Data-Driven Fault Detection and Diagnosis: Challenges and Opportunities in Real-World Scenarios

Data-Driven Fault Detection and Diagnosis: Challenges and Opportunities in Real-World Scenarios

The pervasive digital innovation of the last decades has led to a remarkable transformation of maintenance strategies. The data collected from machinery and the extraction of valuable information through machine learning (ML) have assumed a crucial role. As a result, data-driven predictive maintenan...

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Bibliographic Details
Main Authors: Francesca Calabrese, Alberto Regattieri, Marco Bortolini, Francesco Gabriele Galizia
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
predictive maintenance
industrial application
fault detection and diagnosis
novelty detection
Online Access:https://www.mdpi.com/2076-3417/12/18/9212

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