Recent advances in separation of roughness, waviness and form

Engineering surfaces are comprised of a range of spatial wavelengths. Filtering techniques are commonly adopted to separate the different wavelength components into well-defined bandwidths. Filtering is done prior to numerical characterization and it is also essential for extracting information need...

Full description

Saved in:
Bibliographic Details
Published inPrecision engineering Vol. 26; no. 2; pp. 222 - 235
Main Authors Raja, J., Muralikrishnan, B., Fu, Shengyu
Format Journal Article
LanguageEnglish
Published New York, NY Elsevier Inc 01.04.2002
Elsevier Science
Subjects
Applied sciences
Bandwidth
Correlation methods
Digital filters
Exact sciences and technology
Filters
Frequencies
Industrial metrology. Testing
Mechanical engineering. Machine design
Morphology
Process control
Roughness
Surface measurement
Surface metrology
Waviness
Filters
Surface metrology
Waviness
Roughness
Wavy surface
Image processing
Wavelet transformation
Filter
Numerical method
Rough surface
Profilometry
Texture
Spline approximation
Online AccessGet full text

Cover

More Information
Summary:Engineering surfaces are comprised of a range of spatial wavelengths. Filtering techniques are commonly adopted to separate the different wavelength components into well-defined bandwidths. Filtering is done prior to numerical characterization and it is also essential for extracting information needed to provide process feedback and establish functional correlation. This paper reviews commonly used filters in surface metrology like the 2RC, Gaussian and several new ones currently under research such as the spline, morphological, wavelets, regression filters and robust regression filters. The need for these new filters and examples illustrating the features of these filters are also presented.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0141-6359
1873-2372
DOI:10.1016/S0141-6359(02)00103-4