Supervised Learning-Based Fault Classification in Industrial Rotating Equipment Using Multi-Sensor Data

Supervised Learning-Based Fault Classification in Industrial Rotating Equipment Using Multi-Sensor Data

The reliable operation of rotating machinery is critical in industrial production, necessitating advanced fault diagnosis and maintenance strategies to ensure operational availability. This study employs supervised machine learning algorithms to apply multi-label classification for fault detection i...

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Bibliographic Details
Main Authors: Aziz Kubilay Ovacıklı, Mert Yagcioglu, Sevgi Demircioglu, Tugberk Kocatekin, Sibel Birtane
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
rotating machinery
fault detection
machine learning
multi-label classification
predictive maintenance
multi-sensor data integration
Online Access:https://www.mdpi.com/2076-3417/15/13/7580
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