{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T08:01:45Z","timestamp":1774339305687,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,26]],"date-time":"2023-02-26T00:00:00Z","timestamp":1677369600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Asynchronous motors represent a large percentage of motors used in the electrical industry. Suitable predictive maintenance techniques are strongly required when these motors are critical in their operations. Continuous non-invasive monitoring techniques can be investigated to avoid the disconnection of the motors under test and service interruption. This paper proposes an innovative predictive monitoring system based on the online sweep frequency response analysis (SFRA) technique. The testing system applies variable frequency sinusoidal signals to the motors and then acquires and processes the applied and response signals in the frequency domain. In the literature, SFRA has been applied to power transformers and electric motors switched off and disconnected from the main grid. The approach described in this work is innovative. Coupling circuits allow for the injection and acquisition of the signals, while grids feed the motors. A comparison between the transfer functions (TFs) of healthy motors and those with slight damage was performed with a batch of 1.5 kW, four-pole induction motors to investigate the technique\u2019s performance. The results show that the online SFRA could be of interest for monitoring induction motors\u2019 health conditions, especially for mission-critical and safety-critical applications. The overall cost of the whole testing system, including the coupling filters and cables, is less than EUR 400.<\/jats:p>","DOI":"10.3390\/s23052583","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T02:15:37Z","timestamp":1677464137000},"page":"2583","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Online SFRA for Reliability of Power Systems: Characterization of a Batch of Healthy and Damaged Induction Motors for Predictive Maintenance"],"prefix":"10.3390","volume":"23","author":[{"given":"Giovanni","family":"Bucci","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1676-5273","authenticated-orcid":false,"given":"Fabrizio","family":"Ciancetta","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5378-2558","authenticated-orcid":false,"given":"Andrea","family":"Fioravanti","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6244-5521","authenticated-orcid":false,"given":"Edoardo","family":"Fiorucci","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7227-2975","authenticated-orcid":false,"given":"Simone","family":"Mari","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]},{"given":"Andrea","family":"Silvestri","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Industriale e dell\u2019Informazione e di Economia, Universit\u00e0 dell\u2019Aquila, 67100 L\u2019Aquila, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/MIE.2013.2287651","article-title":"Trends in fault diagnosis for electrical machines: A review of diagnostic techniques","volume":"8","author":"Henao","year":"2014","journal-title":"IEEE Ind. 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