支架压力和位态模糊识别的综放放煤模式

Pattern of automation top-coal caving based on fuzzy recognition of support pressure and state

为解决综放开采放煤自动化的瓶颈问题,探讨了综放开采自动化放煤面临的难点和关键,分析了综放开采放煤过程中特殊的支架压力和位态变化规律,认为顶煤的放出会导致支架压力和位态发生相应规律性的变化,建立了放煤过程支架压力和位态变化理论模型,提出了基于支架压力和位态变化模糊识别的综放自动化放煤模式,通过学习并记忆放煤过程中液压支架立柱压力和位态的变化特征,预测支架上方待放顶煤体的垮落和放出状况,并将实际的顶煤放出量和放煤时间进行拟合,通过预测放煤时间和实际放煤时间差异可以间接得到顶煤放出率,利用基于神经网络方法对芦子沟矿综放面进行了现场实测和分析,验证了其合理性与科学性.

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.