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Fault Diagnosis and Analysis of IoT Motor Bearings Based on Software Definition.

Bibliographic Details
Title: Fault Diagnosis and Analysis of IoT Motor Bearings Based on Software Definition.
Authors: Wang, Wentao, Liu, Weijin, Sun, Min
Source: International Journal of High Speed Electronics & Systems; Aug2026, Vol. 35 Issue 3, p1-17, 17p
Subject Terms: Fault diagnosis, Bearings (Machinery), Machinery maintenance & repair, Internet of things, Electronic data processing, Automatic control systems, Self-adaptive software, Real-time computing
Abstract: This paper aims to explore an innovative motor bearing fault diagnosis technology that deeply integrates the advantages of the Internet of Things (IoT) and software-defined technology. Today, with the continuous advancement of industrial intelligence, the accuracy and real-time fault diagnosis of motor bearings, as the core components of mechanical equipment, are particularly important. This paper proposes a software-defined IoT motor-bearing fault diagnosis model, which utilizes IoT technology to collect motor-bearing operation data and combines the flexibility of software-defined technology for fault diagnosis. In terms of methodology, a series of steps including dataset partitioning, model training, validation, testing, and result analysis were used to systematically evaluate the proposed fault diagnosis model. The outstanding advantage of this innovative model lies in its full utilization of the flexibility of software-defined technology and the extensive connectivity of IoT technology, achieving real-time monitoring and efficient analysis of the operating status of motor bearings. By dynamically adjusting the diagnostic algorithm and data processing flow, the model can adapt to the fault diagnosis requirements under different working conditions, improving the accuracy and adaptability of diagnosis. In addition, its powerful data processing capabilities ensure real-time fault diagnosis, providing strong support for timely maintenance measures, avoiding equipment damage and production interruptions. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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DbLabel: Complementary Index
An: 192030686
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PubTypeId: academicJournal
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IllustrationInfo
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  Label: Title
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  Data: Fault Diagnosis and Analysis of IoT Motor Bearings Based on Software Definition.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Wentao%22">Wang, Wentao</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Weijin%22">Liu, Weijin</searchLink><br /><searchLink fieldCode="AR" term="%22Sun%2C+Min%22">Sun, Min</searchLink>
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  Data: International Journal of High Speed Electronics & Systems; Aug2026, Vol. 35 Issue 3, p1-17, 17p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Bearings+%28Machinery%29%22">Bearings (Machinery)</searchLink><br /><searchLink fieldCode="DE" term="%22Machinery+maintenance+%26+repair%22">Machinery maintenance & repair</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Automatic+control+systems%22">Automatic control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Self-adaptive+software%22">Self-adaptive software</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper aims to explore an innovative motor bearing fault diagnosis technology that deeply integrates the advantages of the Internet of Things (IoT) and software-defined technology. Today, with the continuous advancement of industrial intelligence, the accuracy and real-time fault diagnosis of motor bearings, as the core components of mechanical equipment, are particularly important. This paper proposes a software-defined IoT motor-bearing fault diagnosis model, which utilizes IoT technology to collect motor-bearing operation data and combines the flexibility of software-defined technology for fault diagnosis. In terms of methodology, a series of steps including dataset partitioning, model training, validation, testing, and result analysis were used to systematically evaluate the proposed fault diagnosis model. The outstanding advantage of this innovative model lies in its full utilization of the flexibility of software-defined technology and the extensive connectivity of IoT technology, achieving real-time monitoring and efficient analysis of the operating status of motor bearings. By dynamically adjusting the diagnostic algorithm and data processing flow, the model can adapt to the fault diagnosis requirements under different working conditions, improving the accuracy and adaptability of diagnosis. In addition, its powerful data processing capabilities ensure real-time fault diagnosis, providing strong support for timely maintenance measures, avoiding equipment damage and production interruptions. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1142/S0129156425408022
    Languages:
      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 1
    Subjects:
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Bearings (Machinery)
        Type: general
      – SubjectFull: Machinery maintenance & repair
        Type: general
      – SubjectFull: Internet of things
        Type: general
      – SubjectFull: Electronic data processing
        Type: general
      – SubjectFull: Automatic control systems
        Type: general
      – SubjectFull: Self-adaptive software
        Type: general
      – SubjectFull: Real-time computing
        Type: general
    Titles:
      – TitleFull: Fault Diagnosis and Analysis of IoT Motor Bearings Based on Software Definition.
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            NameFull: Wang, Wentao
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          Name:
            NameFull: Liu, Weijin
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            NameFull: Sun, Min
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            – D: 01
              M: 08
              Text: Aug2026
              Type: published
              Y: 2026
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              Value: 01291564
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              Value: 35
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              Value: 3
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            – TitleFull: International Journal of High Speed Electronics & Systems
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