Fault Diagnosis Methods for Resolvers: A Review

With the advantages of high precision, high reliability, and strong environmental adaptability, resolvers play a central role in position detection across various fields, including aerospace, automotive, and servo systems. However, prolonged operation in harsh environments can lead to faults such as eccentricity and short/open winding, and interference from non-ideal factors. These issues lead to a decrease in position detection accuracy and potentially cause system failure. Thus, fault diagnosis technology has become the focus of considerable research interest. This paper summarizes the research progress related to fault diagnosis of the resolver. First, it explains the working principle of the resolvers and rotor position extraction methods, clarifying their signal output characteristics. Next, it classifies and analyzes typical faults such as eccentricity, winding faults, and those caused by non-ideal factors. systematically summarizes diagnostic methods, including those based on signal processing, model resolution, and artificial intelligence, comparing their diagnostic accuracy, real-time performance, and applicability. Finally, it identifies common challenges in current research, such as unclear fault characteristics, insufficient synergy between diagnosis and fault tolerance, and poor adaptability of diagnostic methods to new structures, and proposes future research directions aligned with technological trends. This review aims to provide a reference for both engineering applications and academic research in resolver fault diagnosis and fault-tolerant control.