Metering cabinet state detection method, device, equipment and medium

A state detection and metering cabinet technology, applied in design optimization/simulation, special data processing applications, etc., can solve the problem that the state of the metering cabinet cannot be accurately judged for latent faults, and achieve the effect of improving trustworthiness

Active Publication Date: 2021-06-18
国网四川省电力公司营销服务中心
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is that the existing method for detecting the state of the metering cabinet cannot accurately judge latent faults and is easy to use in engineering Application, therefore, the present invention provides a metering cabinet state detection method, device, equipment and medium to improve the accuracy of metering cabinet fault detection and the implementation process is simple and convenient for engineering application

Method used

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  • Metering cabinet state detection method, device, equipment and medium
  • Metering cabinet state detection method, device, equipment and medium
  • Metering cabinet state detection method, device, equipment and medium

Examples

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Effect test

Embodiment 1

[0050] Such as figure 1 As shown, the present invention provides a method for detecting the state of a metering cabinet, which specifically includes the following steps:

[0051] S10: Obtain feature information of the metering cabinet to be detected, and divide the feature information into different fuzzy factor sets based on feature identification.

[0052] Wherein, the metering cabinet to be tested refers to the metering cabinet that needs to be tested.

[0053] S20: Obtain the fuzzy factor set weight matrix and comprehensive score value of each fuzzy factor set.

[0054] S30: Calculate the fuzzy factor set weight matrix and comprehensive score value of each fuzzy factor set through the fuzzy normal distribution membership function, and obtain the state score of each fuzzy factor set.

[0055] S40: Calculate the state score of each fuzzy factor set through the minimum fuzzy operator, and select the feature identifier corresponding to the minimum score value as the target i...

Embodiment 2

[0089] Such as Figure 5 As shown, the difference between this embodiment and Embodiment 1 is that a metering cabinet state detection device is provided, including:

[0090] The fuzzy factor set creation module 10 is used to obtain the characteristic information of the metering cabinet to be detected, and divides the characteristic information into different fuzzy factor sets based on the characteristic identification;

[0091] The fuzzy factor set calculation module 20 is used to obtain the fuzzy factor set weight matrix and comprehensive score value of each fuzzy factor set;

[0092] The state score calculation module 30 is used to calculate the fuzzy factor set weight matrix and the comprehensive score value of each fuzzy factor set through the fuzzy normal distribution membership function to obtain the state score of each fuzzy factor set;

[0093] The target identification determination module 40 is used to calculate the state score of each fuzzy factor set by the minimu...

Embodiment 3

[0097] This embodiment provides a computer device, which may be a server, and its internal structure diagram may be as follows Figure 6 shown. The computer device includes a processor, memory, network interface and database connected by a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a computer-readable storage medium and an internal memory. The computer readable storage medium stores an operating system, computer programs and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the computer-readable storage medium. The database of the computer equipment is used to store the data involved in a measuring cabinet state detection method. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by ...

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Abstract

The invention discloses a measuring cabinet state detection method, device, equipment and medium, and the method comprises the steps: dividing feature information into different fuzzy factor sets, and obtaining a fuzzy factor set weight matrix and a comprehensive score value of each fuzzy factor set; calculating the fuzzy factor set weight matrix and the comprehensive score value of each fuzzy factor set through a fuzzy normal distribution membership function to obtain a state score of each fuzzy factor set; selecting a feature identifier corresponding to the minimum score value as a target identifier through a minimum fuzzy operator; inputting the minimum score value into a normal distribution membership function model for calculation to obtain a membership value corresponding to each feature identifier, and determining the state level corresponding to the maximum membership value as the state level of the to-be-detected metering cabinet; and determining the detection result based on the state level and the target identifier, so that more information with relatively low membership and evaluation value is shielded, and the credibility of the evaluation result is improved.

Description

technical field [0001] The invention relates to the field of power distribution technology, in particular to a method, device, equipment and medium for detecting the state of a metering cabinet. Background technique [0002] The metering cabinet is one of the main equipment of the power distribution system, which mainly plays the role of controlling and protecting other power equipment. In practical application, the metering cabinet is the equipment with the highest failure rate in the distribution network, and the detection of the state of the metering cabinet is the main link to ensure the stable operation of the distribution system. At present, threshold value discrimination method and intelligent algorithm (neural network, support vector machine, K nearest neighbor, etc.) are mostly used to detect the status of metering cabinets. The effect is not good; the intelligent algorithm is easy to fall into the local optimal solution, the hyperparameter adjustment is difficult,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20
CPCG06F30/20
Inventor 黄嘉鹏覃剑刘鹍张杰夫刘刚李福超罗睿希叶子阳曾兰
Owner 国网四川省电力公司营销服务中心
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