基于自适应小波的二十辊轧机轧辊局部缺陷识别研究  

Identification of local defects on the roll surface of a twenty-high roll mill based on the adaptive wavelet

作　　者：吴胜利[1] 邵毅敏[1] 王利明[1] 袁意林 叶维军 

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400030 [2]宁波宝新不锈钢有限公司,宁波315807

出　　处：《振动与冲击》2017年第10期117-120,共4页Journal of Vibration and Shock

基　　金：国家自然基金重点资助项目(51035008)

摘　　要：轧辊在磨削过程中,轧辊表面会产生振纹等局部缺陷,严重影响带钢表面质量,有效识别轧辊缺陷尺寸大小仍是目前轧机诊断存在的难题之一。利用MATLAB小波工具箱构造与信号对应的自适应小波,通过与Haar小波、Morlet小波和试验数据的对比分析,不仅证明了构建自适应小波方法的正确性,而且也验证了自适应小波对轧辊缺陷识别的有效性,为有效识别轧辊缺陷以及分析缺陷尺寸提供了理论基础和实践支撑。Local defects are prone to appear on the surface of roll in grinding process,which seriously affect the quality of the steel strip.The identification of defects and the sizes of defects are still existing difficult problems.The MATLAB wavelet toolbox was used to generate an adaptive wavelet.The a greement between the results of the adaptive wavelet and the Haar,Morlet wavelet and the experimental results validates the effectiveness of the generated adaptive wavelet method.The results also provide a theoretical support for identifying defects on the surface of roll.

关 键 词：轧辊缺陷 自适应小波 识别 

分 类 号：TH165.3[机械工程—机械制造及自动化]