Journal of Research in Electrical Circuits and Systems ISSN: 3139-2059 (Online)

Abstract

Fault detection and diagnosis are essential for maintaining the reliability and safety of electrical circuits. This paper explores novel approaches to fault detection, including machine learning algorithms, statistical analysis, and hardware redundancy. By leveraging these advanced techniques, the accuracy and speed of fault detection can be significantly improved. The paper presents a comprehensive evaluation of each approach, highlighting their strengths and potential applications. Experimental results demonstrate the efficacy of these methods in identifying and diagnosing faults in complex electrical circuits. 

Keywords: Fault detection, Fault diagnosis, Machine learning, Statistical analysis, Hardware redundancy