DECREASING THE AMPLITUDE CHARACTERISTIC DEVIATION OF GAUSSIAN FILTER IN SURFACE ROUGHNESS MEASUREMENTS

XU Jingbo¹  YUAN Yibao¹  PIAO Weiying¹  SONG J F²  VORBURGER T V²

(1. Department of Automation Measurement & Control and Instrumentation, Harbin Institute of Technology, Harbin 150001;

2. National Institute of Standards and Technology, Maryland, USA)

Abstract: 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 carried 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 measurements.

Key words: Gaussian filter  Butterworth filter  Moving average filter  Surface roughness measurement

CLC No: TG84

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和美国国家标准与技术研究院(NIST)资助项目. Received 20050221, received in revised form  20050831