摘要详情

ID / 提交时间

263 / 2025-06-15 18:54:54

标题

Research on Bearing Fault Diagnosis Based on Digital Twin Technology

关键字

Digital Twin, Fault Diagnosis, OPC UA, Order Analysis

主题及专题

Special Sessions > SSL 01 Advanced signal processing enabled intelligent fault diagnosis and measurement

状态

全文待审

作者

Haibo Wu / Kunming University of Science and Technology

Yuheng Yang / Kunming University of Science and Technology

Chengpiao Zheng / Kunming University of Science and Technology

Mengqi Yang / Kunming University of Science and Technology

Xuan Wang / Kunming University of Science and Technology

Rongzhen Luo / Kunming University of Science and Technology

摘要

In response to the challenges of bearing fault diagnosis, this paper constructs a fault diagnosis architecture based on digital twin. In the physical layer, a bearing test bench and sensors are used for data collection, and data fusion is achieved through transformation and encapsulation. The data layer relies on the OPC UA communication protocol to complete data interaction and synchronous mapping, generating twin data. In the virtual layer, 3D modeling and rendering are carried out, and then the model is imported into Unity 3D to realize the virtual mapping of the physical entity. On this basis, the fault diagnosis module uses order analysis and result encoding to obtain image data, and combines with a deep - learning model for fault diagnosis. This architecture realizes the coordination of the physical layer, data layer, and virtual layer, which is expected to improve the accuracy and real - time performance of bearing fault diagnosis, and provide effective support for the predictive maintenance of industrial equipment.