of auxiliary analysis materials because no trace is found afterwards, and the power supply reliability is affected. When the master station receives the switching signal, the on-site switch has the condition of non-action due to the reasons of terminal failure, switch switching auxiliary contact damage and the like, so that the system signal of the master station is inconsistent with the on-site condition; in order to ensure the accuracy of the signals, the on-site check needs to be carried out on each split signal, and the phenomena of low working efficiency and waste of manpower and material resources exist. The on-pole switch and the controller are operated with defects for a long time, and at the initial stage of the occurrence of the defects, the defects are usually ignored because the normal operation is not affected, but if any operation with the defects is carried out, the defects are more serious, and bad effects are generated. For example, the temperature and humidity of the field operation environment have different degrees of influence on the on-column switch and the controller, and the long-term abnormal temperature and humidity can cause the problems of mechanism corrosion, short circuit damage of components, insulation performance reduction and the like. If the on-site environment and the running state are monitored, the fault is treated before the fault occurs, and the power supply reliability is improved.
Based on this, in order to solve the above-mentioned problems and realize the state monitoring method of the on-column switch and the controller, the present embodiment further provides an on-column switch and the controller on-line monitoring system and a state monitoring system; as shown in fig. 2, the online monitoring system includes a video monitoring front-end device 1, and a communication device 2 connected to the video monitoring front-end device 1; optionally, the communication device 2 performs data transmission by adopting a 5G technology; the communication device 2 may include a communication unit and a communication controller, and the communication device 2 is connected to the camera 11 through the video server 13.
As shown in fig. 1, the video monitoring front-end device 1 includes a camera 11, and a power module 12 connected to the camera 11; optionally, the camera 11 is mounted between the pole switch and the power distribution terminal through a camera bracket 111; the camera 11 adopts 360 degrees panoramic camera, realizes the omnidirectional rotation, carries out no dead angle control to on-column switch and controller, can not have the blind spot to monitor. The camera 11 is used as a dynamic video/static photo sensor, and can monitor the running state and the running environment in a seamless way; the camera 11 may be a high-definition camera for acquiring an image of a switch housing on a column, an image of a controller housing, and the like.
Optionally, the power module 12 is connected to the voltage transformer 121 and the storage battery 122 through aviation plug, and the storage battery 122 is a lead-acid battery. The storage battery 122 is connected with the camera bracket 111 through the storage battery bracket 123, and optionally, the camera 11 and the storage battery 122 are both supported through a fixed bracket, and the fixed bracket is made of stainless steel; the space radius of the camera support 111 is 20 cm-30 cm. The battery support 123 and the camera support 111 are made of stainless steel, and the connecting screw and other parts are made of stainless steel, so that the service life of the support is prolonged.
In other embodiments, the voltage transformer 121 provides an ac power source for the camera 11, and when the ac power source fails, the dc power source battery 122 is immediately started as a backup power source, so as to ensure stable and reliable operation of the system. The secondary side terminal block of the voltage transformer 121 is connected with the storage battery 122 in parallel through the power module 12 to be connected with the camera 11.
As shown in fig. 2, the video monitoring front-end device 1 further includes a video server 13, the camera 11 is connected with the communication device 2 through the video server 13, and the video server 13 can compress, store and process the collected on-column switch video data. The processed data are converted into data packets based on TCP/IP protocol, the data packets are transmitted to a 5G network through an RJ45 interface, a remote terminal receives a digital video code stream transmitted by a front-end monitoring camera through a network video recorder (Network Video Recorder, NVR), storage management is carried out, a display is connected for playing, and on-line monitoring of a pole switch and a controller is completed.
Operation and maintenance personnel can also operate and control through the handheld terminal, and observe all video images and state monitoring results; the handheld terminal is a mobile phone or PDA (Personal Digital Assistant) provided with a data query system.
The operation and maintenance personnel can randomly switch video pictures, and can finish the state inspection work of the on-pole switch and the controller in a short time. And by combining the state monitoring result, judging whether the on-column switch and the controller normally operate, and carrying out hidden danger treatment work in a targeted manner. Meanwhile, the video of each monitoring point can be recorded, and if no reason can be found after the accident occurs, the video can be played back for auxiliary analysis.
