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Seyfollah Soleimani

Seyfollah Soleimani

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-5541-8768
Education: PhD.
ScopusId: 36740004600
HIndex:
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
Quantifying abrasion and micro-pits in polymer wear using image processing techniques
Type
JournalPaper
Keywords
Quantifying abrasion and pitting Microscopy Segmentation, Granulometry, Partially blurred images, Uneven illumination
Year
2014
Journal Wear
DOI
Researchers Seyfollah Soleimani

Abstract

Identifying wearmechanismsfromwornsurfacesisacomplexandtediousprocessinvolvinghigh expertise.Wearscarsfromthecontactsurfacescanactasapotentialindicatorofwearprocess undergone bythematerialduringthecourseofsurfaceinteraction.Currently,wearmechanismanalysis is performedsubjectivelyandusuallyonlybytheauthor(s)ofthestudy.Theaimofthispaperisto develop imageprocessingtechniquestoquantifytwowearmechanisms:abrasionandmicro-pitting.To characterizewearmechanisms,therequiredsurfacemorphologywasproducedusingweartestingof polymer inatwin-disctestrig.Themicrographsofpolymercontactsurfaceswereacquiredusinga conventionalopticalmicroscope.Subjectivequalityscoreswerecollectedbyastructuredhuman observer studytoquantifytheseverityofmicropittingandabrasion.Thesescoreswereusedtovalidate objectivescoresobtainedusingimageprocessingtechniques.Severalimageprocessingtechniquesare proposed todetectandquantifymicro-pittingandabrasionmechanisms.Thesetechniquesconsistof localandglobalthresholdingsegmentationwithandwithoutunevenilluminationcompensation, granulometrybybinaryopeningandgranulometrybygray-scaleclosing.Theproposedimageprocessing analysisrevealstheseverityofabrasionandpittingmechanisms(whentheyaredominant)whichagree wellwiththemeanopinionscores(MOS)givenbyobservers.Forabrasion,thecorrelationcoefficients betweenobjectivescoresobtainedbydifferentimageprocessingtechniquesandsubjectivevaluesshowa highlinearcorrelation.Forpitting,weclaimthatobjectivevaluesobtainedfromthenewmethods, distinguishthepittingmechanism.Thisstudyisaproofofconcepttowardsautomatedidentificationand quantificationofdifferentwearmechanismsasareplacementforhumanobservers.