Fault Diagnosis Method for Bearing Based on Digital Twin

Xie, Xing; Yang, Zichun; Wu, Wei‐Tao; Zhang, Lei; Wang, Xuefeng; Zeng, Guoqing; Chen, Guobing

doi:10.1155/2022/2982746

Cited by 4 publications

(3 citation statements)

References 38 publications

(38 reference statements)

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“…Finally, a novel multi-scale residual self-focusing feature fusion network was designed for training and verification using twin data. Addressing the challenge of requiring a substantial amount of labeled sample data for bearing fault diagnosis methods based on DL, Xie et al [115] proposed a bearing fault diagnosis framework based on DT. When fault data is available, self-organizing mapping and SVM are used to analyze the data.…”

Section: Dt-assisted Intelligent Fault Diagnosismentioning

confidence: 99%

Intelligent fault diagnosis methods for hydraulic components based on information fusion: review and prospects

Guan,

Ren,

Tang

et al. 2024

Meas. Sci. Technol.

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Hydraulic component faults have the characteristics of nonlinear time-varying signal, strong concealment, and difficult feature extraction, etc. Timely and accurately fault diagnosis of hydraulic components is helpful to curb economic losses and accidents, so researches have carried out a lot of research on hydraulic components. Information fusion technology can combine multi-source data from multiple dimensions to mine fault data characteristics, which effectively improves the accuracy and reliability of fault diagnosis results. However, there is currently a lack of a comprehensive and systematic review in this domain. Therefore, in this paper, the hydraulic components information fusion fault diagnosis technologies are summarized and analyzed, including the main process information fusion fault diagnosis and the research status of information fusion fault diagnosis of hydraulic system. The methods and techniques involved in the fusion process, data source and fusion method of fault diagnosis of hydraulic components information fusion are described and summarized. The problems of information fusion in fault diagnosis of hydraulic components are analyzed, the solutions are discussed, and the research ideas of improving information fusion fault diagnosis are put forward. Finally, digital twin technology is introduced, and the advantages and research status of intelligent fault diagnosis based on digital twin are summarized. On this basis, the intelligent fault diagnosis of hydraulic components based on information fusion is summarized, and the challenges and future research ideas of applying information fusion and digital twin to intelligent fault diagnosis of hydraulic components are put forward and analyzed comprehensively.

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Section: Dt-assisted Intelligent Fault Diagnosismentioning

confidence: 99%

Intelligent fault diagnosis methods for hydraulic components based on information fusion: review and prospects

Guan,

Ren,

Tang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

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“…Around 22% of publications were distributed in other 6 fields, including aerospace, communication, transportation, etc. Nowadays, DT has been applied in at least 18 domains and many more sub-domains 18 like electric vehicle (EV) 25 and unmanned aerial vehicle (UAV) industries 26 . For PHM in industrial assets, DT application is limited.…”

Section: Dt Application In Phmmentioning

confidence: 99%

“…A well-designed hierarchical structure facilitates management, coordination, and reuse of the algorithms, data, and knowledge in DT-PHM, which reduces research costs and improves DT model adaptivity across industrial assets in different hierarchies. Industrial assets in manufacturing are classified into production-oriented and product-oriented hierarchies 18 . Figure 7 visualizes the 73 reviewed papers reflecting the hierarchical theory in manufacturing.…”

Section: Dt Application In Phmmentioning

confidence: 99%

Digital twin-driven prognostics and health management for industrial assets

Xiao,

Zhong,

Bao

et al. 2024

Sci Rep

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As a facilitator of smart upgrading, digital twin (DT) is emerging as a driving force in prognostics and health management (PHM). Faults can lead to degradation or malfunction of industrial assets. Accordingly, DT-driven PHM studies are conducted to improve reliability and reduce maintenance costs of industrial assets. However, there is a lack of systematic research to analyze and summarize current DT-driven PHM applications and methodologies for industrial assets. Therefore, this paper first analyzes the application of DT in PHM from the application field, aspect, and hierarchy at application layer. The paper next deepens into the core and mechanism of DT in PHM at theory layer. Then enabling technologies and tools for DT modeling and DT system are investigated and summarized at implementation layer. Finally, observations and future research suggestions are presented.

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