The vibration signals of wind turbines are often disturbed by strong noise and will be annihilated when exhibiting fault or strong instability. Denoising is required prior to facilitating an analysis of vibration fault characteristics. A wavelet denoising method based on variational mode decomposition (VMD) and multiscale permutation entropy (MPE) is proposed. The characteristics of VMD are analyzed, and the randomness and complexity of noise are evaluated by MPE. If the MPE of the modal component after VMD is larger than the evaluation value, then it is denoised by wavelet, and the signal is reconstructed with other modal components without wavelet denoising to achieve the denoising effect. The db1, sym8, EMD and EWT denoising methods and the proposed method are compared using the same simulation signal. Simulation results show that the denoising effect of the proposed method is better than the other four methods, and the two quantitative evaluation indexes of relative error and root mean square error obtain desirable values. The shaft vibration signals of the Case Western Reserve University and wind turbine are used to verify the effectiveness of the proposed method, and the denoising effect is also better than the other four methods. The proposed method eliminates most of the noise components while retaining the effective information of the signal. Therefore, this method can provide a good foundation for the research and analysis of the characteristics of late vibration signal.
The electromagnetic vibration noise level of a permanent magnet synchronous motor (PMSM) directly affects the Noise, Vibration, and Harshness (NVH) performance of an electric vehicle. Taking a PMSM for electric vehicle driving as an example, the electromagnetic noise characteristics were studied by combining ANSYS Workbench multi-physical field finite element analysis platform. The electromagnetic vibration force of the stator teeth of the motor is the main source of electromagnetic noise. The magnetic field of the motor can be optimized by changing the slot structure of the motor rotor, so as to improve the electromagnetic vibration force of the stator teeth and reduce the electromagnetic vibration noise of the motor. In order to optimize the magnetic field, three different rotor slot structures are proposed. The most suitable slot structure is found by comparing and analyzing the magnetic field, noise field, and electromagnetic force with the structure before optimization. By comparing the results before and after optimization, it can be seen that the optimized motor can effectively reduce the vibration noise of the motor and ensure the electromagnetic performance of the motor.
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