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Developing RCM Strategy for Wind Turbines Utilizing Online Condition E-Monitoring

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Engineering Asset Management 2011

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

The number of offshore wind turbines installed in the seas around Britain’s coasts is likely to increase from just fewer than 150 to 7,500 over the next 10 years with the potential cost of £10 billion. Operation and Maintenance activities are estimated to comprise 35 % of the cost of electricity. However, the development of appropriate and efficient maintenance strategies is currently lacking in the wind industry. The current reliability and failure modes of offshore wind turbines are known and have been used to develop preventive and corrective maintenance strategies which have done little to improve reliability. Unplanned maintenance levels can be reduced by increasing the reliability of the gearbox and individual gears through the analysis of lubricants. In addition, the failure of one minor component can cause escalated damage to a major component, which can increase repair and or replacement costs. A Reliability Centered Maintenance (RCM) approach offers considerable benefit to the management of wind turbine operations, since it includes an appreciation of the impact of faults on operations. Due to the high costs involved in performing maintenance and the even higher costs associated with failures and subsequent downtime and repair, it is critical that the impacts are considered when maintenance is planned. The paper will provide an overview of the application of RCM and on line e-condition monitoring to wind turbine maintenance management. Finally, the paper will discuss the development of a complete sensor-based processing unit that can continuously monitor the wind turbine’s lubricated systems and provide, via wireless technology, real-time data enabling onshore staff the ability to predict degradation, anticipate problems, and take remedial action before damage and failure occurs.

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References

  1. World Wind Energy Report (2009) World Wind Energy Association (WWEA). Bonn, Germany

    Google Scholar 

  2. Botsaris PN, Konstantinidis EI (2010) Wind turbine optimisation: a holisitic approach. In: The seventh international conference on condition monitoring and machinery failure prevention technologies, 22–24 June 2010. Ettington Chase, Stratford-upon-Avon, England, UK

    Google Scholar 

  3. Baglee et al (2006) Modern maintenance practices: the barriers to implementation within small/medium enterprises. In: IMA international conference on modeling in industrial maintenance and reliability. Salford, England, UK

    Google Scholar 

  4. Polinder H, van der Pijl FFA, de Vilder GJ, Tavner PJ (2006) Comparison of direct-drive and geared generator concepts for wind turbines. IEEE Trans Energy Convers 21(3):725–733

    Article  Google Scholar 

  5. Barber S, Golbeck P (2010) The benefits of a pro-active approach using preventive and predictive maintenance tools and strategies: actual examples and case studies (internet). (Cited 2010 Dec)

    Google Scholar 

  6. Available from: http://www.wwindea.org/technology/ch03/en/3_4_3.html

  7. Puigcorbe J, de-Beaumont A (2010) Wind turbine gearbox reliability: the impact of rotor support (internet). (Updated 2010 June 3, cited 2010 Dec)

    Google Scholar 

  8. Available from: http://www.renewableenergyworld.com/rea/news/article/2010/06/wind-turbine-gearbox-reliability

  9. Braam H, Rademakers L (2004) Models to analyse operation and maintenance aspects of offshore wind farms, ECN Report

    Google Scholar 

  10. Tavner P, Bussel GV, Spinato F (2006) Machine and converter reliabilities in wind turbines. In: The 3rd IET international conference on power electronics, machines and drives, Mar 2006, pp 127–130

    Google Scholar 

  11. Tavner PJ, Xiang J, Spinato F (2007) Reliability analysis for wind turbines. Wind Energ 10:1–18. doi:10.1002/we.204

    Article  Google Scholar 

  12. McMillan D, Ault GW (2008) Condition monitoring benefit for onshore wind turbines: sensitivity to operational parameters. IET Renew Power Gener 2(1):60–72

    Article  Google Scholar 

  13. McMillan D, Ault GW (2008) Specification of reliability benchmarks for offshore wind farms. In: Proceedings of the European safety and reliability, Sept 2008, pp 22–25

