ISO 16610

ISO 16610: Geometrical product specifications (GPS) – Filtration is a standard series on filters for surface texture, and provides guidance on the use of these filters in various applications. Filters are used in surface texture in order reduce the bandwidth of analysis in order to obtain functional correlation with physical phenomena such as friction, wear, adhesion, etc. For example, filters are used to separate roughness and waviness from the primary profile, or to create a multiscale decomposition in order to identify the scale at which a phenomenon occurs. Historically, the first roughness measuring instruments - stylus profilometer - used to have electronic filters made of capacitors and resistors that filtered out low frequencies in order to retain frequencies that represent roughness. Later, digital filters replaced analog filters and international standards such as ISO 11562 for the Gaussian filter were published.

Filter toolbox for surface texture

Today, a full set of filters is described in the ISO 16610 standard series. This standard is part of the GPS standards on Geometrical Product Specification and Verification, developed by ISO TC 213.

Filter matrix

ISO 16610 is composed of two families of documents, one for profiles (open and closed) and one for surfaces. A general introduction is provided in:

  • ISO 16610-1: Overview and basic concepts (published in 2015)

Profile filters

Profile filters are defined for open profiles, measured along a line by profilometers and expressed as z=f(x), as well as for closed profiles, measured around a circular component by roundness instruments and expressed as radius=f(angle). Most of these standards were first published as a Technical Specification (TS) and later converted to International Standards or withdrawn.

Parts related to profile filters are:

  • ISO 16610-20: Linear profile filters: Basic concepts (published in 2015)
  • ISO 16610-21: Linear profile filters: Gaussian filters (published in 2011)
  • ISO 16610-22: Linear profile filters: Spline filters (published in 2015)
  • ISO 16610-28: Linear profile filters: End effects (published in 2016)
  • ISO 16610-29: Linear profile filters: Spline wavelets (published in 2015)
  • ISO 16610-30: Robust profile filters: Basic concepts (published in 2015)
  • ISO 16610-31: Robust profile filters: Gaussian regression filters (published in 2016)
  • ISO 16610-32: Robust profile filters: Spline filters (published as a TS in 2009)
  • ISO 16610-40: Morphological profile filters: Basic concepts (published in 2015)
  • ISO 16610-41: Morphological profile filters: Disc and horizontal line-segment filters (published in 2015)
  • ISO 16610-45: Morphological profile filters: Segmentation filters (planned for the future)
  • ISO 16610-49: Morphological profile filters: Scale space techniques (published in 2015)

Note: ISO/TS 16610-32 on robust spline filters was published as a technical specification in 2009 but was withdrawn in 2015 as it provides very similar results as the Robust Gaussian regression filter while being much more complex.

Areal filters

Areal filters are defined for surfaces measured either by lateral scanning instruments or optical profilometers. Parts related to areal filters are:

  • ISO 16610-60: Linear areal filter: Basic concepts (published in 2015)
  • ISO 16610-61: Linear areal filter: Gaussian filters (published in 2015)
  • ISO 16610-62: Linear areal filter: Spline filters
  • ISO 16610-68: Linear areal filter: End-effects (planned for the future)
  • ISO 16610-69: Linear areal filter: Spline wavelets
  • ISO 16610-70: Robust areal filter: Basic concepts
  • ISO 16610-71: Robust areal filter: Gaussian regression filters (published in 2014)
  • ISO 16610-80: Morphological areal filter: Basic concepts
  • ISO 16610-81: Morphological areal filter: Sphere and horizontal planar segment filters
  • ISO 16610-85: Morphological areal filter: Segmentation (published in 2013)
  • ISO 16610-89: Morphological areal filter: Scale space techniques

Guide for the use of filters in surface texture

The following section describes which application is suitable for each filter. References to published papers or books are provided when available. Readers are encouraged to add below proven applications related to surface texture and tribology where a particular filter can be used alone or in conjunction with other treatments or analyses to provide significant results.

Part 21 - Profile Gaussian filter
  • Microroughness filtering (lambda S)
  • Separation of roughness and waviness profiles (lambda C)
  • Band-pass filtering
Part 22 - Profile Spline filter
Part 29 - Profile Spline wavelets
Part 31 - Profile Robust Gaussian filter
Part 41 - Profile Morphological filter
Part 45 - Profile Segmentation filter
Part 49 - Profile Scale space technique
Part 61 - Areal Gaussian filter
  • Microroughness S-Filter
  • L-Filter for the generation of the roughness S-L surface
Part 62 - Areal Spline filter
Part 71 - Areal Robust regression Gaussian filter
  • Microroughness S-Filter on stratified and structured surfaces
  • L-Filter for the generation of the roughness S-L surface on stratified and structured surfaces
  • F-Filter for the generation of S-F surface
  • Outlier detection
Part 81 - Areal Morphological filter
  • F-Filter used to flatten a surface with the upper or lower envelope
  • Tip deconvolution of AFM instrument
Part 85 - Areal Segmentation filter
  • Identification of structures (grains, pores, cells, ...)
  • Automatic leveling of MEMS
Part 89 - Areal Scale space technique

