Fault Diagnosis Approach of Local Ventilation System in Coal Mines Based on Multidisciplinary Technology

查看全文 作　　者：GONG Xiao-[1,2]yan;XUE [1]He;TAO Xin-[1]li;HU [2]Ning 机构地区：[1]School of Mechanical Engineering, Xi 'an University. of Science and Technology, Xi'an, Shanxi 710054, China;[2]Department of Aeronautics and Space Engineer, Tohoku University, Sendai 980-8579, Japan 出　　处：《Journal of China University of Mining and Technology》索引2006年第16卷第3期,共4页 基　　金：Projects 04JK197T supported by Shaanxi Education Bureau Science Foundation and 2005E202 by Shaanxi Science Foundation 摘　　要：In order to reduce the probability of fault occurrence of local ventilation system in coal mine and prevent gas from exceeding the standard limit, an approach incorporating the reliability analysis, rough set theory, genetic algorithm (GA), and intelligent decision support system (IDSS) was used to establish and develop a fault diagnosis system of local ventilation in coal mine. Fault tree model was established and its reliability analysis was performed. The algorithms and software of key fault symptom and fault diagnosis rule acquiring were also analyzed and developed. Finally, a prototype system was developed and demonstrated by a mine instance. The research results indicate that the proposed approach in this paper can accurately and quickly find the fault reason in a local ventilation system of coal mines and can reduce difficulty of the fault diagnosis of the local ventilation system, which is significant to decrease gas exploding accidents in coal mines. 关 键 词：故障诊断 局部通风 粗糙集 遗传算法 煤矿 IDSS