Coal-Gangue Acoustic Signal Recognition Based on Sparse Representation

Ai Xiang He; Nan Liu; Guang Fei Wei

doi:10.4028/www.scientific.net/AMM.333-335.546

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335Coal-Gangue Acoustic Signal Recognition Based on...

Coal-Gangue Acoustic Signal Recognition Based on Sparse Representation

Abstract:

Our country has rich coal resources. Further research is great significant to realize the automation of top coal caving mining technology. This paper presents a new method based on sparse representation for coal and gangue signal recognition. To solve the mining noise problem, the wavelet analysis is used to filter and de-noising. Sparse representation classification is based on the theory of compressed sensing. Recognition is achieved by analysis the sparse vector that the linearly optimal representation for a testing sample based on the training sample. Experimental results performed the method is accurate and stable.

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Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

546-549

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.546

Citation:

Cite this paper

Online since:

July 2013

Authors:

Ai Xiang He, Nan Liu, Guang Fei Wei

Keywords:

Coal-Gangue Acoustic Signal, Signal Recognition, Sparse Representation, Wavelet De-nosing

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