Roller Eccentricity Self-optimization Control Based on Improved Lifting Wavelet Transform

In order to improve the performance of traditional wavelet transform, lifting wavelet transform is used to extract roller eccentricity signals and to make self-optimization control on line. An improved ant colony algorithm is used to optimize the wavelet threshold, and a self-optimization strategy is used to optimize the system parameters. The lifting wavelet transform does not depend on Fourier transform, so the calculation is simple and the operating speed is fast. The simulation results show that the proposed control strategy is effective and is adaptive to the outside interference, so it can make real-time and dynamic control on roller eccentricity signals.