摘要
Abstract
In view of the occurrence and prevention and governance of coupling disasters under the complex environment of coal mines,the data are preprocessed by collecting the information of multiple mixed gases(O2,CO,CO2,etc.),as well as temperature,humidity,atmospheric pressure and others from different sensors.Based on the evolutionary mechanism of coal spontaneous combustion and gas disaster information in goaf,the time series data collected by sensors are converted into image like matrix data through data preprocessing methods such as data cleaning,data transformation,normalization and so on,and a new mixed gas recognition method is proposed;Adopting adaptive correction method to compensate for drift in the distribution of data,and performing drift compensation at the level of classification decision-making to match the algorithm with the current sensor output;The development and system integration of an intelligent early warning software platform based on multi-source spatiotemporal monitoring data are completed,achieving online monitoring,intelligent identification,and real-time early warning of goaf thermodynamic disaster early warning indicators in coal mine,providing technical support for the prediction and early warning of thermodynamic disasters in mines.关键词
热动力灾害/演化机制/数据监测/智能预警/采空区Key words
thermodynamic disaster/evolutionary mechanism/data monitoring/intelligent early warning/goaf分类
矿业与冶金