As shown in fig. 5, the state monitoring system may optionally include a state acquisition device, a communication device, a state monitoring analysis system, and the like. The temperature sensor in the state acquisition device can acquire an operating environment temperature signal; the humidity sensor can collect an operation environment humidity signal; the high-definition camera can acquire an on-column switch shell image and a controller shell image, and the rust damage condition of the on-column switch shell and the damage condition of the controller shell can be obtained through the images; the vacuum degree signal of the vacuum tube of the vacuum circuit breaker and the pressure signal of the SF6 circuit breaker can be acquired through the high-definition camera, the pressure sensor and other related sensors; the infrared camera can collect contact temperature signals; the switching-on/off coil state monitoring device can collect switching-on/off coil state signals; the energy storage motor current state monitoring device can collect energy storage state signals; the controller can collect the switching-on/off time signal and the fault-free working time signal. The signals are transmitted to a state monitoring and analyzing system through the 5G technology of the communication equipment. The state monitoring and analyzing system firstly preprocesses the signal data, and then obtains the state monitoring results of the on-column switch and the controller through a fuzzy chromatography analysis method based on the genetic annealing algorithm improvement.
The on-off coil state monitoring device can comprise an on-pole switch on-off loop and a Hall sensor, wherein the power supply current of an operating mechanism of the on-off loop passes through the Hall sensor, and the state monitoring of the on-off coil is realized by collecting the current through the Hall sensor. The energy storage motor current state monitoring device can comprise a pole-mounted switch energy storage loop and a Hall sensor, wherein the power supply current of the energy storage loop passes through the Hall sensor, and the state monitoring of the energy storage motor current is realized by collecting current through the Hall sensor. The controller is a power distribution terminal, and can collect the switching-on and switching-off time and the fault-free working time of the switch on the column.
The embodiment adopts the camera to monitor the running state and the running environment of the on-column switch and the controller in a real-time monitoring mode of dynamic video/static pictures, reduces the labor intensity of operation and maintenance personnel and provides data basis for on-column switch maintenance. Based on the video playback function, when a fault occurs, auxiliary analysis is performed through the video, so that the accident reason is ascertained. And the on-pole switch on-off state is checked in time through video monitoring, whether the power distribution automation master station system is matched with the on-site situation is checked, and hidden danger is eliminated in time. The temperature and humidity of the operation environment, the on-off coil state of the pole switch, the energy storage state of the pole switch, the contact temperature of the pole switch, the rust damage condition of the pole switch shell, the damage condition of the controller shell, the on-off time, the fault-free working time,And the state information such as the vacuum degree of the vacuum tube of the vacuum circuit breaker, and the like is processed by the state monitoring analysis system to realize the monitoring of the running states of the on-pole switch and the controller.
The method in this embodiment comprises the following specific steps:
s1, constructing a hierarchical structure model of a switch and a controller on a column, wherein the model is divided into a target layer, a factor layer and an index layer. The system comprises a column switch, a controller, a factor layer, an operation and maintenance inspection type state quantity, a state acquisition device, a control device and a control device, wherein the target layer is the operation state of the column switch and the controller, the factor layer is divided into an on-line monitoring type state quantity, a mechanical test type state quantity and an operation and maintenance inspection type state quantity, and the index layer is various indexes acquired by the state acquisition device. The column switch and controller hierarchy is shown in table 1:
table 1 column switch and controller hierarchy
In this embodiment, optionally, the set of state evaluation comments is selected asV= { normal, note, abnormal, urgent } four states.
S2, the data preprocessing process needs to normalize the data. The quantitative index can be classified into a descending index and an ascending index, since a specific value can be directly obtained. For the descending index, the larger and the better, the most recent on-column switch and controller are, and the calculation method is shown as the formula (1):
（1）
for the ascending type index, the smaller the better, the smallest the on-column switch and the controller are, and the calculation method is shown as the formula (2):
（2）
wherein,xis the normalized index;as a measure of the index,iis a factor sequence number; />Is the index optimal value;is a warning value.
For qualitative indexes such as on-column switches and appearance damage conditions of controllers, which cannot be directly represented by numerical values, most of the indexes have subjectivity, in order to avoid the influence on evaluation results, normalization treatment is required for the qualitative indexes, a [0,1] interval scoring method is adopted for the indexes, and the scoring rules are shown in table 2:
table 2 qualitative index scoring rules
For determining each index of index layer in evaluation setVThe degree of four states in = { normal, note, abnormal, urgent }, membership function is used. Taking subjectivity and diversity of indexes into consideration, calculating by adopting a half trapezoid half-ridge function and a half trapezoid half-triangle membership function.
