Gas monitoring warning signal identification based on time series similarity measure
Wei Lian-jiang · Journal of China University of Mining and Technology · 2012
The time series similarity measure technique is presented.In the case of one high gas coal mine from Shanxi province,one hundred and fifty gas warning time series has been got out from the large scale gas time series history database and from which seven representative kinds of time series patterns are listed out by clustering analysis based on DTW distance.With the piecewise morphological measure methods,three key indicators are extracted and filtered out.Then the morphological character table of the gas warning time series can be established.The gas monitoring warning signal identification algorithm is accordingly presented.The experiments indicate that the accuracy rate of this identification method reaches more than ninety two percent.With the values of k0 and k1,it is easily to identify if the alarm is caused by the gas emission after blasting or the gas outburst.From the statistical data,it could be concluded that the gas outburst will happen when k00.1 and k10.