Abstract:
The core of coal mine intelligence is the intelligence of comprehensive mining face, and the key to the intelligence of comprehensive mining face is digitalisation. In order to improve the intelligent level of comprehensive mining face, the academic idea of intelligent mining of comprehensive mining face of ‘coal mining is data mining’ is put forward, and five key technologies such as digital working face construction, precise cutting, equipment position detection and control, equipment group speed control and equipment group co-control are condensed, and the academic thought connotation of the idea based on the five key technologies is elaborated. It elaborates the connotation of academic ideas based on the five key technologies, and constructs the academic idea system architecture based on digital working face intelligent mining. With regard to the construction of the digital coal seam in the comprehensive mining face, it integrates the digital coal seam data, equipment group data, etc., and uses spatial interpolation algorithm and digital twin technology to construct the digital working face, constructs a database including digital coal seam data, historical cutting position and speed data, coal mining data, equipment group cooperative data, etc., and elaborates the dynamic updating method of the digital working face by integrating data from multiple sources, so as to improve the accuracy of the digital working face model. For the problem of accurate cutting in comprehensive mining face, the trajectory planning method that integrates the cutting trajectory planning data driven by digital coal seam and historical cutting position data, as well as the intelligent interpolation trajectory tracking control method based on the planning trajectory data are elaborated, and the artificial intelligence algorithm is used to carry out iterative optimization on the planning cutting trajectory data and the position interpolation data for trajectory tracking control, so as to increase the accuracy of the planning of the cutting trajectory and the control precision of the trajectory tracking. For the problem of detecting and controlling the position of the equipment in the comprehensive mining face, a precise detection method of the position of the equipment in the face based on the fusion of multi-sensor data and a position control method based on the neural network algorithm are elaborated, and the accurate detection and control of the position of the equipment group of the comprehensive mining face is achieved by the in-depth fusion of the position perception data and the position control data and iterative optimization; For the problem of controlling the speed of the equipment group of the comprehensive mining face, a force-electricity coupling method is proposed. For the speed control problem of the equipment group in the comprehensive mining face, the force-electricity coupling cutting load measurement method and the speed intelligent control method based on the artificial intelligence optimisation algorithm are proposed, which integrate the cutting load data and coal mining data, and use the artificial intelligence optimisation algorithm to make decisions on the optimal hauling speed, cutting speed and coal transporting speed, so as to realise the efficient and intelligent cutting control based on the speed matching of the equipment group. For the problem of cooperative control of equipment group in comprehensive mining face, the master-slave cooperative control method of equipment group based on artificial intelligence algorithm is elaborated, taking the position and speed control data of coal mining machine as the dominant, and the control data of scraper conveyor and hydraulic support as the follower, and solving the optimal cooperative control parameter of the displacement and speed of the equipment group by using the neural network algorithm of artificial intelligence, so as to realise the intelligent, efficient and safe operation of the equipment group. The five key technologies of ‘coal mining is data mining’ have been applied in coal mines, verifying the feasibility of the academic idea. The academic idea of ‘coal mining is data mining’ has laid an important theoretical foundation for breaking through the key technical problems of intelligent coal mining.