The semi-trapezoid and semi-ridge membership function is characterized by being excessively gentle, has a wider principal value interval, is applied to quantitative index calculation with more objectivity, and has the following function expression:
（3）
（4）
（5）
（6）
the semi-trapezoid and semi-triangle membership function is characterized in that a main value interval is short, a calculation result is not greatly different, and the function is applied to qualitative index calculation with subjectivity, wherein the function expression is as follows:
（7）
（8）
（9）
（10）
the 4 membership results of each index form a fuzzy evaluation matrix of the index
The index layer membership matrix of the same type of factors is combined to obtain a factor layer fuzzy evaluation matrixRThe factor layer comprises on-line monitoring type state quantity +.>Mechanical test type state quantity->State quantity of operation and maintenance inspection class>Three factor layer fuzzy evaluation matrixes can be obtained：
（11）
Wherein,iis a factor sequence number; the value is [1,2,3 ]]；jIs the number of indicators in each type of factor layer.
The state evaluation needs to consider the influence degree of each layer element of the layering model on the target layer, so that a fuzzy judgment matrix is constructedPAnd comparing the importance degrees of the elements. The fuzzy judgment matrix has complete oneThe elegance is required to satisfy the formula (12):
（12）
wherein,i，j=1，2，...，n，nis the number of elements;the weight value of the element;qthe smaller the measurement unit of the importance degree difference between the elements, the more importance degree difference is emphasized by the decision maker, and the value range is +.> n-1)/2Is generally taken outq =(n-1)/2。
S3, fuzzy judgment matrix considering element diversity and subjectivityPIt is difficult to satisfy the complete consistency condition, so the weight solving problem is converted into a mathematical programming problem:
（13）
solving the problem of formulation (13) by introducing a genetic annealing algorithm.
The genetic algorithm (Genetic Algorithm, GA) has excellent optimizing capability and high convergence rate; the simulated annealing algorithm (Simulated Annealing, SA) is characterized by being capable of jumping out of a local optimal solution and having better capability of searching a global optimal solution. The ability of the SA to jump out of the locally optimal solution is achieved by two parts: metropolis algorithm and annealing process. The implementation of the annealing process is to first determine the initial temperatureAnd termination temperature->Selecting proper cooling coefficient->Each time the temperature is reduced according to the temperature reduction coefficient,let the current temperature equal +.>Multiple of previous temperature, i.e. firstnThe temperature at the time of iteration isUntil the current temperature is less than the end temperature +.>The iteration is then stopped. The Metropolis algorithm is how to jump out when the solution is locally optimal, and is the core of the simulated annealing algorithm. Let the system energy be +.>The energy of the system is +.>. When->When the system energy is proved to be reduced and is closer to the current optimal solution, the new feasible solution is better than the original feasible solution, and the new feasible solution is selected hundred percent. But when->When the new feasible solution deviates from the current optimal solution, however, the current optimal solution is not necessarily the global optimal solution, and may be only the local optimal solution, so that the new feasible solution is received with a certain probability at the moment, and the method is favorable for jumping out of the local optimal solution and searching the global optimal solution. The probability that a new feasible solution is accepted is:
（14）
in this embodiment, the genetic annealing algorithm (GA-SA) is formed by combining the advantages of the two algorithms, so that the evolution mode of selecting cross variation in the genetic algorithm is reserved, and the local optimal solution is jumped out by adopting the Metropolis acceptance criterion of the simulated annealing algorithm, so that the algorithm can be quickly converged to the global optimal solution.
As shown in fig. 6, the flow of the genetic annealing algorithm is as follows:
s3.1, determining the chromosome form according to the actual engineering problem code.
S3.2, initializing an initial temperature, a final temperature and a cooling coefficient.
S3.3, initializing population. Determining population size and genetic algebra, and randomly generating individuals with given population size.
And S3.4, calculating the fitness of each individual according to the fitness function.
S3.5, selecting a parent for genetic operation through a selection function and individual fitness.
S3.6, carrying out cross operation on the genes of the parent individuals according to a certain mode, then carrying out gene mutation operation according to the mutation rate, finally generating new individuals, and calculating the adaptability of the new individuals.
