Application of Digital Twin Technology in Mechanical Fault Diagnosis and Prediction

Changping Duan; Chengling Tan

doi:10.54097/pk24wr80

Authors

Changping Duan
Chengling Tan

DOI:

https://doi.org/10.54097/pk24wr80

Keywords:

Digital twin, Fault diagnosis and prediction method, Equipment operation management, Equipment health management

Abstract

Fault diagnosis and prediction method is an effective method for equipment operation and maintenance management, which is mainly used in aerospace, military equipment and other fields in the early stage. With the continuous development of fault diagnosis and data acquisition and analysis and other related technologies, fault diagnosis and prediction methods are gradually applied in civil aviation, equipment manufacturing and other fields, and further promoted and popularized in many industries. Traditional fault diagnosis and prediction methods include empirical model-based methods, data-driven methods and physical model-based methods. However, these methods have many limitations. With the rise of digital twin technology, the problem processing method of model and data fusion can effectively solve the shortcomings of traditional fault diagnosis and prediction methods, which is a direction of fault diagnosis and prediction method technology development. After studying the related technologies and methods of fault diagnosis and prediction methods, the digital twin technology and its application methods in fault diagnosis and prediction methods are reviewed, and the key problems in the application are summarized and analyzed, and the future development direction of fault diagnosis and prediction methods supported by digital twin is pointed out.

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