Steering motor noise signal recognition based on CEEMDAN and CDSSAICA
In order to solve the problem of inaccurate identification of noise source of vehicle steering motor.In this paper,a complete empirical mode decomposition based on adaptive noise and an improved independent analysis method for Salps populations are proposed.Firstly,an independent analysis method for improved Salp population was proposed.The method used improved Tent chaotic mapping to initialize the population,and Logistic chaotic mapping and dynamic learning were used to update the leader and follower,respectively.The simulation results show that the separation efficiency of the proposed method is 4.38%and 1.01%higher than that of FastICA and SSAICA,respectively.Finally,the combined algorithm is used to separate and identify the single channel noise signal of the vehicle steering motor.The results show that the combined algorithm can effectively separate the characteristic signals of different frequencies in the vibration noise signal of the motor.The main reasons for the motor noise under stable working conditions are rotor unbalance and electromagnetic noise.
万方数据
维普