    Google Scholar 

  14. Ben-Daya M (2000) You may need RCM to enhance TPM implementation. J Qual Maint Eng 6(2):82–85

    Article  Google Scholar 

  15. Meng T, Dresel W (eds) (2007) Lubricants and lubrication. Wiley-VCH, New York

    Google Scholar 

  16. Barnes J, Hengeveld J, Foster S, Schasfoort T, Scheele R (2004) Oil stress investigations in Shell’s medium speed laboratory engine. Paper presented at: CIMAC Congress, Kyoto, 2004

    Google Scholar 

  17. Laurence RB (1994) The effect of lubrication system and marine specific factors on diesel engine emissions (MS Thesis). Massachusetts Institute of Technology 1994. Cambridge, Massachuestts, USA

    Google Scholar 

  18. Knowles MJ, Baglee D (2010) Condition monitoring in an on-ship environment. In: The seventh international conference on condition monitoring and machinery failure prevention technologies (BINDT CM 2010), June 2010

    Google Scholar 

  19. Baldwin A, Lunt S (2010) Latest developments in online oil condition monitoring sensors. The seventh international conference on condition monitoring and machinery failure prevention technologies (BINDT CM 2010), June 2010

    Google Scholar 

  20. Gorritxategi E, Arnaiz A, Aranzabe E, Ciria J, Terradillos J, (2006) Indirect optical measurements for lubricant status assessment. In: Proceedings of the 19th international congress of condition monitoring and diagnostic engineering management June 2006. Luleå, Sweden, pp 367–376

    Google Scholar 

  21. Gorritxategi E, Arnaiz A, Belew J (2007) Marine oil monitorization by means of on-line sensors. Instrumentation viewpoint, p 6

    Google Scholar 

  22. Neammanee B, Sirisumrannukul S, Chtratana S (2007) Development of a wind turbine simulator for wind generator testing. Int Energy J 8:21–28

    Google Scholar 

  23. Nichita C, Luca D, Dakyo B, Ceanga E (2002) Large band simulator of wind speed for real time wind turbine simulators. IEEE Tran Energy Convers 17(4):523–529

    Article  Google Scholar 

  24. Moore I, Ekanayake J (2010) Design and development of a hardware based wind turbine simulator. In: Proceedings of the 45th international universities power engineering conference (UPEC), 31 Aug–3 Sept 2010, pp 1–5

    Google Scholar 

  25. Knowles MJ, Baglee D, Wermter S (2010) Reinforcement learning for scheduling of maintenance. In: The thirtieth SGAI international conference on artificial intelligence (AI-2010), Dec 2010

    Google Scholar 

  26. Kaelbling LP, Littman ML, Moore AW (1996) Reinforcement learning: a survey. J Artif Intell Res 4:237–285

    Google Scholar 

  27. Kuremoto T, Obayashi M, Kobayashi K (2005) Nonlinear prediction by reinforcement learning. In: Proceedings of the 2005 international conference on advances in intelligent computing. Springer, Berlin, pp 1085–1094

    Google Scholar 

  28. Wu F, Wang T, Lee J (2010) An online adaptive condition-based maintenance method for mechanical systems. Mech Syst Signal Process 24(8):2985–2995

    Article  Google Scholar 

  29. Hameed Z, Hong YS, Cho YM, Ahn SH, Song CK (2009) Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renew Sustain Energy Rev 13:1–39

    Article  Google Scholar 

  30. Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and e-maintenance. Comput Ind: e-Maintenance Spec issue 57(6):476–489. doi:10.1016/j.compind.2006.02.014

    Article  Google Scholar 

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Correspondence to D. Baglee .

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Baglee, D., Knowles, M.J. (2014). Developing RCM Strategy for Wind Turbines Utilizing Online Condition E-Monitoring. In: Lee, J., Ni, J., Sarangapani, J., Mathew, J. (eds) Engineering Asset Management 2011. Lecture Notes in Mechanical Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4993-4_2

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  • DOI: https://doi.org/10.1007/978-1-4471-4993-4_2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4992-7

  • Online ISBN: 978-1-4471-4993-4

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