Digital Twin - Based Fault Diagnosis Methodology for Stage Lifts

In response to the issues of limited actual fault data of stage lifts and the high complexity of fault diagnosis implementation, this paper proposes a novel fault diagnosis method for stage lifts based on digital twin technology. The proposed method fuses virtual and real data to detect abnormal data when structural failures occur, thereby enhancing equipment reliability and ensuring operational safety. Additionally, this study utilizes the K-Nearest Neighbors (KNN) algorithm, aiming to achieve early prediction of faults caused by improper use or internal faults of stage lift platforms. Rigorous experimental verification demonstrates the feasibility and effectiveness of the proposed method in fault diagnosis, showcasing its potential to revolutionize fault diagnosis for stage lift systems.