Roller eccentricity signal identification and self-adaptive control based on second generation wavelet transform

The computation time of Classical wavelet transform which based on frequent field is too long to meet the demand of real-time control for roller eccentricity. A novel Wavelet based on lifting scheme is proposed for decomposing and dealing with eccentricity signal at the different resolution. The eccentricity factor is identified from disturbance and noise with lifting and dual lifting scheme theory by analyzing the rolling force and thickness deviation. Moreover, parameter Self-adaptive control is used for on line control of roller eccentricity. The comparative studies with traditional wavelet transform are carried out in this paper and the simulation results show the effectiveness of the proposed algorithm. The execution speed of the proposed algorithm is increased at least twice as conventional wavelet transform method.