Detection of Surging Sound with Wavelet Transform and Neural Networks

摘要

An acoustic diagnosis technique for the blower by wavelet transform and neural networks is described. It is im- portant for this diagnosis to detect surging phenomena, which lead to the destruction of the blower. Dyadic wavelet transform is used as the pre-processing method. A multi-layered neural net- work is used as the discrimination method. Experiment is per- formed for a blower. The results show that the neural network with wavelet transform can detect surging sound well.