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...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Jong Hyun Choi, Sung Kyu Jang, Woon Hyung Cho, Seokbae Moon, Hyeongkeun Kim
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-06-01
Edice:	Machine Learning and Knowledge Extraction
Témata:	motor PHM edge computing anomaly detection fault severity estimation data compression PCA
On-line přístup:	https://www.mdpi.com/2504-4990/6/3/69
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!