Roller eccentricity signal pick-up and adaptive control based on lifting wavelet transform and self-optimization
-
摘要: 由于基于頻域的經典小波變換運算時間較長,不能很好地滿足軋輥偏心信號在線實時控制的要求,提出了用提升結構小波變換對偏心信號進行不同分辨率下分解處理的新方法.通過對軋制力信號和厚差信號的分析,利用提升和對偶提升原理將偏心信號從干擾信號和噪聲信號中提取出來并通過參數自校正控制實現對軋輥偏心的在線動態控制.仿真結果表明,該方法獲得了比較理想的效果,并且在同樣數據長度下,提升小波變換運算速度比經典小波變換至少提高1倍以上.Abstract: 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.
-

計量
- 文章訪問數: 294
- HTML全文瀏覽量: 89
- PDF下載量: 5
- 被引次數: 0