Coal Gangue Interface Recognition Based on MFCC Research

Abstract:

In view of the existing coal gangue interface identification technology use ray method that it is not applicable to the working face what it dose not contain radioactive elements in the roof or contain low amounts of radioactive elements, and the detection range of radar detection is lesser, the signal attenuation is relatively serious, so putting forward a kind of coal gangue interface recognition based on Mel frequency cepstrum coefficient of MFCC. The method using coal gangue were put down in the process of coal gangue on the difference of the characteristics of the acoustic signal recognition, first of all, using Mel frequency cepstrum coefficient will after denoising coal gangue acoustic signal transformation to the frequency domain processing, extracting the 32 d characteristic parameters of coal and gangue acoustic signal;The experimental results show that the method can accurately identify the coal gangue down state.

• Periodical: Applied Mechanics and Materials (Volumes 411-414)
• Pages: 1058-1061
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.411-414.1058
• Online since: September 2013
• Authors: Ai Xiang He, Meng Ke Zhang, Chen Chen Wang
• Keywords: BP Neural Network (BPNN), Caving Technology, Coal Gangue Identification, Mel Frequency Cepstrum Coefficient, Support Vector Machine (SVM)

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