基于小波变换的轧辊偏心分析与仿真

为了提高热轧带钢厚度精度,针对以快速傅立叶变换为基础的轧辊偏心识别方法的固有缺陷,利用在小波变换下奇异信号和随机噪声在多尺度空间中的模极大值传递特性的不同,提出一种基于小波变换识别轧辊偏心的新方法,用于分析轧制力信号和厚差信号,并将信号从随机噪声中有效分离出,实现对轧辊偏心的动态补偿·仿真研究表明,小波变换补偿轧辊偏心优于快速傅立叶和其改进算法,可使轧辊偏心引起的厚度波动减少90%·设计基于小波分析的轧辊偏心补偿控制的方法,使补偿控制系统更有效地工作,对外界环境干扰具有很好的适应性和对偏心信号实行动态实时的补偿控制·

Roll Eccentricity Analysis and Simulation Based on Wavelet Transform

In view of the intrinsic imperfection in identifying roll eccentricity by way of the fast Fourier transform, a new method is proposed to identify the roll eccentricity basis on wavelet transform to improve the delivery gauge of hot-rolled strips, etc., the difference of transmission characteristics of the maximum wavelet modulus between singular signal and random noise in multiscale space is utilized to analyze the signals from rolling load and thickness deviation so as to separate the signal from random noise and realize the dynamic compensation for roll eccentricity. The simulation results showed that the roll eccentricity compensation based on wavelet transform is better than the fast Fourier transform or its modification for improving delivery gauge of which the thickness fluctuation due to roll eccentricity can be reduced by more than 90 percent. The method proposed is a more effective and adaptive to outside interference especially to real-time dynamic compensation control of roll eccentricity.