Method for identifying abnormal sound signal based on convolutional neural network

Abstract

The invention provides a method for identifying an abnormal sound signal based on a convolutional neural network, and relates to the technical field of sound signal classification and identification.The method comprises the steps that firstly, six abnormal sound samples are collected by using an existing abnormal sound bank to form a sample sound bank and form samples with noise; then the sound in the sample sound bank is preprocessed and arranged in two dimensions of time and frequency domain into a two-dimensional sound feature graph as the input of a convolutional neural network model; theerror between an actual output result of a training set and a label result is calculated by using a cost function, a difference value is transferred by using a back propagation algorithm, and a weight vector in a full connection layer of the convolutional neural network is updated; the convolutional neural network model is trained by using a supervised learning method; lastly, data in a test setis input, and the accuracy of the convolutional neural network model is verified. The method for identifying the abnormal sound signal based on the convolutional neural network can identify the abnormal sound signal more efficiently and accurately.

Description

technical field [0001] The invention relates to the technical field of acoustic signal classification and identification, in particular to a method for identifying abnormal sound signals based on a convolutional neural network. Background technique [0002] The continuous noise generated in the industrial production process will cause various damages to the human body, and cause long-term irreversible damage to the human hearing system and nervous system; After the danger, the alarm signal, ringtone, etc. cannot be heard in time, and the danger cannot be actively escaped in time, which will cause greater harm to the people on site. Therefore, in addition to the need to use various technical means to eliminate or reduce the noise in the working environment, it is difficult to completely eliminate It is necessary to be able to monitor and identify various dangerous signals or alarm sound signals in a noisy environment in time to improve the accuracy of early warning of dangero...

AI Technical Summary

Problems solved by technology

[0002] The continuous noise generated in the industrial production process will cause various damages to the human body, and cause long-term irreversible damage to the human hearing system and nervous system; After the danger, the alarm signal, ringtone, etc. cannot be heard in time, and the danger cannot be actively escaped in time, which will cause greater harm to the people on t...

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