NONLINEAR BLIND SOURCE SEPARATION OF MECHANICAL FAULT BASED ON QUANTUM GENETIC ALGORITHM - PI HaiYu; LI ZhiNong; XIAO YaoXian (Jixie qiangdu)
Based on the deficiency in the traditional nonlinear blind separation method of mechanical fault sources,i. e. the separation matrix parameter and nonlinear mixing parameter in the nonlinear blind source separation are usually optimized separately,which easily lead to have one without another and low learning efficiency. Quantum genetic algorithm is introduced into the nonlinear blind source separation of mechanical fault,a nonlinear blind separation method of mechanical fault sources based on the quantum genetic algorithm,which is named as QGA-NBSS method,is proposed. The proposed method can simultaneously optimize all parameters in the nonlinear blind separation,i. e. the separation matrix and nonlinear mixing function,obtain global optimal solution,and greatly improves the global convergence of the algorithm. The simulation and experimental results show that the proposed algorithm is effective.