改进小波降噪算法在轴承缺陷图像的应用.docx

改进小波降噪算法在轴承缺陷图像的应用
Title:ImprovementofWaveletDenoisingAlgorithmforApplicationinBearingFaultImage
Abstract:
Thispaperpresentsanimprovedwaveletdenoisingalgorithmfortheapplicationinbearingfaultimageanalysis.Bearingsplayacrucialroleinthesmoothoperationofvariousmachinery.However,duetolong-termwearandtear,theyarepronetodevelopingfaultsanddefectsthatcansignificantlyimpactthemachine'sperformanceandsafety.Effectivedetectionanddiagnosisofbearingfaultsarecriticalforensuringmachineryreliability.Imageanalysistechniqueshavebeenwidelyusedfordetectinganddiagnosingbearingfaults.Onecommonchallengeinbearingfaultimageanalysisisthepresenceofnoise,whichcandegradetheaccuracyoffaultdetection.Inthispaper,weproposeanenhancedwaveletdenoisingalgorithmtoimprovetheeffectivenessandaccuracyofbearingfaultimageanalysis.
1.Introduction:
1.1Background:
1.2Objectives:
1.3Organization:
2.LiteratureReview:
2.1BearingFaultDetection:
2.2ImageDenoisingTechniques:
2.3WaveletDenoisingAlgorithms:
3.Methodology:
3.1OverviewoftheProposedAlgorithm:
3.2Preprocessing:
3.3WaveletTransform:
3.4Thresholding:
3.5Postprocessing:
4.ExperimentalResults:
4.1DatasetDescription:
4.2PerformanceEvaluationMetrics:
4.3ComparisonwithExistingAlgorithms:
4.4DiscussionofResults:
5.Conclusion:
Inthispaper,wepresentedanimprovedwaveletdenoisingalgorithmfortheapplicationinbearingfaultimageanalysis.Theproposedalgorithmeffectivelyreducednoiseintheimages,therebyenhancingtheaccuracyandreliabilityoffaultdetectioninbearingimages.Experimentalresultsdemonstratedthesuperiorityofouralgorithmcomparedtoexistingstate-of-the-artdenoisingtechniques.Thereliabilityoftheproposedalgorithmmakesitsuitableforpracticalapplicationsinindustry.Futureworkmayfocusonfurtherimprovingthealgorithm'sperformanceandexploringitsapplicationinotherimageanalysistasks.
Keywords:Bearingfaultdetection,Imagedenoising,Wavelettransform,Thresholding,Noisereduction.
1.Introduction
1.1Background
Bearingsarevitalcomponentsinvariousmachineryandequipment,astheyprovidesupportandenablesmo