| The drum is the key cutting part of coal breaking and crushing machine,and the optimization and adjustment of cutting parameters is the premise of low energy consumption and high efficiency mining of shearer.Due to underground mining conditions,thickness of cutting coal wall surface random distribution,drum couldn’t stay according to cutting coal thickness changes in the real time adjustment of cutting parameters,how to acquire accurate stay open mining thickness of the wall surface features,the primary problem is that 3d representation according to coal wall features real-time adjusting roller cutting parameters to be solved.Therefore,precise reconstruction of 3d surface of coal wall and intelligent and efficient mining of shearer can be realized by constructing shearer wall cutting experiment platform,reconstructing 3d surface of coal wall to be cut,constructing shearer multiparameter coupling optimization model.Considering coal wall thickness distribution of fully mechanized working face of randomness and experimental cutting features,casting a variety of different thickness of the coal wall specimen,cutting experiment of coal wall structures,coal mining machines,complete test bench of mechanical system and control system design,control roller cutting speed and the level of the traveling mechanism mobile transmission,gathering drum cutting motor and walking cutting energy consumption data of the samples.Using precision measuring machine arm of the coal wall specimen surface for 3d reconstruction,obtaining 3d model cutting coal wall specimen surface,combined with the point cloud segmentation algorithm based on region growing segmentation for coal wall specimens of different areas,the point cloud denoising is realized by using statistics filter method,calculated the average coal wall specimen thickness values.Using quadratic rotational regression orthogonal combination experiment for drum rotating speed,drawing speed and cutting depth of the optimal combination of the three factors,primary and secondary influence sequence and regression model,combining has access to average thickness of the coal wall and rotational regression model,using the particle swarm algorithm to obtain the minimum cutting than the optimal energy consumption when the roller speed and drawing speed,Further combined optimal speed regulation of cutting parameters of shearer is realized.The experimental results show that by getting coal wall 3d point cloud model,accurately calculate the average thickness of coal wall specimen,using quadratic orthogonal rotating combination test of regression model is very significant,determines the drum rotating speed,drawing speed and the optimal combination of the cutting depth,coal thickness is realized by using particle swarm algorithm changes the further optimization of cutting parameters,Combined with the actual cutting experiment,the reliability of the algorithm is verified,and the low energy consumption and high efficiency mining of shearer is finally realized. |