And S3.7, comparing fitness of the father and the filial generation, and judging whether the filial generation is accepted as an individual of the new population according to a Metropolis acceptance criterion.
S3.8, cycling from step S3.4 to step S3.7 until the genetic algebra is reached.
S3.9, performing cooling operation.
S3.10, cycling from step S3.3 to step S3.9 until the end temperature is reached.
The fuzzy evaluation matrix of the three factor layers is obtained through the stepsAnd the weight of each index->. Multiplying the membership degree by the weight to obtain an index layer comprehensive evaluation matrix>Comprising the element->The calculation method is as follows:
（15）
wherein,i=1，2，3；jis the number of indicators in each type of factor layer.
Obtaining three index layer comprehensive evaluation matrixesThen, the comprehensive fuzzy evaluation matrix of the on-column switch and the controller state can be calculated by utilizing the factor layer weightB：
（16）
Wherein,the state with the highest duty ratio is the current running state of the pole switch and the controller according to the principle of the maximum membership.
A flow chart of the improved fuzzy chromatography based on the genetic annealing algorithm is shown in fig. 7.
Example 2:
the embodiment provides a state monitoring system of a pole-mounted switch and a controller, comprising:
a data acquisition module configured to: acquiring relevant monitoring information of a switch and a controller on a column;
a layering module configured to: constructing a hierarchical structure model of the on-column switch and the controller, wherein the hierarchical structure model comprises a target layer, a factor layer and an index layer, according to the relevant monitoring information;
a matrix construction module configured to: constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller;
the index weight solving module is configured to: solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight;
the comprehensive evaluation matrix construction module is configured to: multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix;
a state evaluation module configured to: and calculating according to the index layer comprehensive evaluation matrix by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix representing the states of the on-column switch and the controller.
The working method of the system is the same as the state monitoring method of the on-column switch and the controller in embodiment 1, and will not be described here again.
Example 3:
the present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the on-column switch and controller status monitoring method described in embodiment 1.
Example 4:
the present embodiment provides an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for monitoring the status of the on-column switch and the controller described in embodiment 1 when executing the program.
The above description is only a preferred embodiment of the present embodiment, and is not intended to limit the present embodiment, and various modifications and variations can be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.
Claims (10)
1. A method for monitoring the state of a pole-mounted switch and a controller, comprising:
acquiring relevant monitoring information of a switch and a controller on a column;
constructing a hierarchical structure model of the on-column switch and the controller, wherein the hierarchical structure model comprises a target layer, a factor layer and an index layer, according to the relevant monitoring information;
constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller;
solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight;
multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix;
and calculating according to the index layer comprehensive evaluation matrix by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix representing the states of the on-column switch and the controller.
2. The method of claim 1, wherein the relevant monitoring information includes one or more of an ambient temperature signal, an ambient humidity signal, an on-column switch housing image, a controller housing image, a vacuum circuit breaker vacuum level signal, an SF6 circuit breaker pressure signal, a contact temperature signal, an on-off coil status signal, an energy storage status signal, a closing time signal, and a fault-free operating time signal.
3. The method for monitoring the state of a pole switch and controller as claimed in claim 1, wherein the target layer is the pole switch and controller operating state; the factor layer is divided into an on-line monitoring state quantity, a mechanical test state quantity and an operation and maintenance inspection state quantity; the index layer is used for each index in the related monitoring information.
4. The method for monitoring the state of a pole switch and a controller according to claim 1, wherein the quantitative index in the related monitoring information is normalized according to a specific value; and carrying out normalization processing on the qualitative indexes in the related monitoring information according to a section scoring method.
5. The method for monitoring the state of a switch and a controller on a column according to claim 1, wherein the genetic annealing algorithm solves for each index weight as:
wherein,i，j=1，2，...，n，nis the number of elements;is the difference of importance degree among elements, wherein +.>The weight value of the element; />Matrix elements are judged for the paste.
