Multisensor Data Fusion
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China is the world's largest coal producer and consumer countries. With the continuous progress of the modernization drive, the demand for coal is more and more, but coal mine safety situation is still grim. All of various types of coal mine accidents in production, the roof accident continued to hold the forefront. As we known, coal production is a dynamic process, a variety of parameters and variables are subject to change, yet all variables are not isolated, they are interconnected. These factors are from a different side to reflect a change or movement of the roof, so they are multi-information fusion integration. In this study, we take Xing-Cun village coal mine, which locate on Shandong province, for an example. In E3207 working face, underground 1000 meters, five kinds of sensors are installed. They are micro seismic sensors, fully mechanized working face powered support sensor, roof-to-floor convergence, two sides convergence of roadway, and borehole stress sensor. The ground control central can collected above five kinds of data in real-time. Using data fusion method, we setup up the model of fuzzy logic. Through data analysis, the five membership function are given, finally we get the fusion curve. By the curve we can identify the roof movement consistent with the law production practices, analysis the overlying rock strata, with good guidance to production. Facts have proved that the information can be fused to fully reflect the comprehensive and complementary data, improve the accuracy of the warning of roof movement, has positive significance to ensure safety in production.