Multi-Sensor Data Fusion Technology Based on BP Neural Network Application in the Coal Mine Equipment Fault Diagnosis

Xiang Zhong Meng; Hui Long Liu; Zi Sheng Hou

doi:10.4028/www.scientific.net/AMM.678.238

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 678Multi-Sensor Data Fusion Technology Based on BP...

Multi-Sensor Data Fusion Technology Based on BP Neural Network Application in the Coal Mine Equipment Fault Diagnosis

Abstract:

In this paper, for the frequent faults problems of the mine air compressor main motor, we use the BP neural network learning algorithms on the basis of the theory of multi-sensor data fusion. The collected characteristic signals were processed by the method of data fusion, and we could get the current motor fault state value. Compared to the experimental results, it can realize the fault diagnosis of mine equipment obviously.

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Periodical:

Applied Mechanics and Materials (Volume 678)

Pages:

238-241

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.678.238

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Online since:

October 2014

Authors:

Xiang Zhong Meng*, Hui Long Liu, Zi Sheng Hou

Keywords:

BP Neural Network (BPNN), Fault Diagnosis, Multi-Sensor Data Fusion

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* - Corresponding Author

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