This paper introduces several tools developed for automated analysis of faults and protective relay operations. The tools are implemented using intelligent techniques based on synchronized sampling, expert systems, neural networks, and fuzzy logic. To promptly detect the faults of the relay protection system and the circuit breakers in time and to ensure the operational reliability of these protective devices, this paper proposes a fault tracing method for a relay protection system–circuit breaker based on improved Random Forest. Firstly, an. This study introduces a new diagnostic framework that combines improved particle swarm optimization, K-means clustering algorithms, support vector machine (SVM), and learning vector quantization neural networks to provide a comprehensive fault diagnosis and pre-diction model for relay protection. Abstract: A method of fault tracking for relay protection devices is presented in this paper. Today, this analysis is performed off line and mostly through manual inspection of different data records captured by digital protective relays (DPRs), digital fault recorders. This paper analyzes the basic principle and function of relay protection, summarizes the common fault types, and analyzes the fault analysis methods and treatment measures combined with actual cases.
