Motor PHM on Edge Computing with Anomaly Detection and Fault Severity Estimation through Compressed Data Using PCA and Autoencoder

The motor is essential for manufacturing industries, but wear can cause unexpected failure. Predictive and health management (PHM) for motors is critical in manufacturing sites. In particular, data-driven PHM using deep learning methods has gained popularity because it reduces the need for domain ex...

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Autors principals:	Jong Hyun Choi, Sung Kyu Jang, Woon Hyung Cho, Seokbae Moon, Hyeongkeun Kim
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-06-01
Col·lecció:	Machine Learning and Knowledge Extraction
Matèries:	motor PHM edge computing anomaly detection fault severity estimation data compression PCA
Accés en línia:	https://www.mdpi.com/2504-4990/6/3/69
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