Blind Sources Separation Method Of Mechanical Fault Based On The Quantum Genetic Algorithm

Based on the deficiency in the blind separation method of mechanical fault sources based on the genetic algorithm, a blind separation method of mechanical fault sources based on the quantum genetic algorithm is proposed. some innovative results are obtained. The research contents in this paper is mainly as follows1. The research illuminates the significance of this paper, the development and application of blind separation of mechanical fault sources and quantum genetic algorithm are also discussed. Based on the above comments, the main innovation Contents and Contents of this paper are briefly given.2. Discussing the relevant theoretical knowledge of quantum genetic algorithm, Based on the deficiency in the blind separation method of mechanical fault sources based on the genetic algorithm, which is named as GA-BSS method, and the unique advantages of quantum genetic algorithm, a blind separation method of mechanical fault sources based on the quantum genetic algorithm, which is named as QGA-BSS method, is proposed. The proposed method is compared with the traditional GA-BSS method. The simulation results show that the QGA-BSS method is superior to the traditional GA-BSS method, especially in the convergence speed. The proposed method avoids the premature convergence in the GA-BSS method and greatly reduces the amount of calculation. Finally, The proposed method is applied to the separation of bearing fault, and can extract the bearing fault features from the mixture signals successfully.The experiment results prove that the proposed QGA-BSS method is effective.3. 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.4. Based on the unique advantages of double chains quantum genetic algorithm and blind source separation, a blind separation method of mechanical fault sources based on the double chains quantum genetic algorithm, which is named as DQGA-BSS method, is proposed. The proposed method is compared with the traditional GA-BSS method and QGA-BSS method. The simulation results show that using three algorithms can achieve satisfying separation performance. However, in the convergence speed and running speed, there are great differences in the three methods, the speed of convergence on QGA-BSS method is faster than GA-BSS method, the running time on QGA-BSS method is shorter than GA-BSS method. However, Compared with QGA-BSS method, the running speed of DQGA-BSS method is faster than QGA-BSS method. Using DQGA-BSS algorithm can save a lot of storage space and reduce the running time. It can be seen that the DQGA-BSS method is superior to the traditional GA-BSS method and QGA-BSS method, Finally, The proposed method is applied to the separation of bearing fault, The experiment results prove that the proposed DQGA-BSS method is effective.5.Inspired by the Double Chain Quantum Genetic Algorithm, If encoding Qubit can transferre from plane circumference to spherical coordinates, then the searching space of algorithm will be greatly increased, For this reason more conducive to find the optimal solution, Based on it, a blind separation method of mechanical fault sources based on the Bloch double chains quantum genetic algorithm, which is named as BQGA-BSS method, is proposed. The proposed method is compared with the traditional DQGA-BSS method. Finally, The experimental results prove the effectiveness of the algorithm.