Roundness Filtration by Using a Robust Regression Filter

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

In roundness measurement, filtration is a basic step before the evaluation of the roundness deviation parameters. Currently the widely used phase-correct 2RC and Gaussian filters are not robust against measurement outliers. This paper introduces a robust roundness filtration technology which is based on the robust Gaussian regression filter. Mathematical solution and its algorithms calculated in time and frequency domains are both presented. Both simulated and practical roundness profile data have been used to test the speed and accuracy of the algorithm. Results show that with the proposed robust algorithm, the outlier's influence on the roundness deviation parameters can be reduced significantly, while still keeping the similar transmission characteristics with the standard Gaussian filter very well. Also, the difference between the results of the two presented algorithms is very tiny and negligible.

LanguageEnglish
Article number035108
JournalMeasurement Science and Technology
Volume22
Issue number3
DOIs
Publication statusPublished - 15 Feb 2011

Fingerprint

Filters (for fluids)
Roundness
Robust Regression
Filtration
regression analysis
Filter
filters
Gaussian Filter
Outlier
deviation
Deviation
Robust Algorithm
Frequency Domain
Time Domain
Regression
evaluation
profiles
Evaluation

Cite this

@article{06190423e7534b12b121aa8f467e2fb5,
title = "Roundness Filtration by Using a Robust Regression Filter",
abstract = "In roundness measurement, filtration is a basic step before the evaluation of the roundness deviation parameters. Currently the widely used phase-correct 2RC and Gaussian filters are not robust against measurement outliers. This paper introduces a robust roundness filtration technology which is based on the robust Gaussian regression filter. Mathematical solution and its algorithms calculated in time and frequency domains are both presented. Both simulated and practical roundness profile data have been used to test the speed and accuracy of the algorithm. Results show that with the proposed robust algorithm, the outlier's influence on the roundness deviation parameters can be reduced significantly, while still keeping the similar transmission characteristics with the standard Gaussian filter very well. Also, the difference between the results of the two presented algorithms is very tiny and negligible.",
keywords = "Fast Algorithm, Robust Regression Filter, Roundness",
author = "W. Zeng and Scott, {P. J.} and Xiangqian Jiang",
year = "2011",
month = "2",
day = "15",
doi = "10.1088/0957-0233/22/3/035108",
language = "English",
volume = "22",
journal = "Measurement Science and Technology",
issn = "0957-0233",
publisher = "IOP Publishing",
number = "3",

}

Roundness Filtration by Using a Robust Regression Filter. / Zeng, W.; Scott, P. J.; Jiang, Xiangqian.

In: Measurement Science and Technology, Vol. 22, No. 3, 035108, 15.02.2011.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Roundness Filtration by Using a Robust Regression Filter

AU - Zeng, W.

AU - Scott, P. J.

AU - Jiang, Xiangqian

PY - 2011/2/15

Y1 - 2011/2/15

N2 - In roundness measurement, filtration is a basic step before the evaluation of the roundness deviation parameters. Currently the widely used phase-correct 2RC and Gaussian filters are not robust against measurement outliers. This paper introduces a robust roundness filtration technology which is based on the robust Gaussian regression filter. Mathematical solution and its algorithms calculated in time and frequency domains are both presented. Both simulated and practical roundness profile data have been used to test the speed and accuracy of the algorithm. Results show that with the proposed robust algorithm, the outlier's influence on the roundness deviation parameters can be reduced significantly, while still keeping the similar transmission characteristics with the standard Gaussian filter very well. Also, the difference between the results of the two presented algorithms is very tiny and negligible.

AB - In roundness measurement, filtration is a basic step before the evaluation of the roundness deviation parameters. Currently the widely used phase-correct 2RC and Gaussian filters are not robust against measurement outliers. This paper introduces a robust roundness filtration technology which is based on the robust Gaussian regression filter. Mathematical solution and its algorithms calculated in time and frequency domains are both presented. Both simulated and practical roundness profile data have been used to test the speed and accuracy of the algorithm. Results show that with the proposed robust algorithm, the outlier's influence on the roundness deviation parameters can be reduced significantly, while still keeping the similar transmission characteristics with the standard Gaussian filter very well. Also, the difference between the results of the two presented algorithms is very tiny and negligible.

KW - Fast Algorithm

KW - Robust Regression Filter

KW - Roundness

UR - http://www.scopus.com/inward/record.url?scp=79951923092&partnerID=8YFLogxK

U2 - 10.1088/0957-0233/22/3/035108

DO - 10.1088/0957-0233/22/3/035108

M3 - Article

VL - 22

JO - Measurement Science and Technology

T2 - Measurement Science and Technology

JF - Measurement Science and Technology

SN - 0957-0233

IS - 3

M1 - 035108

ER -