Condition Monitoring of Power Insulators Using Intelligent Techniques–A Survey

Abstract

Studies that evaluate the monitoring of the condition of power insulators and the malfunction of these devices are especially focused on the main variables involved with their aging process. The early degradation of power insulators, which is more common in highly polluted locations, results in risks to the operation of the electrical system and can financially impact power utilities due to unplanned service interruptions and premature maintenance. Many techniques have been proposed in the literature to evaluate the condition of power insulators. Among these techniques, intelligent systems or machine learning techniques stand out, being pointed out as one of the most promising tools for the early detection of malfunctions in such equipment. However, there is a lack of studies that address this problem more broadly, using the full capacity of intelligent techniques to compile a complete and expert monitoring system that can make automatic decisions or provide subsidies to the operator for more assertive maintenance actions. Based on the studies found in the literature and on the shortcomings identified on the subject, this work presents an investigation into the use of intelligent techniques for monitoring the condition of power insulators in transmission lines, mainly focusing on the early detection of malfunctions of these devices.