{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T02:27:37Z","timestamp":1783132057049,"version":"3.54.6"},"reference-count":96,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo (ANID)\u2013Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","award":["11251490"],"award-info":[{"award-number":["11251490"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3655166","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T21:00:02Z","timestamp":1769202002000},"page":"13098-13112","source":"Crossref","is-referenced-by-count":1,"title":["Integrating DWT and Bayesian Neural Networks for Effective Bearing Fault Detection With Uncertainty Evaluation in Induction Machines"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3187-3253","authenticated-orcid":false,"given":"Johnny","family":"Rengifo","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Campus San Joaqu&#x00ED;n, Universidad T&#x00E9;cnica Federico Santa Mar&#x00ED;a, Santiago, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reynaldo","family":"Garc\u00eda-Aguiar","sequence":"additional","affiliation":[{"name":"Departamento de Converis&#x00F3;n y Transporte de Energ&#x00CD;a, Universidad Sim&#x00F3;n Bol&#x00CD;var, Caracas, Venezuela"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4704-1067","authenticated-orcid":false,"given":"Jose M.","family":"Aller","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Universidad Polit&#x00E9;cnica Salesiana, Cuenca, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1787\/caf32f3b-en"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.118684"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2375853"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2019.2905821"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3092605"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3090473"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2024.105694"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2022.3167632"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2023.3245186"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2024.3409768"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1002\/9780470977668.ch2"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10377-8_13"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.joi.2016.10.006"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2018.09.013"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3089251"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3177735"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3066489"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3274696"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.12.010"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3005422"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3380438"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TEC.2023.3338447"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s40684-025-00748-7"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105919"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2018.08.010"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-32369-y"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ECCE.2018.8557651"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2024.3408058"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2025.111057"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2025.3551823"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2948202"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3139706"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/APARM49247.2020.9209470"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICPHM51084.2021.9486569"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2014.11.062"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2010.2095391"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2021.108572"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IECON49645.2022.9969003"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/DEMPED.2015.7303681"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3177233"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2017.06.022"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.05.008"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00302"},{"issue":"1","key":"ref44","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref45","first-page":"1613","article-title":"Weight uncertainty in neural network","volume-title":"Proc. 32nd Int. Conf. Mach. Learn.","author":"Blundell"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.09.005"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2022.3155327"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.3390\/en15020453"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.3390\/en12112105"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICEES51510.2021.9383729"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TEC.2005.847955"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2010.2090839"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-0624-1_9"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/2943.930988"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2006.885131"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2008.921431"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1049\/PBPO120E_ch6"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TEC.2004.837304"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3200058"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1049\/ip-b.1986.0022"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2017.2691736"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CMD.2018.8535744"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2004.1383462"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2008.2007527"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/b978-0-12-374370-1.x0001-8"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2002.802988"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/b978-0-12-374370-1.x0001-8"},{"issue":"2","key":"ref68","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1111\/joes.12012","article-title":"The continuous wavelet transform: A primer","volume":"28","author":"Aguiar-Conraria","year":"2014","journal-title":"J. Econ. Surv."},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.5772\/649"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1117\/12.160487"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1002\/0470841834"},{"key":"ref72","first-page":"894","article-title":"Wavelet coefficients energy redistribution and Heisenberg principle of uncertainty","volume-title":"Proc. Math. Methods Econ.","author":"Vo\u0161vrda"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.06.100"},{"key":"ref74","article-title":"Wavelet theory and applications: A literature study","author":"Merry","year":"2005"},{"key":"ref75","volume-title":"Probabilistic Deep Learning: With Python, Keras and Tensorflow Probability","author":"D\u00fcrr","year":"2020"},{"key":"ref76","article-title":"Uncertainty estimation in Bayesian neural networks and links to interpretability","author":"Chai","year":"2018"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2023.109049"},{"key":"ref78","volume-title":"Case Western Reserve University Bearing Data Center Website","year":"2025"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-023-08459-3"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.12.051"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1145\/1543834.1543860"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3284922"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2010.07.018"},{"key":"ref84","first-page":"1050","article-title":"Dropout as a Bayesian approximation: Representing model uncertainty in deep learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gal"},{"issue":"1","key":"ref85","first-page":"6765","article-title":"Hyperband: A novel bandit-based approach to hyperparameter optimization","volume":"18","author":"Li","year":"2017","journal-title":"J. Mach. Learn. Res."},{"key":"ref86","volume-title":"Kerastuner","author":"O\u2019Malley","year":"2019"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.4135\/9781412983907.n1717"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60032-7_3"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10562-9"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2022.111902"},{"key":"ref91","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/978-3-030-57077-4_10","volume-title":"Programming With Tensorflow: Solution for Edge Computing Applications","author":"Imambi","year":"2021"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3169217"},{"key":"ref94","first-page":"22","article-title":"Uncertainty quantification using Bayesian neural networks in classification: Application to ischemic stroke lesion segmentation","author":"Kwon","year":"2018","journal-title":"Med. Imag. with Deep Learn."},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3123300"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2025.3529048"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11357934.pdf?arnumber=11357934","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:25:29Z","timestamp":1769721929000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11357934\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":96,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3655166","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}