{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:40:10Z","timestamp":1774456810446,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Ministry of Science and Technology, Taiwan, R.O.C.","award":["MOST 109-2221-E-011-075-"],"award-info":[{"award-number":["MOST 109-2221-E-011-075-"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A novel framework of model-based fault detection and identification (MFDI) for induction motor (IM)-driven rotating machinery (RM) is proposed in this study. A data-driven subspace identification (SID) algorithm is employed to obtain the IM state-space model from the voltage and current signals in a quasi-steady-state condition. This study aims to improve the frequency\u2013domain fault detection and identification (FDI) by replacing the current signal with a residual signal where a thresholding method is applied to the residual signal. Through the residual spectrum and threshold comparison, a binary decision is made to find fault signatures in the spectrum. The statistical Q-function is used to generate the fault frequency band to distinguish between the fault signature and the noise signature. The experiment in this study is performed on a wastewater pump in an existing industrial facility to verify the proposed FDI. Two faulty conditions with mathematically known and mathematically unknown faulty signatures are experimented with and diagnosed. The study results present that the residual spectrum demonstrated to be more sensitive to fault signatures compare to the current spectrum. The proposed FDI has successfully shown to identify the fault signatures even for the mathematically unknown faulty signatures.<\/jats:p>","DOI":"10.3390\/s21175865","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:58:15Z","timestamp":1630450695000},"page":"5865","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A Novel Fault Detection and Identification Framework for Rotating Machinery Using Residual Current Spectrum"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3534-6269","authenticated-orcid":false,"given":"Widagdo","family":"Purbowaskito","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan"},{"name":"Department of Industrial Engineering, Universitas Atma Jaya Yogyakarta, Yogyakarta 55281, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7043-5822","authenticated-orcid":false,"given":"Chen-Yang","family":"Lan","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenny","family":"Fuh","sequence":"additional","affiliation":[{"name":"Jhunan Facility Engineering Division Group, Innolux Corporation, Jhunan Science Park, Zhunan 35053, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1842","DOI":"10.1109\/TIE.2006.885131","article-title":"Online Diagnosis of Induction Motors Using MCSA","volume":"53","author":"Jung","year":"2006","journal-title":"IEEE Trans. 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