摘要
为了提高平直度模式识别的精度,引入小波消噪技术对平直度信号进行预处理,然后采用以1次、2次、3次和4次勒让德多项式作为平直度基本模式的基于最小二乘原理的多项式回归方法进行模式识别,提出了一种计算精度高、抗干扰能力强的平直度模式识别方法。该方法能够从本质上提高平直度模式识别的精度,计算过程稳定可靠,能够为平直度控制模型提供准确的平直度信息,适合在线应用。
In order to increase the precision of flatness recognition,a new flatness recognition method is brought forward with high precision and strong anti-jamming ability by the Legendre polynomial regression method based on least square theory.It processes with the original flatness data by wavelet de-noising techniques with linear,quadratic,cubic and biquadratic Legendre orthogonal polynomials as flatness basic patterns.The method can increase the precision of flatness recognition with steady computational process and provide exact flatness information for flatness control model,being fit for on-line applications.
出处
《燕山大学学报》
CAS
2011年第1期23-28,共6页
Journal of Yanshan University
基金
国家高技术研究发展计划(863计划)资助项目(2009AA04Z143)
河北省自然科学基金资助项目(E2006001038)
河北省科技计划资助项目(10212101D)
关键词
平直度
模式识别
最小二乘法
勒让德多项式
小波消噪
flatness
pattern recognition
least square method
Legendre orthogonal polynomials
wavelet de-noising
