ELECTRICAL FAULT DIAGNOSIS AND MAINTENANCE STRATEGIES FOR INDUSTRIAL POWER SYSTEMS

Industrial power systems are essential to manufacturing, petrochemical, mining, processing, and other energy-intensive operations, yet their increasing complexity raises the frequency and consequences of electrical faults. This review examines fault-diagnosis techniques and maintenance strategies for improving reliability, operational efficiency, safety, and equipment life. Relevant literature on industrial power systems, common fault mechanisms, diagnostic practices, intelligent monitoring, and maintenance management was critically synthesized and compared. The review covers short-circuit, ground, open-circuit, insulation, overload, arc, harmonic, transformer, and motor faults. Conventional techniques include visual inspection, insulation-resistance testing, protective-relay monitoring, infrared thermography, vibration analysis, dissolved-gas analysis, partial-discharge measurement, and power-quality analysis. Advanced approaches based on artificial intelligence, neural networks, fuzzy logic, expert systems, machine learning, internet-connected sensors, and supervisory control are also assessed. Maintenance philosophies considered include corrective, preventive, predictive, condition-based, reliability-centered, and total productive maintenance. The evidence indicates that predictive and condition-based strategies can reduce unplanned downtime and improve asset reliability by identifying deterioration before catastrophic failure. Their effectiveness is strengthened when diagnostic data are integrated with maintenance planning and skilled human judgment. However, aging infrastructure, weak maintenance culture, limited technical expertise, financial constraints, inconsistent power quality, harsh operating conditions, and cybersecurity risks continue to hinder implementation, particularly in developing economies. Integrating intelligent diagnosis with proactive maintenance, digital monitoring, workforce development, and robust cybersecurity is therefore recommended to improve long-term industrial power-system performance. Overall, the review supports a coordinated framework in which diagnostic evidence, risk-based prioritization, and timely maintenance decisions are managed as one continuous reliability process.