Transformer Fault Diagnosis Method Based on Improved Cuckoo Search Optimization Neural Network

A technology of cuckoo search and transformer fault, applied in the field of transformer fault diagnosis based on improved cuckoo search optimization neural network, can solve the problems of low diagnosis accuracy, poor quality, slow convergence speed, etc., to alleviate the instability of fitting, fast Convergence speed, the effect of overcoming incomplete coding

Active Publication Date: 2022-04-22
HONGHE COLLEGE
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Problems solved by technology

[0005] The purpose of the present invention is to provide a transformer fault diagnosis method based on the improved cuckoo search optimization neural network, which solves the problems of over-fitting and slow convergence speed of the existing BP neural network, poor solution quality and low diagnostic accuracy in the CS algorithm

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  • Transformer Fault Diagnosis Method Based on Improved Cuckoo Search Optimization Neural Network
  • Transformer Fault Diagnosis Method Based on Improved Cuckoo Search Optimization Neural Network
  • Transformer Fault Diagnosis Method Based on Improved Cuckoo Search Optimization Neural Network

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[0049] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0050] The present invention is based on the transformer fault diagnosis method of improved cuckoo search optimization neural network, such as figure 1 As shown, the specific steps are as follows:

[0051]Step 1. Collect the concentration of DGA characteristic gas that can reflect the type of transformer fault, and use the mapminmax function to normalize the concentration of DGA characteristic gas, and use it as an input sample for fault diagnosis; encode the fault type of transformer as an output sample;

[0052] Input samples include training samples and test samples;

[0053] The collected DGA characteristic gas is H 2 、CH 4 、C 2 h 6 、C 2 h 4 and C 2 h 2 , the diagnosed fault types are no fault, medium and low temperature overheating (150°C ~ 700°C), high temperature overheating (>700°C), low energy discharge and high energy disc...

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Abstract

The transformer fault diagnosis method based on the improved cuckoo search optimization neural network disclosed by the present invention first collects the concentration of DGA characteristic gas, and after normalization processing; determines the hidden layer neuron number, training function and The transfer function from the input layer to the output layer is used to establish a fault diagnosis model based on BP neural network; the improved cuckoo search algorithm is used to optimize the parameters of BP neural network to obtain the best weight threshold parameters, and the optimized BP neural network model is obtained. Utilize the training sample to train the optimized BP neural network model, and obtain the improved cuckoo search neural network diagnostic model; adopt the improved cuckoo search neural network diagnostic model to predict the test sample, and its output is the diagnosis result of the transformer failure; the present invention It solves the problems of over-fitting and slow convergence speed of the existing BP neural network, poor solution quality and low diagnostic accuracy in the CS algorithm.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis methods for oil-immersed transformers, in particular to a transformer fault diagnosis method based on an improved cuckoo search optimization neural network. Background technique [0002] The transformer is the core equipment in the power system. According to statistics, the annual failure rate of oil-immersed transformers is 0.00625. Therefore, effective diagnosis of latent faults in transformers is of great significance to the safe and stable operation of power systems; in addition, overheating and discharge faults of oil-immersed transformers are always related to oil Dissolved gas analysis (DGA) technology developed based on this has become an important means of diagnosing transformer faults. [0003] However, in engineering practice, the three-ratio method based on DGA technology has some defects, such as incomplete coding and too absolute coding boundaries. It is an effective way to...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/00G06N3/04
CPCG06N3/006G06N3/044G06F18/24G06F18/214
Inventor 程加堂梅俊熊燕
Owner HONGHE COLLEGE
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