Abstract：The bottleneck of fully mechanized caving mining further development is automation. The key difficulties top-coal caving faced were discussed and the change law of support pressure and state in the process of caving were analyzed. The research suggests that the release of top-coal will cause the regular changes in support pressure and state. By setting up the theory model of support pressure and state change, monitoring the correlation indexes, and then inputting the inherent structural parameters, the resultant force and action spot of top-coal body was obtained. Through the learning and memory of the support change characteristics in the process of caving, the automation pattern based on fuzzy recognition of support pressure and state was put forward, which can forecast the collapse and releasing features of top coal body. By fitting the actual top-coal caving rate and the effective working time, the rate of recovery according to the time difference was indirectly acquired. This automation method based on the principle of neural network was then applied in Luzigou Mine, which verified the rationality and the scientific nature of this method.
范志忠，王耀辉，黄志增. 支架压力和位态模糊识别的综放放煤模式[J]. 辽宁工程技术大学学报(自然科学版), 2016, 35(11): 1205-1211.
FAN Zhizhong, WAGN Yaohui, WAGN Dongpan. Pattern of automation top-coal caving based on fuzzy recognition of support pressure and state. Journal of LNTU.Natural Science, 2016, 35(11): 1205-1211.