Abstract
Overloading is one of the faults that occur very often in the operation of electrical machines. Therefore, a continuous monitoring and diagnosis for this is necessary in safety-critical applications. This paper presents a sound analysis system used for detecting and classifying induction motor and power transformer overload levels with a microphone. Three acoustic features and six classification models are evaluated. The obtained results show that this is a promising way to monitor electrical machines overload.
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Cong-Phuong, N., Ninh, N.T. (2023). Overload Monitoring System Using Sound Analysis for Electrical Machines. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13588. Springer, Cham. https://doi.org/10.1007/978-3-031-23492-7_24
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DOI: https://doi.org/10.1007/978-3-031-23492-7_24
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