The Open Automation and Control Systems Journal

2014, 6 : 1793-1797
Published online 2014 December 31. DOI: 10.2174/1874444301406011793
Publisher ID: TOAUTOCJ-6-1793

Researching Coal and Rock Character Recognition Based on Wavelet Packet Frequency Band Energy

Guanghui Xue , Xinying Zhao , Ermeng Liu , Weijian Ding and Baohua Hu
School of Mechanical, Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.

ABSTRACT

At present top coal caving is done by workers at the fully mechanized top-coal caving face, where the production rate is low and the workers’ safety is under threat. In order to reduce the casualties, realize ”less people” even “no people” and the high-efficient and high-yield of coal mine, the coal and rock character recognition was researched on underground, the method based on the wavelet packet frequency band energy analysis, for coal and rock identification was proposed. Using the self-developed mine portable vibration data recorder to pick up the vibration signals at the hydraulic support tail beam under the different conditions of coal caving, gangue caving and roof rock caving in the fully mechanized top-coal caving face. The conclusion has been drawn after analyzing the vibration signals by the wavelet packet frequency band energy: When coal caving, the Edge band focus on 1250 Hz~1562.5 Hz and 2187.5 Hz~2500 Hz, when gangue caving, the Edge band focus on 0~625 Hz and 937.5~1250 Hz, when roof rock caving, the Edge band focus on 1875~2187.5 Hz and 3750~4062.5 Hz. The result shows that different edge bands under the different conditions can be used as the criterion for the coal and rock character recognition in the fully mechanized top-coal caving face. And research results could provide a new idea and the method for the coal and rock character recognition.

Keywords:

Coal and rock characters recognition, fully mechanized top-coal caving face, vibration signals, wavelet packet frequency band energy..