基于隐马尔可夫模型的煤矿胶带机异常时间点预测  

Predication of abnormal accident occurrence time for mine belt conveyor based on Hidden Markov Model

作　　者：李小斌[1,2] 任世锦[1] 李世银[3] 

机构地区：[1]江苏师范大学计算机科学与技术学院,徐州221116 [2]中国矿业大学计算机科学与技术学院,徐州221008 [3]中国矿业大学信息与电气工程学院,徐州221008

出　　处：《南京大学学报（自然科学版）》2013年第2期217-225,共9页Journal of Nanjing University（Natural Science）

基　　金：国家"863"计划(2008AA062200);江苏省产学研联合创新资金(BY2009114);徐州市工业科技计划(XX001);徐州师范大学重点基金(10XLA13)

摘　　要：煤矿胶带输送机的保护可以保障煤矿生产的平稳高效.针对如何有效地对胶带机发生异常的时刻的预测,提出了一种基于隐马尔可夫(Hidden Markov Model,HMM)和其改进型隐式半马尔可夫模型(Hidden Semi-Markov Model,HSMM)的胶带输送机异常时刻预测的方法.通过对胶带输送机保护传感器采集的时间序列进行特征提取,建立对应的HMM模型及HSMM模型,对胶带机异常发生时刻进行预测.在实际生产数据集上的实验表明,HMM和HSMM模型可以有效地对异常事件发生的时间点进行预测.In a mine enterprise generous goods and materials are transmitted by belt conveyor.So it is of great importance to guarantee the belt conveyor running stable and efficient.There are many abnormal accidents in production when belt conveyor is running.Two distinct abnormal accident,i.e.pile coal lightly accident and pile coal severity accident are inspected in this paper.The pile coal lightly accident should be removed immediately when it happened,otherwise it will cause the coal severity accident happen.While the pile coal severity accident would cause the mine production interruption immediately.So how to keep the mine conveyor continuous running is valuable for mine enterprise production.This paper puts forward a method to predict the abnormal accident occurrence time based on Hidden Markov Model（HMM）and Hidden Semi-Markov Model（HSMM）.Firstly the paper gives a thorough theory description about the structure and inference for HMM and HSMM.Especially a stated occurrence time predication algorithm is given based on the HSMM.Large amount of time series is collected through belt conveyor protection sensors in Pin Ding Shan Mine Enterprise.After feature extraction the corresponding HMM or HSMM model could be built on these datasets.The accident occurrence time is able to be predicted based on the HMM model or HSMM model.Experiments carried on the actual production datasets illustrate that HSMM model can effectively predict abnormal accident ＇ s occurrence time.

关 键 词：隐马尔可夫模型 隐半马尔可夫模型 胶带输送机 预测 

分 类 号：TD7[矿业工程—矿井通风与安全]