Volume 8 Number 1 (Jan. 2013)
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JSW 2013 Vol.8(1): 142-150 ISSN: 1796-217X
doi: 10.4304/jsw.8.1.142-150

Special Event Time Predication for Mine Belt Conveyor Based on Hidden Markov Model

Xiaobin Li1, 2, Jiansheng Qian1, Zhikai Zhao1
1School of Computer Science and Technology, China University of Mining and Technology, Xuzhou Jiangsu,China
2School of Computer Science and Technology, Jiangsu Normal University, Xuzhou Jiangsu,China

Abstract—Coal mine belt conveyor can guarantee the coal mine production stable and efficient. On how to effectively predict abnormal accident occurrence time, this paper puts forward a method to predict the abnormal accident occurrence time based on Hidden Markov Model and Hidden Semi-Markov Model. Large amount of time series is collected through belt conveyor protection sensors. The corresponding HMM or HSMM model could be built after feature extraction. At last the accident occurrence time is able to be predicted based on the HMM model or the HSMM model. Experiments carried on the actual production data set illustrate that HMM and HSMM model can effectively predict specific event occurrence time.

Index Terms—Hidden Markov Model, Hidden Semi- Markov Model, Belt Conveyor, Prediction.


Cite: Xiaobin Li, Jiansheng Qian, Zhikai Zhao, "Special Event Time Predication for Mine Belt Conveyor Based on Hidden Markov Model," Journal of Software vol. 8, no. 1, pp. 142-150, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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