Publication:
Estimating average power of welding process with emitted noises based on adaptive neuro fuzzy inference system

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dc.contributor.authorGÖKMEN, GÖKHAN
dc.contributor.authorKIYAK, İSMAİL
dc.contributor.authorsGÖKMEN G., Akıncı T. Ç., Kocyigit G., KIYAK İ., Akbas M. I.
dc.date.accessioned2023-05-15T11:19:44Z
dc.date.accessioned2026-01-11T18:01:39Z
dc.date.available2023-05-15T11:19:44Z
dc.date.issued2023-01-01
dc.description.abstractIn this study, the average power consumption of an electrode welding machine during the welding process was estimated using the features of the sound emitted during welding. First, the instantaneous values of electrode current and voltage and the sound emitted during the welding process were recorded simultaneously. The minimum, maximum, average, root mean square (RMS), and energy values of the sound data were found and feature extraction was performed, and the instantaneous power and average power values were calculated using the instantaneous current and voltage values. Three Adaptive Neuro-Fuzzy Inference Systems (ANFIS) using the sound features as inputs and average power values as outputs were created, and their results were compared. The average power values consumed during the welding process have been successfully estimated at a rate of 87-95%.
dc.identifier.citationGÖKMEN G., Akıncı T. Ç., Kocyigit G., KIYAK İ., Akbas M. I., "Estimating Average Power of Welding Process With Emitted Noises Based on Adaptive Neuro Fuzzy Inference System", IEEE Access, cilt.11, ss.39154-39164, 2023
dc.identifier.doi10.1109/access.2023.3268525
dc.identifier.endpage39164
dc.identifier.issn2169-3536
dc.identifier.startpage39154
dc.identifier.urihttps://avesis.marmara.edu.tr/api/publication/1740f613-a8a4-4fbc-8a52-077917026844/file
dc.identifier.urihttps://hdl.handle.net/11424/289350
dc.identifier.volume11
dc.language.isoeng
dc.relation.ispartofIEEE Access
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectBilgisayar Bilimleri
dc.subjectMühendislik ve Teknoloji
dc.subjectInformation Systems, Communication and Control Engineering
dc.subjectSignal Processing
dc.subjectComputer Sciences
dc.subjectEngineering and Technology
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectMühendislik
dc.subjectMalzeme Bilimi
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectCOMPUTER SCIENCE
dc.subjectENGINEERING
dc.subjectMATERIALS SCIENCE
dc.subjectENGINEERING, ELECTRICAL & ELECTRONIC
dc.subjectGenel Bilgisayar Bilimi
dc.subjectFizik Bilimleri
dc.subjectGenel Malzeme Bilimi
dc.subjectGenel Mühendislik
dc.subjectElektrik ve Elektronik Mühendisliği
dc.subjectGeneral Computer Science
dc.subjectPhysical Sciences
dc.subjectGeneral Materials Science
dc.subjectGeneral Engineering
dc.subjectElectrical and Electronic Engineering
dc.subjectWelding
dc.subjectElectrodes
dc.subjectArtificial intelligence
dc.subjectWires
dc.subjectFuzzy logic
dc.subjectTungsten
dc.subjectHelium
dc.subjectData acquisition
dc.subjectWelters
dc.subjectaverage power
dc.subjectemitted noise
dc.subjectneuro-fuzzy inference
dc.subjectdata acquisition
dc.titleEstimating average power of welding process with emitted noises based on adaptive neuro fuzzy inference system
dc.typearticle
dspace.entity.typePublication

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