WNN模型在预测声发射信号方面的应用

doi:10.11872/j.issn.1005-2518.2016.01.086

Abstract

Abstract:

Wavelet neural network has advantages of high precision，simple structure and fast convergence，etc. Therefore，attempts with this advantage model is applied to forecast aspect of acoustic emission，and the new predicting method in mining field be further improved.Based on a huge number of data in the process of coustic emission at laboratory rock loading experiment，a corresponding prediction model can be set up.Firstly，acoustic emission data obtained in the process of monitoring of laboratory experiments can be used to establish Wavelet Neural Network Model，and the acoustic emission monitoring of acoustic emission events rate for network autonomous learning can be further conducted.Finally，the obtained prediction results were compared with the actual value in order to calculate the error.The results demonstrated that the prediction accuracy was higher, and basically comparable with the actual monitoring results，which suggested that the Wavelet Neural Network Model can be employed to predict the acoustic emission signal in future.

Key words: acoustic emission, rock, Wavelet Neural Network, prediction

CLC Number:

TU45

WANG Xiaojun，CHEN Chen， ZHUO Yulong， DENG Shuqiang，FENG Xiao. Application of the WNN Model to Prediction of Acoustic Emission Signal[J].Gold Science and Technology, 2016, 24(1): 86-91.

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Application of the WNN Model to Prediction of Acoustic Emission Signal

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