Research On Abnormal Diagnosis Of Ventilation System In Daping Coal Mine

The abnormality of the ventilation system is the same as other objective things,it is a gradual process from quantitative change to qualitative change.If the abnormality of the ventilation system can be diagnosed promptly and accurately,the cause of the abnormality is identified,and effective preventive measures are taken,the occurrence of a safety accident can be reduced or avoided.In view of the poor timeliness and low level of abnormal diagnosis of ventilation system,the actual situation of heavy gas explosion accident occurred.This paper constructs the abnormality diagnosis index system of ventilation system from the physical composition of ventilation system,and uses AHP to determine the weight of indicators and formulate corresponding diagnostic criteria.The abnormal state diagnosis of the mine ventilation system is realized.The ventilation simulation software is used to simulate and analyze the abnormality of the ventilation system,and the abnormal influence range of the ventilation system is established.The mine ventilation online monitoring data and the BP neural network are used to identify the abnormal causes of the ventilation system.The abnormal diagnosis is based on the definition of the mine ventilation system,and the analytical structure model,which consists of three levels: target layer,factor layer and index layer,is constructed from the physical composition of the ventilation.Combined with mine ventilation resistance measurement and fan performance measurement data,the corresponding influencing factors are selected to establish the abnormal diagnostic index system of mine ventilation system.The abnormal diagnosis of mine ventilation system is based on the definition of mine ventilation system.The analytical structure model is constructed from the physical composition of ventilation.It consists of three levels: target layer,factor layer and index layer.Combined with mine ventilation resistance measurement and fan performance measurement data,the corresponding influence is selected.Factor indicators to establish an abnormal diagnostic index system for mine ventilation systems.Based on the analytic hierarchy process,the weights of each index in the abnormality diagnosis index system of ventilation system are determined.Combined with the mathematical statistical outlier processing method,the abnormal diagnosis criteria of ventilation system are established,and the corresponding mathematical model of abnormal diagnosis is established.The fault tree analysis method is used to determine the abnormal factors of the underground ventilation system,and the abnormal factors of the underground well are studied and analyzed to determine the location of the mine ventilation system and the difficulty of identifying the abnormal causes.The mine ventilation simulation software was used to construct the current simulation system of Daping mine ventilation system.Based on the current situation simulation,the ventilation anomalies that may occur in Daping Mine were simulated and analyzed,and a complete ventilation system abnormal sample library was formed to establish an abnormal influence scope library.The BP neural network was used to diagnose the abnormal cause of the ventilation system in Daping Mine.