Industrial Electrical Event Data Recorder (IE-EDR): A Black-Box System for Electrical Panel Accident Investigation

Author

Dr. D. D. Dhawale, Harshal Fulpatil , Abhay Thakare , Arpit Ganorkar, Ravindra Rahangdale, Saish Badhe

Abstract

 Industrial electrical panels operate under a range of potentially hazardous conditions, such as excessive current, short circuits, poor electrical connections, elevated temperatures, arc faults, and unauthorized access. Although protective relays and monitoring systems help maintain operational safety, information required to investigate an electrical incident may be recorded by separate devices or may lack a common time reference. To address this limitation, this paper proposes an Industrial Electrical Event Data Recorder (IE-EDR), a compact monitoring system designed to preserve operational information from an electrical panel in a black-box format.

The proposed system integrates voltage and current measurement units, temperature and environmental sensors, door and switching-status inputs, a real-time clock (RTC), a microcontroller, and removable data storage. A rule-based event detection mechanism continuously evaluates the monitored parameters against predefined threshold values. Whenever a specified abnormal condition is identified, the system stores the corresponding measurements, status indicators, and timestamp to support subsequent analysis. This paper presents the system architecture, monitoring methodology, event-recording procedure, proposed data structure, fundamental decision logic, safety requirements, and experimental validation plan for a single-phase prototype. The design can potentially be extended to three-phase installations by incorporating suitable measurement devices and electrically isolated interfaces.

Advanced capabilities, including sensor-data fusion, TinyML- and LSTM-based anomaly analysis, power-quality monitoring, tamper-evident data logging, and industrial communication protocols, are identified as possible future developments rather than implemented or experimentally verified functions. As measured laboratory results are not currently available, no claims are made regarding detection accuracy, predictive capability, or overall system performance. Instead, a structured testing methodology is proposed to evaluate event-detection delay, completeness of recorded information, clock synchronization error, false-trigger frequency, and data-storage dependability. The proposed framework aims to provide a practical foundation for improving post-event analysis and fault investigation in industrial electrical panel applications.

Keywords

industrial electrical safety, event data recorder, electrical panel monitoring, embedded systems, fault investigation, event logging, predictive maintenance

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