Study on the sound quality of unsteady exhaust noise based on RNR-WVD calculation and GA-wavelet network

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Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (12) : 74-80.

ZENG Falin1,SUN Sumin2

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Abstract

The GA-BP acoustic quality prediction model based on the psychoacoustical objective parameters can accurately predict the sound quality of the steady state exhaust noise.For the research on unsteady state noise, RNR (regularization non-stationary regression technique) was applied to compute the WVD distribution (RNR-WVD), and a new parameter SQP-RW was built to replace the objective parameters that have less correlation with the satisfaction degree.Meanwhile, a WNN (Wavelet Neural Network, WNN) was constructed by using the Morlet wave basis function which was used as the transfer function of the hidden layer.And GA was used to optimize the weights and thresholds of the WNN layers, the GA-WNN was constructed and used to predict the acoustic quality of the unsteady exhaust noise.The results show that the GA-WNN is more accurate in predicting the sound quality of unsteady exhaust noise than the GA-BP neural network.With the introduction of SQP-RW, the model has higher accuracy and it can reflect the characteristics of unsteady signals and the sound quality characteristics.

Key words

Non-stationay exhaust noise / Wavelet Neural Network / Acoustic quality / Regularization and unsteady regression / WVD distribution

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ZENG Falin1,SUN Sumin2. Study on the sound quality of unsteady exhaust noise based on RNR-WVD calculation and GA-wavelet network[J]. Journal of Vibration and Shock, 2019, 38(12): 74-80

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