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Vol. 172, Issue 6, June 2014, pp. 124-129

 

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Research on Health State Perception Algorithm of Mining Equipment Based on Frequency Closeness
 

1 Gang Wang, 1 Yanjun Hu,2 Guoqing Ji

1 The Engineering Research Centre of Perception Mine, China university of Mine & Technology, Xuzhou, 221008, China
2 Department of Aviation Ammunition, Air Force Logistics College, Xuzhou, China, 221006
1 Tel.: 051683899723, fax: 051683899597

E-mail: wgcumt@yeah.net

 

Received: 16 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems

 

Abstract: The health state perception of mining equipment is intended to have an online real- time knowledge and analysis of the running conditions of large mining equipments. Due to its unknown failure mode, a challenge was raised to the traditional fault diagnosis of mining equipments. A health state perception algorithm of mining equipment was introduced in this paper, and through continuous sampling of the machine vibration data, the time-series data set was set up; subsequently, the mode set based on the frequency closeness was constructed by the d neighborhood method combined with the TSDM algorithm, thus the forecast method on the basis of the dual mode set was eventually formed. In the calculation of the frequency closeness, the Goertzel algorithm was introduced to effectively decrease the computation amount. It was indicated through the simulation test on the vibration data of the drum shaft base that the health state of the device could be effectively distinguished. The algorithm has been successfully applied to equipment monitoring in the Huoer Xinhe Coal Mine of Shanxi Coal Imp&Exp. Group Co., Ltd.

 

Keywords: Mining equipment, The dual mode set, Health state perception, Time-series data mining, Frequency closeness.

 

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