Piechocki, MateuszKraft, MarekPajchrowski, Tomasz2023-09-212023-09-212023Piechocki M., Kraft M., Pajchrowski T., Fault Diagnosis in a Squirrel-Cage Induction Motor Using Thermal Imaging. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 37-42, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.4.978-83-66741-92-8http://hdl.handle.net/11652/4779https://doi.org/10.34658/9788366741928.4Fault diagnosis is a vivid topic in industrial applications or intelligent building solutions. One of the well-established techniques involves the measurement and analysis of current signals. However, this method has several significant drawbacks, such as the inability to inspect during machinery operation or the lack of precise information on the malfunction location. This article proposes a non-invasive method for squirrel-cage induction motor’s state classification and fault diagnosis. The approach is based on thermal image analysis that utilizes a compact convolution neural network. In addition, the gathered and annotated image set, which consists of thermal images with 640 x 512 pixels resolution, is presented.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionthermal imagingfault diagnosissquirrel-cage induction motordeep learninginterpretabilitytermowizjadiagnostyka ustereksilnik indukcyjny klatkowygłębokie uczenie sięinterpretowalnośćRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.4