Roller eccentricity signal pick-up and adaptive control based on lifting wavelet transform and self-optimization

Traditional wavelet transform based on frequency domain is too long to meet the need for real-tlme control of roller eccentricity. A novel wavelet based on lifting scheme is used to decompose and deal with eccentricity signals at different resolutions. Through analyzing roll force and thickness deviation signals, the lifting and dual lifting scheme theory is applied to distinguish eccentricity signals from disturbances and noise, and self-optimization is employed to real-time control the roller eccentricity. The results of simulation show that the control strategy is effective and at the same data length, the operational speed of lifting scheme is enhanced at least twice as that of traditional wavelet.