{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T07:20:59Z","timestamp":1725866459154},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002367","name":"Key Laboratory of Space Utilization, Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["Y3140611PN"],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tim.2020.3009343","type":"journal-article","created":{"date-parts":[[2020,7,20]],"date-time":"2020-07-20T20:54:12Z","timestamp":1595278452000},"page":"1-17","source":"Crossref","is-referenced-by-count":58,"title":["A Novel Method for Imbalanced Fault Diagnosis of Rotating Machinery Based on Generative Adversarial Networks"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-4964-9276","authenticated-orcid":false,"given":"Zhenxiang","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2418-0520","authenticated-orcid":false,"given":"Taisheng","family":"Zheng","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9365-9223","authenticated-orcid":false,"given":"Yang","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4726-6047","authenticated-orcid":false,"given":"Zhi","family":"Cao","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-7948-3521","authenticated-orcid":false,"given":"Zhiqi","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5095-9477","authenticated-orcid":false,"given":"Hongyong","family":"Fu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2013.12.003"},{"key":"ref32","year":"0","journal-title":"2009 PHM Challenge Dataset"},{"key":"ref31","year":"0","journal-title":"Case Western Reserve University Bearing Data Center Website"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2016.06.024"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2751612"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2018.04.005"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref14","first-page":"634","article-title":"A distance-based over-sampling method for learning from imbalanced data sets","author":"de la calleja","year":"2007","journal-title":"Proc FLAIRS Conf"},{"key":"ref15","first-page":"1322","article-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning","volume":"1","author":"he","year":"2008","journal-title":"Proc IEEE Int Joint Conference Neural Netw (IEEE World Congr Comput Intell )"},{"key":"ref16","first-page":"15","article-title":"Fisher linear discriminant model with class imbalance","volume":"30","author":"xie","year":"2006","journal-title":"J Beijing Jiaotong Univ"},{"key":"ref17","first-page":"1883","article-title":"Pruning support vectors for imbalanced data classification","author":"chen","year":"2005","journal-title":"Proc IEEE Int Joint Conf Neural Netw"},{"key":"ref18","first-page":"2672","article-title":"Generative adversarial networks","volume":"3","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","article-title":"Wasserstein GAN","author":"arjovsky","year":"2017","journal-title":"arXiv 1701 07875"},{"key":"ref28","article-title":"Towards principled methods for training generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"arXiv 1701 04862"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2903615"},{"key":"ref27","first-page":"2234","article-title":"Improved techniques for training GANs","author":"salimans","year":"2016","journal-title":"Proc 30th Conf Neural Inf Process Syst (NIPS)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1006\/mssp.2001.1462"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2018.2806984"},{"key":"ref29","first-page":"5767","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc 31st Conf Neural Inf Process Syst (NIPS)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2016.2564078"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2798633"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2017.06.022"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2017.2698738"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2018.03.025"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.07.019"},{"key":"ref20","article-title":"Conditional image synthesis with auxiliary classifier GANs","author":"odena","year":"2016","journal-title":"arXiv 1610 09585"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.23919\/ECC.2018.8550560"},{"key":"ref21","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"2015","journal-title":"arXiv 1511 06434"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.024"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.23919\/ChiCC.2018.8483334"},{"key":"ref26","article-title":"Improved generator objectives for GANs","author":"poole","year":"2016","journal-title":"arXiv 1612 02780"},{"key":"ref25","article-title":"Unrolled generative adversarial networks","author":"metz","year":"2016","journal-title":"arXiv 1611 02163"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/9259274\/09144241.pdf?arnumber=9144241","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:51:31Z","timestamp":1652194291000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9144241\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/tim.2020.3009343","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"value":"0018-9456","type":"print"},{"value":"1557-9662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}