ISSN: 2265-6294

Real-time Anomaly Detection and Predictive Maintenance in Metro Train APU Compressors: A Data-driven Approach

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Swathi , Anand Gangula , Maruth Reddy Vootukuri , Rakesh Manchiryala

Abstract

Metro rail systems play a crucial role in contemporary urban transportation networks. Ensuring the dependable functioning of auxiliary power units (APU) is essential for the overall efficiency and security of metro trains. Utilizing anomaly detection in APU compressors can effectively mitigate failures and reduce downtime, hence improving the efficiency and dependability of metro services. Anomaly detection in industrial settings often utilizes rule-based systems or threshold-based alarms as conventional solutions

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