The Grey Markov Chain Model Based on Sliding Window in Vertical Steering Locus Forecasting for Shearers

Abstract

Aiming at the current situation that the coal-rock interface identification in the coal mining process is difficult to realize, the solution of predictive algorithm to realize the locus prediction of the shearer is proposed, so that the intelligent control of the shearer is realized. The gray Markov chain predictive model based on sliding window is proposed due to the small number of data samples in the process of locus prediction of the shearer. The model has the characteristics of relatively simple algorithm, ability to respond to random events, high prediction accuracy and fast calculation speed. Through the simulation experiment, the sliding window width was determined and the predictive algorithm was verified at the same time. The simulation experiment results indicated that the predictive algorithm has fast response speed and high prediction accuracy, which is suitable for practical applications.