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Fault evolution-test dependency modeling for mechanical systems

  • Xiao-dong Tan
  • Jian-lu Luo
  • Qing Li
  • Bing Lu
  • Jing Qiu
Article
  • 42 Downloads

Abstract

Tracking the process of fault growth in mechanical systems using a range of tests is important to avoid catastrophic failures. So, it is necessary to study the design for testability (DFT). In this paper, to improve the testability performance of mechanical systems for tracking fault growth, a fault evolution-test dependency model (FETDM) is proposed to implement DFT. A testability analysis method that considers fault trackability and predictability is developed to quantify the testability performance of mechanical systems. Results from experiments on a centrifugal pump show that the proposed FETDM and testability analysis method can provide guidance to engineers to improve the testability level of mechanical systems.

Keywords

Mechanical systems Design for testability (DFT) Fault evolution-test dependency model (FETDM) 

Document code

CLC number

TP277 

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References

  1. Alabakhshizadeh, A., Iskandarani, Y., Hovland, G., et al., 2011. Analysis, modeling and simulation of mechatronic systems using the Bond Graph method. Model. Identif. Contr., 32(1):35–45. [doi:10.4173/mic.2011.1.3]CrossRefGoogle Scholar
  2. Biswas, G., Mahadevan, S., 2007. A hierarchical model-based approach to systems health management. Proc. IEEE Aerospace Conf., p.1–14. [doi:10.1109/AERO.2007.352943]Google Scholar
  3. Byington, C.S., Watson, M., Edwards, D., et al., 2004. A model-based approach to prognostics and health management for flight control actuators. Proc. IEEE Aerospace Conf., p.3551–3562. [doi:10.1109/AERO.2004.1368172]Google Scholar
  4. Deb, S., Pattipati, K.R., Raghavan, V., et al., 1995. Multisignal flow graphs: a novel approach for system testability analysis and fault diagnosis. IEEE Aerosp. Electron. Syst. Mag., 10(5):14–25. [doi:10.1109/62.373993]CrossRefGoogle Scholar
  5. Gao, Y.C., Feng, Y.X., Tan, J.R., 2014. Multi-principle preventive maintenance: a design-oriented scheduling study for mechanical systems. J. Zhejiang Univ.-Sci. A (Appl. Phys. & Eng.), 15(11):862–872. [doi:10.1631/jzus.A1400102]CrossRefGoogle Scholar
  6. Hess, A., Stecki, J.S., Rudov-Clark, S.D., 2008. The maintenance aware design environment: development of an aerospace PHM software tool. Proc. Conf. on Prognostics and Health Management, p.1–9.Google Scholar
  7. Johnson, J., 2008. Fault Propagation Timing Analysis to Aid in the Selection of Sensors for Health Management Systems. MS Thesis, University of Missouri-Rolla, USA.Google Scholar
  8. Kallesøe, C., 2005. Fault Detection and Isolation in Centrifugal Pumps. PhD Thesis, Aalborg University, Denmark.Google Scholar
  9. Kurtoglu, T., Tumer, I.Y., 2008. A graph-based fault identification and propagation framework for functional design of complex system. J. Mech. Des., 130(5):051401.1–051401.8. [doi:10.1115/1.2885181]CrossRefGoogle Scholar
  10. Lin, C., Hayes, L., Malais, A., et al., 1998. A new dependency model based testability analyzer. Proc. IEEE Systems Readiness Technology Conf., p.187–191. [doi:10.1109/ AUTEST.1998.713442]Google Scholar
  11. Pattipati, K.R., Raghavan, V., Shakeri, M., et al., 1994. TEAMS: testability engineering and maintenance system. Proc. American Control Conf., p.1989–1995. [doi:10.1109/ACC.1994.752424]Google Scholar
  12. Sheppard, J.W., 1996. Maintaining diagnostic truth with information flow models. Proc. IEEE Conf. Record Test Technology and Commercialization, p.447–454. [doi:10. 1109/AUTEST.1996.547773]Google Scholar
  13. Simpson, W.R., Balaban, H.S., 1982. The ARINC research system testability and maintenance program (STAMP). Proc. IEEE AUTOTESTCON Conf., p.88–95.Google Scholar
  14. Simpson, W.R., Sheppard, J.W., Unkle, C.R., 1989. POINTER—an intelligent maintenance aid. Proc. IEEE Automatic Testing Conf., p.26–31. [doi:10.1109/AUTEST.1989.81094]Google Scholar
  15. Stone, R.B., Wood, K.L., 2000. Development of a functional basis for design. J. Mech. Des., 122(4):359–370. [doi:10.1115/1.1289637]CrossRefGoogle Scholar
  16. Tan, X.D., Qiu, J., Liu, G.J., et al., 2013. A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism. Chin. J. Aeronaut., 26(3):766–776. [doi:10.1016/j.cja.2013.04.044]CrossRefGoogle Scholar
  17. Yang, S.M., Qiu, J., Liu, G.J., 2014. Hierarchical model-based approach to testability modeling and analysis for PHM of aerospace systems. J. Aerosp. Eng., 27(1):131–139. [doi:10.1061/(ASCE)AS.1943-5525.0000203]CrossRefGoogle Scholar
  18. Zhang, G.F., 2005. Optimum Sensor Localization/Selection in a Diagnostic/Prognostic Architecture. PhD Thesis, Georgia Institute of Technology, USA.Google Scholar

Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Xiao-dong Tan
    • 1
    • 2
  • Jian-lu Luo
    • 1
  • Qing Li
    • 1
  • Bing Lu
    • 1
  • Jing Qiu
    • 2
  1. 1.Department of Electronic TechnologyOfficers College of PAPChengduChina
  2. 2.Science and Technology on Integrated Logistics Support LaboratoryNational University of Defense TechnologyChangshaChina

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