Analysis and Diagnosis of Coal Shearer Machine Fault Based on Improved Support Vector Theory

In coal shearer monitoring system, the early detecting of fault is key technique for preventing the shearer fail. In this paper, the improved support vector machine theory is introduced to detected shearer fault under the mine underground, the improved algorithm based on support vector machine theory is analyzed, the multiple fault classifier is used to judge the fault types of coal shearer. The temperature fault types of coal shearer are reconstructed. Simulation results verify the validity of this method for early detecting fault under strong noise background in the coal shearer monitoring system.