BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART

Abstract

Roller is an important task of the coal winning machine cutting coal institutions,its structure and motion parameters will directly affect the working efficiency and working reliability of coal winning machine.Based on virtual prototype technology coal winning machine the coupled model is established,through dynamic simulation of coal winning machine equivalent stress values of key parts;Simulation different drum rotating speed,drawing speed,cylinder helix Angle,and the cutting line spacing they cut the shell and the equivalent stress value of planet carrier,the roller structure and motion parameters on reliability of key parts of coal winning machine cutting part influence trend;Combined with neural network technology,with different roller structure and motion parameters of the equivalent stress of key parts of coal winning machine values as the neural network training sample,the helix Angle of optimization design,stress value of key parts in the hour of cylinder helix Angle.The research for the drum more accurate theoretical foundation for the selection of structure and motion parameters,has certain engineering application value.

Keywords

• Shearer;Drum;Reliability;Neural network;Optimization design