Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods

Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods

Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relying on the assumption of linearity, might potentially provide u...

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Bibliographic Details
Main Authors: Nicholas Cartocci, Marcello R. Napolitano, Francesco Crocetti, Gabriele Costante, Paolo Valigi, Mario L. Fravolini
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Sensors
Subjects:
additive model
anomaly detection
multivariate adaptive regression splines
time-dependent directional residuals
non-linear residual-based technique
fault isolation
Online Access:https://www.mdpi.com/1424-8220/22/7/2635

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https://www.mdpi.com/1424-8220/22/7/2635

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