See also

Bibliography
  • BAKUCZ P, 2013, Spline filtering in accordance to ISO/TS 16610: ANSI C-code for engineers, 8th IEEE conf. on applied comput. intel. informatics
  • BAKUCZ P, KRÜGER-SEHM R, 2009, A new wavelet filtering for analysis of fractal engineering surfaces, Wear
  • BLATEYRON F, 2014, Good practices for the use of areal filters, 3rd Seminar on surface metrology of the Americas, Albuquerque.
  • BRINKMANN S, BODSCHWINNA H, LEMKE H W, 2001, Accessing roughness in three-dimensions using Gaussian regression filtering, Int. J of mach. tools manuf.
  • DEMIRCI I, MEZGHANI S, YOUSFI M, EL MANSORI M, 2013, Multiscale analysis of the roughness effect on lubricated rough contact, J of tribology
  • DOBRZANSKI P, PAWLUS P, 2010, Digital filtering of surface topography: part II, applications of robust and valley suppression filters, Prec. eng., 01/2010
  • FRIIS K S, GODI A, DE CHIFFRE L, 2011, Characterization and robust filtering of multifunctional surfaces using ISO standards, Meas. sci. technol. 22 125101
  • GOTO T, MIYAKURA J, UMEDA K, KADOWAKI S, 2005, A robust spline filter on the basis of L2-norm, Prec. eng.
  • GURAU L, IRLE M, MANSFIELD-WILLIAMS H, 2013, Minimising the computation time of using a robust Gaussian regression filter on sanded wood surfaces, Pro Ligno, 8(3):3-11
  • HANADA H, SAITO T, HASEGAWA M, YANAGI K, 2008, Sophisticated filtration technique for 3D surface topography data of rectangular area, Wear, 264(5):422-427
  • JIANG X, SCOTT P J, WHITEHOUSE D, 2008, Wavelets and their applications for surface metrology, CIRP Annals manuf. tech., 57:555-558
  • KONDO Y, NUMADA M, KOSHIMIZU H, 2014, A robust Gaussian filter corresponding to the transmission characteristic of the Gaussian filter, J of physics conf. series, 483(1):012016.
  • KRYSTEK M, 2010, ISO filters in precision engineering and production measurement, Meas. sci. technol.
  • KRYSTEK M, 2005, Spline filters for surface texture analysis, Key eng. materials
  • KRYSTEK M, 1996, A fast gauss filtering algorithm for roughness measurements, Prec. eng.
  • KUMAR J, SHUNMUGAM M S, 2006, A new approach for filtering surface profiles using morphological operations, Int. J of mach. tools manuf., 46(3):260-270
  • LI H, JIANG X, LI Z, 2004, Robust estimation in Gaussian filtering for engineering surface characterization, Prec. eng. 28(2):186-193
  • LINGADURAI K, SHUNMUGAM M S, 2006, Metrological characteristics of wavelet filters used for engineering surfaces, Measurements
  • LINGADURAI K, SHUNMUGAM M S, 2005, Use of morphological closing filters for three-dimensional filtering of engineering surfaces, J of manuf. syst., 24(4):366-376
  • LIU X, RAJA J, 1996, Analyzing engineering surface texture using wavelet filter, Proc. SPIE
  • LOU S, JIANG X, SCOTT P J, 2013, Correlating motif analysis and morphological filters for surface texture analysis, Measurement, 46(2):993-1001, ISSN 0263-2241
  • LOU S, JIANG X, SCOTT P J, 2012, Algorithms for morphological profile filters and their comparison, Prec. Eng., 36(3):414-423
  • MURALIKRISHNAN B, REN W, STANFIELD E, EVERETT D, ZHENG A, DOIRON T, 2013, Applications of profile filtering in the dimensional metrology of fuel cell plates, Meas. sci. technol. 24 065003
  • NUMADA M, NOMURA T, YANAGI K, KAMIYAMA K, TASHIRO H, 2007, High-order spline filter and ideal low-pass filter at the limit of its order, Prec. eng.
  • PODULKA P, PAWLUS P, DOBRZANSKI P, LENART A, 2014, Spikes removal in surface measurement, J of physics conf. series, 483(1):012025
  • RAJA J, MURALIKRISHNAN B, FU S, 2002, Recent advances in separation of roughness, waviness and form, Prec. eng.
  • SEEWIG J, EIFER M, 2014, Periodic Gaussian filter according to ISO 16610-21 for closed profiles, Prec. Eng. 38(2):439-442.
  • SEEWIG J, 2005, Linear and robust Gaussian regression filters, J of physics conf. series, 13(1):254
  • THOLATH J, RADHAKRISHNAN V, 1999, Three-dimensional filtering of engineering surfaces using envelope system, Prec. eng., 23:221-228
  • VERMEULEN M, SCHEERS J, 2000, Robust filtering applied to sheet metal surfaces, Xth Int. coll. on surfaces, Chemnitz
  • VOLK R, VILLE J-F, 2007, Filters for contour measurement, Wear, 264(5):469-473
  • XIN B, 2009, Multiscale analysis of rough groove textures for three-dimensional optical measurements, Opt. eng., 48(7)
  • YUAN Y, VORBURGER T V, SONG J F, RENEGAR T B, 2000, A simplified realization for the Gaussian filter in surface metrology, Xth Int. coll. on surfaces, Chemnitz
  • ZELELEW H, KHASAWNEH M, ABBAS A, 2014, Wavelet-based characterization of asphalt pavement surface macro-structure, Road materials and pavement design, 15(3)
  • ZENG W, JIANG X, SCOTT P J, 2011, A generalised linear and nonlinear spline filter, Wear, 271:544-547
  • ZENG H, JIANG X, SCOTT P J, 2010, Fast algorithm of the robust Gaussian regression filter for areal surface analysis, Meas. sci. technol., 21(5):055108tech., 59(1):573-576
  • ZHANG H, YUAN Y, HUA J, CHENG Y, 2014, High-order spline filter: design and application to surface metrology, Prec. eng.
  • ZHANG H, YUAN Y, PIAO W A, 2010, Universal spline filter for surface metrology, Measurement, 43(10):1575-1582
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.