Abstract
Coal mining professionals in coal mining have recognized that the assessment of top coal release rate can not only improve the recovery rate of top coal, but also improve the quality of coal. But the process was often performed using a manual-based operation mode, which intensifies workload and difficulty, and is at risk of human errors. The study designs a assessment system to give the caving output ratio in top coal caving as accurately as possible based on the parameters adaptive Takagi-Sugeno (T-S) fuzzy system and the Levenberg-Marquardt (LM) algorithm. The main goal of the adaptive parameters based on LM algorithm is to construct its damping factor in the light of lowering of the objective function which is as taken as the index of termination iteration. The performance of the system is evaluated by Pearson correlation coefficient, Coefficient of Determination and relative error where the results of the Takagi-Sugeno method and the parameters adaptive Takagi-Sugeno method are compared to make the evaluation more robust and comprehensive.
Highlights
Mechanized top-coal caving is one of the most important production technologies to realize high production, high efficiency and low-consumption coal mining
The simulation experiments were designed to realistically simulate the actual process of topcoal caving such that the intrinsic relation between rock proportion of coal-rock flow (RPCRF) and caving output ratio (COR) can be directly reflected in the simulation
A T-S fuzzy inference system based on adaptive parameter identification method was successfully developed and applied for the assessment of COR in top coal caving work
Summary
Mechanized top-coal caving is one of the most important production technologies to realize high production, high efficiency and low-consumption coal mining. One of the focuses of scientific and technological developments in fully mechanized top coal caving system is related to improving the assessment of caving output ratio. The aforementioned discussion motivates us to develop a method to analyze the relationship between the caving output ratio (COR) and rock proportion of coal-rock flow (RPCRF), so as to assess the COR and meet the embedded equipment requirements of coal caving automation platform. The output ratio of different levels of top coal can be determined by calculating the released markers at the different levels [27]. Using the coal-rock recognition idea of the multi-sensor information fusion in [5], we can obtain the more accurate RPCRF according to the sensor installation and data acquisition methods. The installation position of sensor is shown in Figs 1and 2, and the definition of rock proportion has been described in Ref [5]
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