Audio Signal Fault Diagnosis Based on Convolutional Neural Network

Abstract

Monitoring the audio signal of each link of the broadcast transmission is not only to control the broadcast quality, but also the basis for fault diagnosis. Broadcast transmission has problems such as wrong signal, lost signal, downtime, interference signal, etc. To prevent these problems, traditional monitoring system uses audio contrast technology. This technique requires signal synchronization for delayed signals. What’s more, it is also impossible to classify and diagnose audio signals. As a feed forward neural network, convolutional neural network is one of the typical algorithms of deep learning. This article mainly discusses how to use convolutional neural networks to preprocess audio signals, extract features and diagnose faults. This article also summarizes the advantages of convolutional neural networks for audio fault diagnosis.KeywordsBroadcast audio signalConvolutional neural networkExtract featuresFault diagnosis