首页|Technical University Federico Santa Maria Researcher Details New Studies and Fin dings in the Area of Machine Learning (Detection of Inter-Turn Short Circuits in Induction Motors Using the Current Space Vector and Machine Learning Classifier s)
Technical University Federico Santa Maria Researcher Details New Studies and Fin dings in the Area of Machine Learning (Detection of Inter-Turn Short Circuits in Induction Motors Using the Current Space Vector and Machine Learning Classifier s)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on artificial intelligence are presented in a new report. According to news reporting from Santiago, Chile, by NewsRx journalists, research stated, "Electric motors play a fundamental rol e in various industries, and their relevance is strengthened in the context of t he energy transition." Funders for this research include Espol; Universidad Tecnica Federico Santa Mari a. The news journalists obtained a quote from the research from Technical Universit y Federico Santa Maria: "Having efficient tools and techniques to detect and dia gnose faults in electrical machines is crucial, as is providing early alerts to facilitate prompt decision-making. This study proposes indicators based on the m agnitude of the space vector stator current for detecting and diagnosing incipie nt inter-turn short circuits (ITSCs) in induction motors (IMs). The effectivenes s of these indicators was evaluated using four machine learning methods previous ly documented in the literature: random forests (RFs), support vector machines ( SVMs), the k-nearest neighbor (kNN), and feedforward and recurrent neural networ ks (FNNs and RNNs). This assessment was conducted using experimental data."
Technical University Federico Santa Mari aSantiagoChileSouth AmericaCyborgsEmerging TechnologiesMachine Learn ing
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