Environmental safety monitoring based on information optimization fusion in coal mines
Yin Li · Journal of Heilongjiang Institute of Science and Technology · 2007
Aimed at improving conventional mine environment-monitoring method suffering from lower judgment certainty and less sufficient data, this paper proposes a new safe monitor way based on multi parameters and two stage information optimization fusion. This method synthesizes gas, dust, CO, wind [JP+2]speed and temperature, and uses multi sensors to collect parameters, and the method firstly involves using Bayes estimate theory to fuse the homogeneous data for the first time and generate characteristic vector of mine environmental, and then comparing it with standard characteristic vector of mine environmental to obtain grey associated degree for the second data fusion time. According to grey associated degree, it is possible to judge the environmental safe level, optimize and integrate environmental monitored parameters. This method, characterized by sufficiently utilizing the effective monitored data, optimizing homogeneous data, and considering the complementation of the different data source makes possible an improvement in the reliability and entirety of monitor system.