Yayın:
Fault detection of washing machine with discrete wavelet methods

Basit öğe sayfası
dc.contributor.authorAkıncı, Tahir Çetin
dc.contributor.authorKarabeyoğlu, Sencer Süreyya
dc.contributor.authorYılmaz, Özgür
dc.contributor.authorŞeker, Serhat
dc.contributor.ituauthorAkıncı, Tahir Çetin
dc.date.accessioned2026-01-26T02:52:25Z
dc.date.issued2014-04-14
dc.description.abstractIn the last decade, a new mathematical method has allowed scientists and engineers to view the details of time varying and transient phenomena that are not possible through conventional tools. This invention, called wavelet transform, has created revolutionary changes in the areas of signal processing, and image compression. In this study, both properly working and fault washing machine is distinguished by using discrete wavelet analysis and statistical analysis. The result of statistical analysis to distinguish the properties of both machines has been quite successful .Based on the analysis, particular energy levels are important to distinguish the machines. All the dynamics and control of electrical machines and analysis is necessary for effective control. In the study vibration dynamics of the washing machine was analyzed. DOI: http://dx.doi.org/10.5755/j01.mech.20.2.6943
dc.description.urihttps://doi.org/10.5755/j01.mech.20.2.6943
dc.description.urihttps://dx.doi.org/10.60692/qn9rg-wj178
dc.description.urihttps://dx.doi.org/10.60692/srw9q-gtj85
dc.description.urihttps://dx.doi.org/10.5755/j01.mech.20.2.6943
dc.description.urihttps://hdl.handle.net/20.500.11857/3508
dc.identifier.doi10.5755/j01.mech.20.2.6943
dc.identifier.eissn2029-6983
dc.identifier.endpage182
dc.identifier.issn1392-1207
dc.identifier.openairedoi_dedup___::cbcf4f1c8777bc5c9ed25f1303d34332
dc.identifier.orcid0000-0002-4657-6617
dc.identifier.orcid0000-0001-8253-6412
dc.identifier.orcid0000-0002-1122-4558
dc.identifier.startpage177
dc.identifier.urihttps://hdl.handle.net/11527/58206
dc.identifier.volume20
dc.publisherKaunas University of Technology (KTU)
dc.relation.ispartofMechanics
dc.rightsOPEN
dc.sdg.typeGoal 3: Good Health and Well-being
dc.subjectSignal processing
dc.subjectArtificial intelligence
dc.subjectMachine Fault Diagnosis and Prognostics
dc.subjectdata analysis
dc.subjectPattern recognition (psychology)
dc.subjectVibration
dc.subjectAnalytical Chemistry
dc.subjectFault (geology)
dc.subjectEngineering
dc.subjectFOS: Chemical sciences
dc.subjectActuator
dc.subjectFOS: Mathematics
dc.subjectwashing machine
dc.subjectSeismology
dc.subjectdiscrete wavelet analysis
dc.subjectTransient (computer programming)
dc.subjectElectronic engineering
dc.subjectControl engineering
dc.subjectPhysics
dc.subjectStatistics
dc.subjectGeology
dc.subjectAcoustics
dc.subjectFOS: Earth and related environmental sciences
dc.subjectChemometrics in Analytical Chemistry and Food Technology
dc.subjectFault Diagnosis
dc.subjectDigital signal processing
dc.subjectComputer science
dc.subjectChemistry
dc.subjectOperating system
dc.subjectControl and Systems Engineering
dc.subjectStatistical analysis
dc.subjectPhysical Sciences
dc.subjectComputer Science
dc.subjectDiscrete wavelet transform
dc.subjectFault detection and isolation
dc.subjectWavelet transform
dc.subjectComputer Vision and Pattern Recognition
dc.subjectvibration
dc.subjectImage Denoising Techniques and Algorithms
dc.subjectEnergy (signal processing)
dc.subjectWavelet
dc.subjectMathematics
dc.titleFault detection of washing machine with discrete wavelet methods
dc.typeOther
dspace.entity.typePublication
person.identifier.orcid0000-0002-4657-6617

Dosyalar

Koleksiyonlar

Yayınlar