APPLICATION OF STATISTICAL PROCESS CONTROL THEORY IN COAL AND GAS OUTBURST PREVENTION

Abstract

With Chinese coal exploitation extending to depth rapidly, a large number of coal and gas outburst accidents happened and resulted in thousands of casualties in the last decade. Coal and gas outburst prevention project has become the prerequisite of underground coal mining, but its process control ability is especially poor. By integrating statistical process control theory into the process of coal and gas outburst prevention, three urgent problems were solved. First at all, data structure of the process inspection parameters was designed asvectors, which only consisted of principle elements and formed data series as time went by. Secondly, based on sample data of the experimental area, statistical characteristic of inspection parameters was gained and their X-Rs control charts were drawn. Finally, performance of process running statuses that might be in control or beyond control were analyzed in detail. When the process was in control, curves should slightly fluctuate around their center lines and between upper control limits and lower control limits. Otherwise, the process was beyond control, in which X control charts were used to identify anomalies of data value fluctuation and Rs control charts were used to identify anomalies of data fluctuation amplitudes. By the experimental application in Hexi colliery of China, the interdisciplinary research was proved to be helpful to improve process control ability and then prevent coal and gas outburst accidents.