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Lightning arrester monitoring method based on leakage current sensor and BP neural network algorithm

A BP neural network, leakage current technology, applied in neural learning method, biological neural network model, neural architecture, etc., can solve the problems of valve aging of arrester, increase the load of arrester, low operating voltage, etc., to reduce the number of times , good anti-interference, improve the effect of reliability

Pending Publication Date: 2022-06-24
MAANSHAN POWER SUPPLY COMPANY STATE GRID ANHUI ELECTRIC POWER +1
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Problems solved by technology

Another important reason for the accelerated aging of the arrester valve is that the operating voltage loaded on both ends of the arrester is lower than normal. rapid aging

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  • Lightning arrester monitoring method based on leakage current sensor and BP neural network algorithm
  • Lightning arrester monitoring method based on leakage current sensor and BP neural network algorithm
  • Lightning arrester monitoring method based on leakage current sensor and BP neural network algorithm

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Embodiment Construction

[0087] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0088] like Figure 1-8 As shown, a lightning arrester monitoring method based on a leakage current sensor and a BP neural network algorithm in this embodiment includes the following steps:

[0089] Step 1: Propose a method of resistive sensor to obtain the leakage current of MOA;

[0090] Step 2: propose a leakage current harmonic analysis method based on compensation technology;

[0091] Step 3: Use the BP neural network to train...

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Abstract

The invention discloses a lightning arrester monitoring method based on a leakage current sensor and a BP neural network algorithm, and relates to the technical field of oxide lightning arrester detection. According to the method, a new leakage current sensor is used for collecting the leakage current of the MOA, a new method for measuring the leakage current of the MOA based on harmonic analysis is provided, and some key parameters capable of reflecting the aging condition of the MOA are trained through a BP neural network. Experiments show that the leakage current fitting obtained according to the simulation result approaches the leakage current actually needing to be measured, the anti-interference performance is good, and aging monitoring can be effectively carried out on the MOA. On-line monitoring of the operation state of the lightning arrester is achieved, the number of times of power-off maintenance of the MOA is reduced, and the operation reliability of a power system is greatly improved.

Description

technical field [0001] The invention relates to the technical field of oxide arrester detection, in particular to a lightning arrester monitoring method based on a leakage current sensor and a BP neural network algorithm. Background technique [0002] With the rapid development of my country's economy, the demand for electricity increases exponentially, and the normal and stable operation of substation equipment is the premise and guarantee for users to use reliable electricity. As an indispensable part of the safe operation of substations, the metal oxide arrester (MOA) can not only limit the transient high voltage that the electrical equipment is subjected to, but also limit the freewheeling time and the intrusion current value to prevent the electrical equipment from suffering from overvoltage. impact. [0003] Studies have shown that the main reason for the failure of the arrester is that the internal valve plate of the arrester is seriously damped or the valve plate of...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/00G01R31/52G06N3/04G06N3/08
CPCG01R31/00G01R31/52G06N3/04G06N3/084
Inventor 张忠何涛张宇金亚曦杨冬华云梅吴曦翱朱元杰
Owner MAANSHAN POWER SUPPLY COMPANY STATE GRID ANHUI ELECTRIC POWER