Gray Markov chain trajectory prediction method for shearer memory cutting

Abstract

The invention discloses a gray Markov chain trajectory prediction method for shearer memory cutting. The method comprises the steps that a drum height data sequence for prediction is acquired: mining machine memory cutting data in the mining process of 6 to 8 working faces on the back side of the current working face are acquired; the drum height is preliminarily predicted; a drum height preliminary prediction results is amended, wherein prediction residual Markov chain establishing, Markov predicting, drum height prediction data set calculating and shearer heightening data set acquiring are carried out; and a heightening trajectory is acquired, and specifically a data processing device acquires the shearer heightening trajectory of the current working face according to the shearer heightening data set acquired in the previous step in the mining process of the current working face. The method provided by the invention has the advantages of simple steps, reasonable design and simple realization, good use effect, simple method steps, reasonable design, easy realization, good use effect and high prediction accuracy, and carries out heightening trajectory prediction based on a gray Markov chain.

Description

technical field [0001] The invention belongs to the technical field of coal seam mining, and in particular relates to a gray Markov chain trajectory prediction method for coal shearer memory cutting. Background technique [0002] Shearer is the core equipment of mechanized mining in coal mines. Its degree of automation determines the automation level of fully mechanized mining face. Realizing the automatic height adjustment of shearer drum is not only an important link to realize the automation of the production process of coal mining face, but also has a great impact on the extension of the machine. It is of great significance to improve the service life, improve the reliability of equipment, ensure the safety of workers, and improve the quality of coal. It also has a greater role in promoting the intelligent control of coal mining machinery and the sustainable development of the coal industry. In order to realize the automation and intelligence of the height adjustment of ...

AI Technical Summary

Problems solved by technology

At present, the automatic height adjustment of coal shearers at home and abroad generally adopts the memory cutting method, which mainly relies on the height adjustment data of the previous knife drum, lacking the data of the next coal seam, it is difficult to adapt to the fluctuation of the coal seam

In order to improve the accuracy of the height adjustment of the shearer drum, scholars have carried out various researches on the prediction of the trajectory of the shearer drum, and achieved certain results, but there are still many shortcomings in the reliability, real-time and accuracy of the algorithm , it has been successfully applied in the control of the height adjustment of the shearer drum in the working face

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