Abnormal Data Analysis and Chart Recognition of Mine Safety Monitoring and Early Warning System
There have always been a large number of data anomalies such as missing,interference,error,and concealment in the mine safety risk monitoring and early warning data,which is not conducive to safety management and rescue.In this paper,we summarize and verify the various types and quantity proportions of abnormal data from two perspectives,and find that about 70%of the violations or safety hazards related to the two professional systems related to the two professional systems can be traced back to human factors,and discuss the causes and countermeasures of these factors.In view of the types of abnormal data that occur with high frequency,this paper expounds a chart analysis method that is helpful to improve the efficiency of data analysis and quickly determine or eliminate violations,and tries to systematically and theoretically summarize and sort out the early warning and analysis technology of mine safety perception data.Measures to reduce abnormal data and improve the application effect of monitoring and early warning system are proposed.
big datasecurity-aware datadata analysisrisk early warningmine hidden danger investigation