Insulator fault diagnosis apparatus and method based on fuzzy cerebellar model neural network

A fault diagnosis device and neural network technology, applied to measuring devices, instruments, measuring electronics, etc., can solve problems such as limited recognition ability, and achieve high accuracy, accurate data, and fast speed

Pending Publication Date: 2018-06-19
FUZHOU UNIV
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Problems solved by technology

There have been studies on the fault diagnosis of insulators, but many studies only identify a specific fault. Although the

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  • Insulator fault diagnosis apparatus and method based on fuzzy cerebellar model neural network
  • Insulator fault diagnosis apparatus and method based on fuzzy cerebellar model neural network
  • Insulator fault diagnosis apparatus and method based on fuzzy cerebellar model neural network

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Embodiment Construction

[0018] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0019] see figure 1 , the present invention provides a kind of insulator fault diagnosis device based on fuzzy cerebellar model neural network, it is characterized in that: comprise MCU, the first preprocessing circuit, the second preprocessing circuit, the third preprocessing circuit, electric field sensor, leakage current sensor, A temperature sensor, a remote transceiver module and a remote computer; the MCU is respectively connected to the first preprocessing circuit, the second preprocessing circuit, the third preprocessing circuit, and the remote transceiver module; the first preprocessing circuit is connected to the electric field sensor; The second preprocessing circuit is connected with a leakage current sensor; the third preprocessing circuit is connected with a temperature sensor; and the remote transceiver module is connected with a...

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Abstract

The invention provides an insulator fault diagnosis apparatus and method based on a fuzzy cerebellar model neural network. The insulator fault diagnosis apparatus is composed of an MCU, a first pre-processing circuit, a second pre-processing circuit, a third pre-processing circuit, an electric field sensor, a leakage current sensor, and a temperature sensor, a remote transceiver module and a remote computer. The electric field sensor, the leakage current sensor and the temperature sensor collect signals; denoising processing is carried out based on a Kalman filter algorithm to obtain a featuresample with fault information; an insulator fault information training sample library is established; classification training is carried out on samples based on FCMAC; training is carried out by using a BP algorithm to obtain a weight value and a threshold value that enable network optimization to be realized; and when a new information sample is inputted into the network, a fault type of an insulator is determined rapidly and accurately. On the basis of combination of the Kalman algorithm and the CMAC, a few of weight values need to be corrected each time, the learning is accelerated, and the certain generalization ability is enhanced. Besides, the efficiency and accuracy of the insulator fault analysis are improved.

Description

technical field [0001] The invention belongs to the field of insulator detection, and in particular relates to an insulator fault diagnosis device and method based on a fuzzy cerebellum model neural network. Background technique [0002] Traditional insulator detection methods include infrared temperature measurement, ultraviolet imaging, ultrasonic detection, and leakage current method, but these detection methods have disadvantages such as high cost, low safety, or poor applicability. With the continuous development of computer technology and sensor technology, machine learning has been successfully applied to fault detection in many industries. There have been studies on the fault diagnosis of insulators, but many studies only identify a specific fault. Although the identification results are highly accurate, the identification ability is limited and there are still certain defects. Contents of the invention [0003] The purpose of the present invention is to provide a...

Claims

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Application Information

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IPC IPC(8): G01R31/12
CPCG01R31/1245
Inventor 林琼斌陈诗灿万志松王武蔡逢煌柴琴琴
Owner FUZHOU UNIV
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