Application of the hybrid integration displacement algorithm based on CEEMDAN and wavelet threshold denoising in vibration screening equipment

Abstract

Vibration screening equipment has an extensive application profile in material screening, in which the displacement parameters can reveal the motion state of the material and affect the screening efficiency. These displacement parameters can be obtained by integrating the acceleration signal of the equipment. In this paper, to prevent the noise in the acceleration signal from further amplifying its negative effects on the subsequent integration, the acceleration signal is preprocessed by the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold denoising. Besides, a hybrid integration displacement algorithm is utilized to mitigate the influence of integration errors. The consistent results between simulation and platform experiments demonstrate that CEEMDAN in combination with wavelet threshold denoising can effectively remove noise while retaining the main frequency signal. In addition, the displacement signal obtained by the hybrid integration algorithm proposed in this paper is closer to the original displacement signal. Compared with the 2nd time-domain integration, the 2nd frequency-domain integration, and the empirical mode decomposition (EMD) integration methods, the integration method proposed in this paper achieves a smaller peak error, mean absolute error (MAE), and root mean square error (RMSE). The experimental results corroborate the superiority of this method in the application of vibration screening equipment.