Early Fault Detection in Electro-Pneumatic Actuators using Mathematical Modelling and Machine Learning: A Bottling Company Case Study

Early Fault Detection in Electro-Pneumatic Actuators using Mathematical Modelling and Machine Learning: A Bottling Company Case Study

This research examines the vital problem of detecting anomalies at an early stage within industrial systems by studying an electro-pneumatic double-acting cylinder actuator used in a bottling facility production line. The occurrence of malfunctions in valves leads to operational inefficiencies, and...

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Bibliographic Details
Main Authors: Samuel Olufemi Amudipe, Adeyinka Moses Adeoye, Aderonke Oluwaseunfunmi Akinwumi, Rotimi Adedayo Ibikunle, Segun Adebayo
Format: Article
Language:English
Published: College of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, Nigeria 2025-04-01
Series:ABUAD Journal of Engineering Research and Development
Subjects:
Operational deviations
Machine
Early detection
Techniques
Learning
Online Access:https://www.journals.abuad.edu.ng/index.php/ajerd/article/view/1061
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