Skip to main content
SpringerLink
Log in

Research on Electric Gate Valve On-Line Fault Diagnosis Method Based on Fuzzy Pattern Recognition

  • Conference paper
  • First Online:
Advances in Intelligent Automation and Soft Computing (IASC 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 80))

Included in the following conference series:

  • 2138 Accesses

Abstract

The motor current parameters of electric gate valve were studied to avoid the disadvantages of strain sensor application, to realize the development of electric gate valve monitoring and fault diagnosis technology from offline monitoring and manual diagnosis to online monitoring and computer diagnosis. The time-domain and frequency-domain indicators from the current curve were extracted to form a standard pattern characteristic matrix, the faults were analyzed and reasoned by using fuzzy pattern recognition technology, and the valve faults were identified according to the quantified closeness data, which improves the intuitiveness and reliability of fault diagnosis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Dai, B., Gui, C., Huang, P.: Application and prospect of valve diagnosis technology in China's nuclear power plants. In: Chinese Mechanical Engineering Society. Proceedings of the Sixth National Academic Conference on Equipment Maintenance and Modification, Hangzhou: The Sixth National Academic Conference on Equipment Maintenance and Modification, pp. 147–153 (2007)

    Google Scholar 

  2. Miller, L.: The past, present and future of valve diagnostic technology. In: China Instrumentation Society. Proceedings of the Symposium on Fieldbus and Intelligent Instrumentation, pp. 173–177. China Instrumentation Society, Hainan (2003)

    Google Scholar 

  3. Chen, L., Wang, X., Zhang, Y., Huang, G.: Summary of valve fault diagnosis techniques. Fluid Mach. 43(9), 36–43 (2015)

    Google Scholar 

  4. Longlong, X.: Application of electric valve diagnostic technology in nuclear power plants. China High-Tech Enterpr. 22(337), 42–43 (2015)

    Google Scholar 

  5. EPRI. Using Motor-Operated Valve (MOV) Static Diagnostic Testing to Diagnose Valve Degradation. 3002012918 (2018)

    Google Scholar 

  6. Yang, G., Shouyin, H., Li, Z.: Research and design of a fault diagnosis system for safety-grade electric isolation valves. Nucl. Power Eng. 30(3), 102–106 (2009)

    Google Scholar 

  7. Yang, Y.: Research on the Combination of SVM and FCM for Fault Diagnosis. Xi'an University of Science and Technology, Xi'an (2008)

    Google Scholar 

  8. Wen, B.: Handbook of Mechanical Design, 5th edn. Machinery Industry Press, Beijing (2010)

    Google Scholar 

Download references

Acknowledgement

This article is supported by National Natural Science Foundation of China (No. 2017ZX06002001).

Author information

Authors and Affiliations

  1. Shanghai Nuclear Engineering Research and Design Institute Co., Ltd., No.29 Hongcao Road, Shanghai, 200233, China

    Qiangqiang Zhou, Haiping Shen, Xiuhui Le & Chunjing Song

Authors
  1. Qiangqiang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haiping Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiuhui Le
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chunjing Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qiangqiang Zhou .

Editor information

Editors and Affiliations

  1. Electronics and Computer Engineering Technology, Indiana State University, Terre Haute, IN, USA

    Xiaolong Li

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhou, Q., Shen, H., Le, X., Song, C. (2022). Research on Electric Gate Valve On-Line Fault Diagnosis Method Based on Fuzzy Pattern Recognition. In: Li, X. (eds) Advances in Intelligent Automation and Soft Computing. IASC 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-81007-8_43

Download citation

Publish with us

Policies and ethics

Search

Navigation