Research on Fault Diagnosis of Electromechanical Equipment Based on Digital Twin Technology

The paper presents a fault diagnosis method for electromechanical equipment based on digital twin technology. Taking the rotary sorting mechanism as the research object, the dynamic model including the drive system, the locking mechanism and the sorting arm mechanism is established, and the multi-sensor collaborative data acquisition scheme and the virtual-real mapping mechanism are designed. Through the case verification of the brake unlocking fault in the locking mechanism, this method realizes the rapid fault location and cause analysis, with high diagnostic accuracy and short reaction time, and greatly improves the efficiency compared with the traditional manual diagnosis method. The research results provide a new technical path for the intelligent operation and maintenance of electromechanical equipment.

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Publication Details

Published
2025-01-10
DOI
https://doi.org/10.1109/citsc64390.2025.00164
Primary Topic
Engineering Diagnostics and Reliability
Type
article
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article

Research on Fault Diagnosis of Electromechanical Equipment Based on Digital Twin Technology

Xiaomeng Zhang, Shan Yan, Han Hongmin
Engineering Diagnostics and Reliability
article

Research on Fault Diagnosis of Electromechanical Equipment Based on Digital Twin Technology

Xiaomeng Zhang, Shan Yan, Han Hongmin
article en

Abstract

The paper presents a fault diagnosis method for electromechanical equipment based on digital twin technology. Taking the rotary sorting mechanism as the research object, the dynamic model including the drive system, the locking mechanism and the sorting arm mechanism is established, and the multi-sensor collaborative data acquisition scheme and the virtual-real mapping mechanism are designed. Through the case verification of the brake unlocking fault in the locking mechanism, this method realizes the rapid fault location and cause analysis, with high diagnostic accuracy and short reaction time, and greatly improves the efficiency compared with the traditional manual diagnosis method. The research results provide a new technical path for the intelligent operation and maintenance of electromechanical equipment.

Openalex Percentile: Top 93%
Engineering Diagnostics and Reliability
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