摘要
提出了一种减小表面粗糙度测量用的高斯滤波器幅度传输特性偏差的新方法。根据中心极限定理,可以构造出不同的高斯逼近滤波器。用多级一阶巴特沃思滤波器和多级移动平均滤波器分别去逼近高斯滤波器时,两者的幅度偏差方向相反、极值位置相近,所以这两种方法的线性组合可以大大减小偏差。用这两种不同逼近滤波器的并联方法构成的一个简单的线性组合滤波器,去逼近高斯滤波器的幅度传输特性,其幅度传输特性的最大偏差只有0．11％。这种新的逼近方法,算法简单、精度高,实现了表面测量高斯滤波处理的高精度和高效率的高度统一。
A new approach for decreasing the amplitude characteristic deviation of Gaussian filter in surface roughness measurements is presented. On the basis of the central limit theorem, various kinds of Gaussian approximation filters can be carded out. The cascaded first-order Butterworth filters and the cascaded moving average filters are used respectively to implement the Gaussian filter approximately. Their amplitude characteristic deviation curves are almost equal in their shapes and opposite in their phases, and their locations of extremum are very close to each other. So the linear combination of the two Gaussian approximation filters may reduce the amplitude characteristic deviation greatly. The most amplitude deviation of a simple combination filter consisting of two approximation filters is about 0.11%. This new Gaussian approximation filter is both efficient and accurate for surface roughness measu-rements.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2006年第4期42-46,共5页
Journal of Mechanical Engineering
基金
国家教育部归国留学人员基金国家劳动人事部归国留学人员基金美国国家标准与技术研究院(NIST)资助项目
