A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

Abstract Prognostics and health management (PHM) significantly improves system availability and reliability, and reduces the cost of system operations. Design for testability (DFT) developed concurrently with system design is an important way to improve PHM capability. Testability modeling and analysis are the foundation of DFT. This paper proposes a novel approach of testability modeling and analysis based on failure evolution mechanisms. At the component level, the fault progression-related information of each unit under test (UUT) in a system is obtained by means of failure modes, evolution mechanisms, effects and criticality analysis (FMEMECA), and then the failure-symptom dependency can be generated. At the system level, the dynamic attributes of UUTs are assigned by using the bond graph methodology, and then the symptom-test dependency can be obtained by means of the functional flow method. Based on the failure-symptom and symptom-test dependencies, testability analysis for PHM systems can be realized. A shunt motor is used to verify the application of the approach proposed in this paper. Experimental results show that this approach is able to be applied to testability modeling and analysis for PHM systems very well, and the analysis results can provide a guide for engineers to design for testability in order to improve PHM performance.

[1]  Andrew Hess,et al.  Extending advanced failure effects analysis to support Prognostics and Health Management , 2010, 2010 Prognostics and System Health Management Conference.

[2]  Michael Pecht,et al.  Health assessment and prognostics of electronic products , 2009, 2009 8th International Conference on Reliability, Maintainability and Safety.

[3]  Michael J. Roemer,et al.  Extending FMECA-health management design optimization for aerospace applications , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[4]  Irem Y. Tumer,et al.  A Graph-Based Fault Identification and Propagation Framework for Functional Design of Complex Systems , 2008 .

[5]  Thomas G. Habetler,et al.  An unsupervised, on-line system for induction motor fault detection using stator current monitoring , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[6]  B. Singh,et al.  A review of stator fault monitoring techniques of induction motors , 2005, IEEE Transactions on Energy Conversion.

[7]  Bertrand Raison,et al.  Models for bearing damage detection in induction motors using stator current monitoring , 2008, 2004 IEEE International Symposium on Industrial Electronics.

[8]  M. Ramamoorty,et al.  Online condition monitoring of induction motors through signal processing , 2005, 2005 International Conference on Electrical Machines and Systems.

[9]  Michael G. Pecht,et al.  Parameter selection for health monitoring of electronic products , 2010, Microelectron. Reliab..

[10]  John W. Sheppard,et al.  POINTER-an intelligent maintenance aid , 1989, IEEE Automatic Testing Conference.The Systems Readiness Technology Conference. Automatic Testing in the Next Decade and the 21st Century. Conference Record..

[11]  Kristin L. Wood,et al.  Development of a Functional Basis for Design , 2000 .

[12]  W. T. Thomson,et al.  On-line MCSA to diagnose shorted turns in low voltage stator windings of 3-phase induction motors prior to failure , 2001, IEMDC 2001. IEEE International Electric Machines and Drives Conference (Cat. No.01EX485).

[13]  M.A. Malik,et al.  Bond graph modeling and simulation of mechatronic systems , 2003, 7th International Multi Topic Conference, 2003. INMIC 2003..

[14]  M.G. Pecht,et al.  Prognostics and health management of electronics , 2008, IEEE Transactions on Components and Packaging Technologies.

[15]  Mojdeh Shakeri.  Advances in system fault modeling and diagnosis , 1996 .

[16]  B. S. Doyle,et al.  A lifetime prediction method for hot-carrier degradation in surface-channel p-MOS devices , 1990 .

[17]  Andrew Hess,et al.  The Maintenance Aware Design environment: Development of an Aerospace PHM Software Tool , 2008 .

[18]  A. Hess,et al.  The Joint Strike Fighter (JSF) PHM concept: Potential impact on aging aircraft problems , 2002, Proceedings, IEEE Aerospace Conference.

[19]  Krishna R. Pattipati,et al.  TEAMS: Testability Engineering and Maintenance System , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[20]  S. H. Chetwani,et al.  Online condition monitoring of induction motors using signature analysis , 2009 .

[21]  Kota Sridhar,et al.  コンプライアンス及び剛性楕円体を活用したコンプライアンス機構の概念的シンセシスのビルディングブロック手法 | 文献情報 | J-GLOBAL 科学技術総合リンクセンター , 2008 .

[22]  Danwei Wang,et al.  Quantitative Hybrid Bond Graph-Based Fault Detection and Isolation , 2010, IEEE Transactions on Automation Science and Engineering.

[23]  John W. Sheppard.  Maintaining diagnostic truth with information flow models , 1996, Conference Record. AUTOTESTCON '96.

[24]  P.W. Kalgren,et al.  Prognostic health management for avionic systems , 2006, 2006 IEEE Aerospace Conference.

[25]  Ji Chao.  Study on Enhanced FMECA Method Application , 2011 .

[26]  Rong Zhang,et al.  On-line broken-bar fault diagnosis system of induction motor , 2008 .

[27]  P.W. Kalgren,et al.  Defining PHM, A Lexical Evolution of Maintenance and Logistics , 2006, 2006 IEEE Autotestcon.

[28]  M. Pecht,et al.  Prognostics and health management using physics-of-failure , 2008, 2008 Annual Reliability and Maintainability Symposium.

[29]  Yang Peng.  Integrated Function-Fault-Behavior-Test-Environment Model for Virtual Testability Verification , 2012 .

[30]  Yong Sun,et al.  A review on degradation models in reliability analysis , 2010, WCE 2010.

[31]  Andrew Hess,et al.  The Joint Strike Fighter (JSF) PHM and the Autonomic Logistic Concept: Potential Impact on Aging Aircraft Problems , 2003 .

[32]  David Coppit,et al.  Developing a low-cost high-quality software tool for dynamic fault-tree analysis , 2000, IEEE Trans. Reliab..

[33]  Lu Jun.  GA-BP Adaptive Weighted Fuzzy Petri Net for Fault Diagnosis , 2012 .

[34]  J. Stecki,et al.  The language of FMEA : on the effective use and reuse of FMEA data , 2009 .

[35]  Jing Qiu,et al.  Hierarchical Model-Based Approach to Testability Modeling and Analysis for PHM of Aerospace Systems , 2014 .

[36]  B. Kelley,et al.  A new dependency model based testability analyzer , 1998, 1998 IEEE AUTOTESTCON Proceedings. IEEE Systems Readiness Technology Conference. Test Technology for the 21st Century (Cat. No.98CH36179).

[37]  Krishna R. Pattipati,et al.  Multi-signal flow graphs: a novel approach for system testability analysis and fault diagnosis , 1994 .

[38]  Jan F. Broenink.  Introduction to Physical Systems Modelling with Bond Graphs , 2000 .