基于小波和小波分形的冷连轧机振动识别方法  

Vibration identification technology of tandem cold rolling mills based on wavelet and fractal analysis

作　　者：米凯夫[1] 张杰[1] 曹建国[1] 李洪波[1] 贾生晖[2] 褚玉刚[2] 

机构地区：[1]北京科技大学机械工程学院,北京100083 [2]武汉钢铁(集团)公司,武汉430083

出　　处：《北京科技大学学报》2013年第8期1064-1071,共8页Journal of University of Science and Technology Beijing

摘　　要：针对2180 mm冷连轧机振纹现象的随机性和隐蔽性的特点,基于小波分析和分形理论,系统地研究了能够准确地识别轧机振动的方法.对典型工况下轧机振动信号的分析结果显示,两种方法均能有效地识别轧机振动的现象,为在复杂振动环境下识别振纹振动提供了有效途径,这对于实时监测轧机的运行状况,避免恶性生产事故的发生,进而实现预知轧机振动具有积极的现实意义.Aiming at the randomness and imperceptibility of chatter marks in a 2180 mm tandem cold rolling mill, two methods to identify the vibration of the rolling mill were systematically studied based on wavelet analysis and the fractal theory. Vibration signals from the rolling mill under typical conditions were analyzed by the two methods. The results show that both can effectively identify the vibration of the rolling mill. This paper provides an effective way to identify the chatter vibration in the complex vibration environment. The two methods have practical significance for real-timely monitoring the operation condition of rolling mills, avoiding the occurrence of hazardous production accidents, and then predicting the vibration of rolling mills.

关 键 词：冷轧机 带钢 表面缺陷 机械振动 信号分析 小波分析 分形 

分 类 号：TG333.71[金属学及工艺—金属压力加工]