{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T09:47:52Z","timestamp":1724924872803},"reference-count":50,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Spanish \u2018Ministerio de Ciencia e Innovaci\u00f3n\u2019, Agencia Estatal de Investigaci\u00f3n and FEDER program","award":["PID2021-122343OB-I00"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Due to their robustness, versatility and performance, induction motors (IMs) have been widely used in many industrial applications. Despite their characteristics, these machines are not immune to failures. In this sense, breakage of the rotor bars (BRB) is a common fault, which is mainly related to the high currents flowing along those bars during start-up. In order to reduce the stresses that could lead to the appearance of these faults, the use of soft starters is becoming usual. However, these devices introduce additional components in the current and flux signals, affecting the evolution of the fault-related patterns and so making the fault diagnosis process more difficult. This paper proposes a new method to automatically classify the rotor health state in IMs driven by soft starters. The proposed method relies on obtaining the Persistence Spectrum (PS) of the start-up stray-flux signals. To obtain a proper dataset, Data Augmentation Techniques (DAT) are applied, adding Gaussian noise to the original signals. Then, these PS images are used to train a Convolutional Neural Network (CNN), in order to automatically classify the rotor health state, depending on the severity of the fault, namely: healthy motor, one broken bar and two broken bars. This method has been validated by means of a test bench consisting of a 1.1 kW IM driven by four different soft starters coupled to a DC motor. The results confirm the reliability of the proposed method, obtaining a classification rate of 100.00% when analyzing each model separately and 99.89% when all the models are analyzed at a time.<\/jats:p>","DOI":"10.3390\/s23010316","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:38:43Z","timestamp":1672223923000},"page":"316","source":"Crossref","is-referenced-by-count":10,"title":["Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-8229-7447","authenticated-orcid":false,"given":"Vicente","family":"Biot-Monterde","sequence":"first","affiliation":[{"name":"Instituto Tecnol\u00f3gico de la Energ\u00eda (ITE), Universitat Polit\u00e8cnica de Val\u00e8ncia (UPV), Camino de Vera S\/N, 46022 Valencia, Spain"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9963-8204","authenticated-orcid":false,"given":"Angela","family":"Navarro-Navarro","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico de la Energ\u00eda (ITE), Universitat Polit\u00e8cnica de Val\u00e8ncia (UPV), Camino de Vera S\/N, 46022 Valencia, Spain"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8499-3948","authenticated-orcid":false,"given":"Israel","family":"Zamudio-Ramirez","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico de la Energ\u00eda (ITE), Universitat Polit\u00e8cnica de Val\u00e8ncia (UPV), Camino de Vera S\/N, 46022 Valencia, Spain"},{"name":"HSPdigital CA-Mecatronica Engineering Faculty, Autonomous University of Queretaro, San Juan del Rio 76806, Mexico"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-1898-2228","authenticated-orcid":false,"given":"Jose A.","family":"Antonino-Daviu","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico de la Energ\u00eda (ITE), Universitat Polit\u00e8cnica de Val\u00e8ncia (UPV), Camino de Vera S\/N, 46022 Valencia, Spain"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-0868-2918","authenticated-orcid":false,"given":"Roque A.","family":"Osornio-Rios","sequence":"additional","affiliation":[{"name":"HSPdigital CA-Mecatronica Engineering Faculty, Autonomous University of Queretaro, San Juan del Rio 76806, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.worlddev.2016.12.013","article-title":"The Importance of Manufacturing in Economic Development: Has This Changed?","volume":"93","author":"Haraguchi","year":"2017","journal-title":"World Dev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/2943.930988","article-title":"Current signature analysis to detect induction motor faults","volume":"7","author":"Thomson","year":"2001","journal-title":"IEEE Ind. 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