A Discussion of the Prognostics and Health Management Aspects of Embedded Condition Monitoring System

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Roger I. Grosvenor Paul W. Prickett

Abstract

This paper presents a review of embedded condition monitoring research carried out at Cardiff University. A variety of application areas are described, along with a discussion of the evolution of the hardware platforms used. The current operating philosophies of the Intelligent Process Monitoring and Management (IPMM) research group and the deployed hierarchical and distributed architectures are described. The paper sets out to discuss the on-going trend towards such monitoring systems needing to provide more than fault detection and diagnostic capabilities. System requirements such as tracking operational settings, performance and efficiency measures and providing limp-home facilities are seen to be consistent with prognostics and health management ideals. The paper concludes with a discussion of new and future developments and applications.

How to Cite

I. Grosvenor, R., & W. Prickett, P. (2011). A Discussion of the Prognostics and Health Management Aspects of Embedded Condition Monitoring System. Annual Conference of the PHM Society, 3(1). https://doi.org/10.36001/phmconf.2011.v3i1.1964
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Keywords

embedded condition monitoring, elligent process monitoring

References
Ahsan, Q., Grosvenor, R.I. & Prickett, P.W. (2006) Distributed On-Line System for Process Plant Monitoring. Proc I.Mech.E, J.Process Mech.Eng., vol 220 (e2), pp 61 – 77. doi: 10.1243/09544089JPME53.
Amer, W., Grosvenor, R. & Prickett, P. (2007) Machine Tool Condition Monitoring Using Sweeping Filter Techniques. Proc. I.Mech.E. J. Systems & Control Eng., vol 221 (1), pp 103 – 117. doi:10.1243/09596518JSCE133.

Davies, G.R., Grosvenor, R.I., Prickett, P.W. & Lee, C.(2009) An Approach to the Detection and Characterisation of Faults in a Water Treatment Plant. Proc. Comadem, (pp 553 – 558), June 9-14, San Sebastian. ISSN 9788493206468.

Drake, P.R., Grosvenor, R.I. & Jennings, A.D. (1995) Review of Data Acquisition System Developed for the MIRAM Project. Conf. Proc. Sensors & Their Applications VII, (pp 433 – 437), Sept 10-13, Dublin. ISBN 0 7503 0331 X Edwards, P.M., Grosvenor, R.I. & Prickett, P.W. (2006) A Review of Lamp Condition Monitoring Techniques. Lighting Journal, vol 71 (5), pp 31 – 38. ISSN 09504559.

Eyers, D.R., Grosvenor, R.I. & Prickett, P.W. (2005) Welding Station Condition Monitoring using Bluetooth Enabled Sensors and Intelligent Data Management. Sensors & their Applications XIII, (pp 143 – 148), Sept 6-6, Greenwich. doi: 10.1088/1742-6596/15/1/024.
Frankowiak, M., Grosvenor, R. & Prickett, P. (2005) A Review of the Evolution of Microcontroller-Based machine and Process Monitoring. International Journal of Machine Tools & Manufacture, vol. 45, pp 573 – 582. doi: 10.1016/j.ijmachtools.2004.08.018.
Franowiak, M.R., Grosvenor, R.I. & Prickett, P.W. (2009) Microcontroller-based Process Monitoring Using PetriNets. EURASIP Journal on Embedded Systems, ID 282708, pp 1 – 12. doi: 10.1155/2009/282708.

Hess, A., Calvello, G. & Frith, P. (2005) Challenges, Issues, and Lessons Learned Chasing the “Big P”: Real Predictive Prognostics Part1. Aerospace Conf. IEEE, (pp 3610 – 3619) March 5-12. Big Sky MT. doi: Systems. 5 th IFAC Symp. Mechatronic Systems, (pp 614 – 619) Sept 13-15, Cambridge
MA. Rashid, M. & Grosvenor, R.I. (1997) Fault diagnosis of Ballscrew Systems Through Neural Networks.Proc. Comadem ’97, (pp 142 – 151), June 9-11, Helsinki. ISBN 1 901892131. Sharif, M.A. & Grosvenor, R.I. (1998) Fault Diagnosis in Industrial Control Valves and Actuators. Proc. IEEE Instn&Meast.Tech Conf, (pp 770 – 778), May 18-21, Minnesota. ISSN 0 7803 4797 8/98.
Siddiqui, R.A., Amer, W., Ahsan, Q., Grosvenor, R.I. & Prickett, P.W. (2007) Multi-band Infinite Impulse Response Filtering using Microcontrollers for eMonitoring Applications. Microprocessors and Microsystems 31, pp 370-380. doi: 10.1016/j.micpro.2007.02.007.
Siddiqui, R.A., Grosvenor, R. & Prickett, P. (2010) An Overview of a Microcontroller based approach to Intelligent Machine Tool Monitoring. Lecture Notes in Computer Science, 6277, 371-380. doi: 10.1007/978-3642-15390-7_38.
Wheeler, K.R., Kurtoglu, T. & Poll, S.D. (2010) A Survey of Health Management User Objectives in Aerospace Systems Related to Diagnostic and Prognostic Metrics. Int. J. Prog. & Health. Mangt.
Section
Poster Presentations