6. The method for monitoring the state of a pole-mounted switch and controller as claimed in claim 1, wherein the genetic annealing algorithm comprises: determining the form of the chromosome according to the actual problem codes; initializing an initial temperature, a termination temperature and a cooling coefficient; initializing a population, determining the population scale and genetic algebra, and randomly generating individuals with a given population scale; calculating the fitness of each individual according to the fitness function; selecting a parent for genetic manipulation by selecting a function and individual fitness; performing cross operation on the genes of the parent individuals according to a certain mode, then performing gene mutation operation according to the mutation rate, finally generating new individuals, and calculating the adaptability of the new individuals; comparing the fitness of the parent and the offspring, and judging whether to accept the offspring as the individuals of the new population according to the Metropolis acceptance criterion; circularly calculating the fitness of each individual until judging whether to accept the offspring as the individual content of the new population until the genetic algebra is reached; cooling operation is carried out; and initializing the population to the cooling operation content in a circulating way until reaching the end temperature.
7. The method of claim 1, wherein the on-column switch and controller status includes normal, attention, abnormal and emergency.
8. A condition monitoring system for a pole-mounted switch and controller, comprising:
a data acquisition module configured to: acquiring relevant monitoring information of a switch and a controller on a column;
a layering module configured to: constructing a hierarchical structure model of the on-column switch and the controller, wherein the hierarchical structure model comprises a target layer, a factor layer and an index layer, according to the relevant monitoring information;
a matrix construction module configured to: constructing a factor layer fuzzy evaluation matrix and a fuzzy judgment matrix for comparing the importance degrees of all elements according to the hierarchical structure model of the on-column switch and the controller;
the index weight solving module is configured to: solving the fuzzy judgment matrix by using a genetic annealing algorithm to obtain each index weight;
the comprehensive evaluation matrix construction module is configured to: multiplying membership in the factor layer fuzzy evaluation matrix with index weight to obtain an index layer comprehensive evaluation matrix;
a state evaluation module configured to: and calculating according to the index layer comprehensive evaluation matrix by utilizing the factor layer weight to obtain a comprehensive fuzzy evaluation matrix representing the states of the on-column switch and the controller.
9. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method for status monitoring of on-column switches and controllers as claimed in any of claims 1-7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for on-column switch and controller status monitoring as claimed in any one of claims 1-7 when the program is executed by the processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311628822.XA CN117335577A (en) | 2023-12-01 | 2023-12-01 | Method and system for monitoring state of pole-mounted switch and controller |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311628822.XA CN117335577A (en) | 2023-12-01 | 2023-12-01 | Method and system for monitoring state of pole-mounted switch and controller |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117335577A true CN117335577A (en) | 2024-01-02 |
Family
ID=89279674
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311628822.XA Pending CN117335577A (en) | 2023-12-01 | 2023-12-01 | Method and system for monitoring state of pole-mounted switch and controller |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117335577A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109613380A (en) * | 2019-02-19 | 2019-04-12 | 广东电网有限责任公司 | On-pole switch complete set of equipments method for evaluating state, device, system and server |
| CN109902336A (en) * | 2019-01-15 | 2019-06-18 | 国网浙江省电力有限公司 | Cable insulation lifetime estimation method based on Fuzzy AHP |
| CN110009208A (en) * | 2019-03-26 | 2019-07-12 | 武汉理工大学 | A kind of on-pole switch complete set of equipments health state evaluation method and device based on integrated intelligent algorithm |
| CN110991876A (en) * | 2019-11-30 | 2020-04-10 | 华南理工大学 | Primary and secondary fusion on-column switch inspection strategy based on state assessment |
| CN114297948A (en) * | 2022-03-07 | 2022-04-08 | 广东电网有限责任公司佛山供电局 | On-pole circuit breaker state evaluation method and system |
| CN115689322A (en) * | 2022-07-22 | 2023-02-03 | 国网天津市电力公司 | Power multi-service 5G application scheme evaluation method based on fuzzy analytic hierarchy process |
