Transformer noise prediction method based on wavelet neural network and wavelet technology

Abstract

The invention discloses a transformer noise prediction method based on a wavelet neural network and the wavelet technology. A neuronal hyperbolic tangent S-type excitation function of a hidden layer in the traditional BP (back propagation) neural network is replaced with a wavelet-based function, momentum factors are introduced when parameters of the neural system are adjusted, and accordingly, a prediction model is higher in convergence speed and higher in error precision. Vibration and noise digital signals are decomposed by means of the wavelet decomposition technology, wavelet low-frequency coefficients obtained are used as input-output pairs for the prediction model, the wavelet low-frequency coefficients obtained by prediction are reconstructed by means of the wavelet reconstruction technology after modeling, and predicted noise digital signals are obtained. The transformer noise prediction method based on the wavelet neural network and the wavelet technology has the advantages that fewer training samples are required, time of training neurons in the neural network is shortened, and the problem that poor prediction effect is caused by ambient high-frequency interference noise contained in actually-measured transformer noise data is further avoided.

Description

technical field [0001] The invention relates to a transformer noise prediction method, in particular to a transformer noise prediction method based on wavelet neural network and wavelet technology, which belongs to the technical field of electric power environment protection. Background technique [0002] As large transformers enter residential areas, the low-frequency noise pollution they generate has seriously affected the physical and mental health of residents. Traditional transformer passive noise technology is only effective for medium and high frequency noise, and the control effect for low frequency noise is not ideal. In order to effectively control the low-frequency noise of transformers, many scholars at home and abroad have applied active noise control technology to the problem of transformer noise suppression. Although these studies can achieve a certain noise reduction effect, the effect is not ideal. One of the main reasons is that when using active noise con...

AI Technical Summary

Problems solved by technology

Although the above prediction methods can accurately predict the noise sound pressure level in a certain area of ​​the substation, these methods are not suitable for transformer noise prediction, and the predicted noise sound pressure level is not the initial requirement of the active noise cancellation system. noisy digital signal

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