IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v8y2017i3d10.1007_s13198-017-0573-0.html
   My bibliography  Save this article

Risk assessment of sensor failures in a condition monitoring process; degradation-based failure probability determination

Author

Listed:
  • Farzin Salehpour-Oskouei

    (Sahand University of Technology)

  • Mohamad Pourgol-Mohammad

    (Sahand University of Technology)

Abstract

Condition monitoring of a system is in need of an efficient sensor network for detecting system faults in early stages. Sensor is a silent-failure component as it is not monitored in the main system misleading in estimation of the system health state. Then, failure-causes of the system are not detected due to missed detection. A risk-based measure is proposed in this research to take into account the consequence of sensor missed-detection. All possible combinations are determined for failure-causes as components state vectors. The probability of missed-detection is estimated by applying occurrence probability of failure causes and degradation-based failure probability of sensors. First, a sensor characteristic is selected through which the degradation process is affected. Then a degradation model is developed to calculate the sensor time to failure. The consequences of missed-detection are also corresponding quantifiable potential losses through both failure costs and maintenance expenditure. Finally, all feasible sensors placement scenarios are compared due to proposed risk measure. As a case study, sensor network of steam turbine condition monitoring is selected. Various sensor placement scenarios of steam turbine are prioritized based on the risk index and results are discussed.

Suggested Citation

  • Farzin Salehpour-Oskouei & Mohamad Pourgol-Mohammad, 2017. "Risk assessment of sensor failures in a condition monitoring process; degradation-based failure probability determination," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 584-593, September.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:3:d:10.1007_s13198-017-0573-0
    DOI: 10.1007/s13198-017-0573-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-017-0573-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-017-0573-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Farzin Salehpour-Oskouei & Mohammad Pourgol-Mohammad, 2018. "Sensor placement determination in system health monitoring process based on dual information risk and uncertainty criteria," Journal of Risk and Reliability, , vol. 232(1), pages 65-81, February.
    2. Mohammad Pourgol-Mohammad & Farzin Salehpour-Oskouei, 2023. "Multi-criteria sensor placement determination in prognostics and health management using combined fault diagnosis, fault detection, and risk indexes," Journal of Risk and Reliability, , vol. 237(6), pages 1234-1247, December.
    3. Bahareh Tajiani & Jørn Vatn, 2023. "Adaptive remaining useful life prediction framework with stochastic failure threshold for experimental bearings with different lifetimes under contaminated condition," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1756-1777, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:8:y:2017:i:3:d:10.1007_s13198-017-0573-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.