| CN116644984A (en) * | 2023-04-23 | 2023-08-25 | 广东电网有限责任公司 | Reliability evaluation method, device, equipment and storage medium for electric power optical communication network |
| CN116702084A (en) * | 2023-02-16 | 2023-09-05 | 中国电力科学研究院有限公司 | Secondary fusion on-column breaker state evaluation method based on fuzzy theory |
-
2023
- 2023-12-01 CN CN202311628822.XA patent/CN117335577A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109902336A (en) * | 2019-01-15 | 2019-06-18 | 国网浙江省电力有限公司 | Cable insulation lifetime estimation method based on Fuzzy AHP |
| CN109613380A (en) * | 2019-02-19 | 2019-04-12 | 广东电网有限责任公司 | On-pole switch complete set of equipments method for evaluating state, device, system and server |
| CN110009208A (en) * | 2019-03-26 | 2019-07-12 | 武汉理工大学 | A kind of on-pole switch complete set of equipments health state evaluation method and device based on integrated intelligent algorithm |
| CN110991876A (en) * | 2019-11-30 | 2020-04-10 | 华南理工大学 | Primary and secondary fusion on-column switch inspection strategy based on state assessment |
| CN114297948A (en) * | 2022-03-07 | 2022-04-08 | 广东电网有限责任公司佛山供电局 | On-pole circuit breaker state evaluation method and system |
| CN115689322A (en) * | 2022-07-22 | 2023-02-03 | 国网天津市电力公司 | Power multi-service 5G application scheme evaluation method based on fuzzy analytic hierarchy process |
| CN116702084A (en) * | 2023-02-16 | 2023-09-05 | 中国电力科学研究院有限公司 | Secondary fusion on-column breaker state evaluation method based on fuzzy theory |
| CN116644984A (en) * | 2023-04-23 | 2023-08-25 | 广东电网有限责任公司 | Reliability evaluation method, device, equipment and storage medium for electric power optical communication network |
Non-Patent Citations (5)
| Title |
|---|
| 吴鹏等: "一二次融合柱上开关状态监测与运维技术研究", 电子器件, vol. 46, no. 01, 28 February 2023 (2023-02-28), pages 179 - 184 * |
| 林伟: "遗传算法和模糊评价方法在教师绩效考核中的应用研究", 中国优秀硕士学位论文全文数据库 社会科 学Ⅱ辑, no. 6, 15 June 2017 (2017-06-15), pages 15 * |
| 王东芳等: "一二次融合柱上开关组合加权模糊状态评价", 浙江电力, vol. 39, no. 2, 29 February 2020 (2020-02-29), pages 48 - 54 * |
| 王军霞等;: "基于改进模糊层次分析法的SF_6断路器状态评估", 四川电力技术, vol. 6, no. 03, 20 June 2013 (2013-06-20), pages 5 - 10 * |
| 黄智鹏等: "基于改进层次分析法的柱上开关成套设备状态评估研究", 广东电力, vol. 33, no. 3, 31 March 2020 (2020-03-31), pages 88 - 95 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113763667B (en) | Fire disaster early warning and state monitoring device and method based on 5G edge calculation | |
| CN117078017A (en) | Intelligent decision analysis system for monitoring power grid equipment | |
| CN113806420A (en) | Power grid data monitoring method and device | |
| CN112531908A (en) | Internet of things household power supply control system and method | |
| CN115453267A (en) | Fault diagnosis system for electric power information system | |
| CN114743089A (en) | Image recognition GIS fault diagnosis device and method based on SSA-SVM | |
| CN108594076B (en) | Power failure fault study and judgment method for power distribution network | |
| CN117335577A (en) | Method and system for monitoring state of pole-mounted switch and controller | |
| CN112202241A (en) | Distribution network equipment state monitoring and fault judgment system | |
| CN116667783A (en) | Distributed photovoltaic power station maintenance system | |
| CN116522746A (en) | Power distribution hosting method for high-energy-consumption enterprises | |
| CN114069865A (en) | Converter station operation monitoring system, method and device, computer equipment and medium | |
| CN114997375A (en) | Insulator surface metal pollution model building system in air type switch cabinet | |
| CN113572837A (en) | Power grid monitoring system data processing service scheduling method based on fragmentation technology | |
| CN113570473A (en) | Equipment fault monitoring method and device, computer equipment and storage medium | |
| CN112557745A (en) | Power superposition comparison system and method for line loss monitoring | |
| CN1665088A (en) | Digital diagrammatic view switch apparatus system | |
| LU500843B1 (en) | A monitoring system and prediction method of temperature for generator carbon brush based on an infrared image | |
| Liu et al. | Health status evaluation method of smart distribution station based on operation trajectory information matrix | |
| Han et al. | Application of artificial intelligence technology in power grid enterprises based on enterprise architecture method | |
| CN115942155B (en) | Equipment monitoring method, device and system | |
| CN117706258B (en) | Fault detection system based on big data processing | |
| CN116882766B (en) | Power consumption abnormal distribution risk analysis method and system | |
| CN116008685B (en) | Automatic overhaul method and system for power equipment | |
| CN115242664A (en) | Intelligent machine room management method based on big data analysis model |
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 |