Online algorithm with memory range for identification of roll eccentricity
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摘要: 軋制控制過程中軋輥偏心信號是影響帶鋼厚度精度的重要因素.針對該類問題,將基于設定記憶長度的在線反向傳播算法用于對偏心信號的檢測.通過與普通在線反向傳播算法在檢測性能上的對比表明:該方法具有學習收斂速度快,抗噪聲能力強等特點,可有效使變幅、變相和變頻的偏心信號引起的厚度波動減少95%左右,從而準確地補償由偏心信號引起的厚度偏差,提高軋鋼過程中的帶鋼厚度精度.Abstract: Roll eccentricity in rolling mills has an important influence on the delivery gauge of rolled strips. An online back propagation algorithm with memory range was used to identify roll eccentricity and compared with the simple online back propagation algorithm on identification. The results show that the roll eccentricity identification method with memory range has a faster convergence and a better anti-noise performance. It can make the thickness fluctuation decrease about 95 96 when the eccentricity's magnitude, phase and frequency change, consequently compensate thickness error induced by roll eccentricity and improve the delivery gauge of rolled strips effectively.
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Key words:
- roll eccentricity /
- online detection /
- memory range /
- back propagation algorithm
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