High-voltage circuit breaker mechanical fault diagnosis method

A technology for high-voltage circuit breakers and mechanical faults, which is used in instruments, computer parts, character and pattern recognition, etc. It can solve the problems of insufficient fault sample data, complex feature extraction methods, and insufficient characterization of feature quantities, so as to improve feature expression. Ability and separable performance, improving generalization ability, and the effect of good classification performance

Inactive Publication Date: 2019-08-02
SOUTHEAST UNIV
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  • Abstract
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Problems solved by technology

[0005] Purpose of the invention: In view of the above problems, the present invention proposes a method for diagnosing mechanical faults of high-voltage circuit breakers, which solves the problems of complex feature extraction...

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  • High-voltage circuit breaker mechanical fault diagnosis method
  • High-voltage circuit breaker mechanical fault diagnosis method
  • High-voltage circuit breaker mechanical fault diagnosis method

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Embodiment Construction

[0040] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0041] Such as figure 1 As shown, the fault diagnosis model based on DBN network and transfer learning mechanism is mainly divided into two parts: DBN feature extraction part and fault classification part. The DBN feature extraction part uses the original target and auxiliary feature sample data to realize the unsupervised training of the DBN network, and adaptively extracts effective features from high-dimensional original data. The fault classification part realizes the integration of feature extraction and fault diagnosis by constructing a BPNN network classifier that adds a label output layer on the basis of the DBN network structure, and uses the pre-trained DBN network parameters to initialize the DNN network, and uses the labeled The training samples and the corresponding sample weights are combined with the BP algorit...

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Abstract

The invention discloses a high-voltage circuit breaker mechanical fault diagnosis method. Opening and closing coil current obtained by a high-voltage circuit breaker fault simulation experiment is used as a target data sample for fault diagnosis; data obtained through simulation by establishing an opening and closing coil mathematical model serve as an auxiliary data sample, deep mining and self-adaptive extraction of sample data features are achieved through a deep belief network (DBN), and information matching of the auxiliary data and target data is achieved in combination with a transfer learning method. According to the method, transfer learning and a deep belief network are combined; the deep belief network is utilized to carry out deep mining and self-adaptive extraction on the current time domain signal of the opening and closing coil of the circuit breaker, the transfer learning method is combined to solve the problem that the actual fault training sample data size is small, and the generalization capability of the fault diagnosis model is improved.

Description

technical field [0001] The invention belongs to the technical field of electric engineering, and in particular relates to a method for diagnosing a mechanical fault of a high-voltage circuit breaker. Background technique [0002] Smart grids are inseparable from high-voltage circuit breakers with high reliability, and their operating status will directly affect the stability of the entire power system and the reliability of power supply. As an important content and development direction of high-voltage circuit breaker intelligence, fault diagnosis technology can provide more reliable diagnostic information for condition-based maintenance, prevent equipment failures, and improve maintenance efficiency. [0003] At present, the fault diagnosis of high-voltage circuit breakers mainly includes two parts. First, feature extraction is performed on the signal data of the high-voltage circuit breaker opening and closing coil current, mechanical vibration, and contact displacement, a...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/12G06F18/2321G06F18/241G06F18/214
Inventor 郑建勇潘益周程朱睿石天尹德扬
Owner SOUTHEAST UNIV
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