Abstract
Focusing on the problem of nonlinear noise cancellation caused by complex rail vehicles noise sources, this study proposes an active noise cancellation system based on the noise prediction of a convolutional fuzzy neural network. The multi-source noise signals of rail vehicles are predicted by the convolutional network to obtain the virtual error signal of the ideal noise reduction point, and then a fuzzy neural network is used to reduce the noise in a targeted manner. The simulation indicated that the system can operate stably and can effectively control the low-frequency noise of multi-source rail vehicles below 1000 Hz.
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