摘要
为了提高传统小波变换的性能,使用提升小波变换提取轧辊偏心信号,并对其进行在线自寻优控制.采用一种改进的蚁群算法优化小波阈值,并运用自寻优策略对系统参数进行优化.提升小波不依赖傅里叶变换,计算简单,运行速度快.仿真试验表明,该方法是有效的,对外界环境干扰具有很好的适应性,能够实现轧辊偏心信号的实时动态控制.
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.
出处
《信息与控制》
CSCD
北大核心
2009年第5期532-538,共7页
Information and Control
关键词
二代小波变换
提升算法
轧辊偏心
自寻优
消噪
second generation wavelet transform
lifting algorithm
roller eccentricity
self-optimization
de-noising
