Fault Classification in HVDC Systems: A Fuzzy Logic Classifier Approach

In order to classify faults in High Voltage Direct Current (HVDC) systems, this research proposes a unique method based on fuzzy logic and signals gathered from simulated HVDC systems under various failure situations. In long-distance power transmission, where fault diagnosis and classification are critical to preserving system stability and dependability, HVDC systems are indispensable. Several failure types that are often seen in HVDC systems are simulated in this study, and voltage and current data are collected for analysis via chromatic monitoring. The suggested fault classification method accurately classifies faults by interpreting the analysed signals using a fuzzy logic classifier. The ability of fuzzy logic to handle the uncertainty and imprecision included in real-world data makes it appropriate for fault classification jobs in intricate systems such as HVDC. The fuzzy logic classifier is trained to identify patterns linked to particular defect kinds using the data gathered from simulated scenarios.