Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Kongresse
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Veranstaltungskalender Awards MyNewsletter Firmensuche
Kunden Login
Über Einzelzugang informieren
Über Unternehmenszugang informieren
Referenzkunden
12. Internationaler Motorenkongress 2025 | 25. + 26. Februar 2025

Treffpunkt der Community für Antriebe und nachhaltige Kraftstoffe

Der Kongress beleuchtet die zukünftige Rolle des Verbrennungsmotors und seiner nichtfossilen Kraftstoffe aus globaler Sicht mit führenden Experten. Seien Sie dabei! Weitere Informationen und Buchungsmöglichkeiten finden Sie auf unserer Website.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:

2014 | OriginalPaper | Buchkapitel

Condition Monitoring and Maintenance Methods in Wind Turbines

verfasst von : Rodrigo J. A. Vieira, Miguel A. Sanz-Bobi

Erschienen in: Use, Operation and Maintenance of Renewable Energy Systems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Wind is an attractive source of renewable energy, and its use has become increasingly important over the last decades all around the world. After this explosion of installations of wind farms, an important concern has arisen concerning several topics in which the goals are to keep the value of the assets of the wind farms and to guarantee long life cycles. The continuous monitoring of the life of the wind turbines and a correct application of maintenance plan contribute to achieving these goals. This chapter first reviews the main principles supporting different strategies of maintenance, later a framework is presented integrating different aspects of the lives of the wind turbine, and finally some methods for the detection of abnormal behavior in wind turbines and for failure risk evaluation are presented applied to some real cases.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Nächstes Kapitel Operation and Maintenance Methods in Solar Power Plants
Literatur
1.
Al-Najjar B, Alsyouf I (2004) Enhancing a company’s profitability and competitiveness using integrated vibration-based maintenance: a case study. Eur J Oper Res 157(3):643–657MATH
2.
Amirat Y, Benbouzid MEH, Bensaker B, Wamkeue R (2007) Condition monitoring and fault diagnosis in wind energy conversion systems: a review. In: Proceedings of 2007 IEEE international electric machines and drives conference, vol 2, pp 1434–1439
3.
Amirat Y, Benbouzid MEH, Bensaker B, Wamkeue R (2007) Generators for wind energy conversion systems: state of the art and coming attractions. J Electr Syst 3–1:26–38
4.
Andrade Vieira RJ, Sanz-Bobi MA (2013) Failure risk indicators for a maintenance model based on observable life of industrial components with an application to wind turbines. IEEE Trans Reliab 62(3):569–582
5.
Andrade Vieira RJ, Sanz-Bobi MA, Kato S (2013) Wind turbine condition assessment based on changes observed in its power curve. In: 2nd international conference on renewable energy research and applications—ICRERA 2013, Madrid, Spain
6.
Arranz AL, Cruz A, Sanz-Bobi MA, Ruíz P, Coutiño J (2008) DADICC: intelligent system for anomaly detection in a combined cycle gas turbine plant. Expert Syst Appl 34–4:2267–2277
7.
Arts RHPM, Knapp GMJ, Lawrence M (1998) Some aspects of measuring maintenance performance in the process industry. J Qual Maintenance Eng 4(1):6–11
8.
9.
Bengtsson M (2004) Condition based maintenance system technology—where is development heading? In: Proceedings of the 17th European maintenance congress Euromaintenance, Barcelona, Spain
10.
Bengtsson M (2004) Condition based maintenance systems: an investigation of technical constituents and organizational aspects. In: Citeseer
11.
Bengtsson M, Jackson M (2004) Important aspect to take into considerations when deciding to implement condition based maintenance. In: Proceeding from the 17th conference of condition monitoring and diagnostic management, England, Cambridge: The Central Printing Services, University of Birmingham, UK
12.
Bertling L, Allan R, Eriksson R (2005) A reliability-centered asset maintenance method for assessing the impact of maintenance in power distribution systems. IEEE Trans Power Syst 20(1):1–8
13.
Bin L, Yaoyu L, Xin W, Zhongzhou Y (2009) A review of recent advances in wind turbine condition monitoring and fault diagnosis. In: Proceedings of IEEE power electronics machines in wind applications (PEMWA), pp 1–7
14.
Birolini A (1994) Quality and reliability of technical systems. Springer, BerlinMATH
15.
Birolini A (2004) Reliability engineering: theory and practice, 4th edn. Springer, Berlin
16.
Bouno T, Yuji T, Hamada T, Hideaki T (2005) Failure forecast diagnosis of small wind turbine using acoustic emission sensor. KIEE Int Trans Electr Mach Energy Convers Syst 5-B(1):78–83
17.
Brown RE, Frimpong G et al (2004) Failure rate modeling using equipment inspection data. IEEE Trans Power Syst 19(2):782–787
18.
Buczkowski PS, Hartmann ME, Kulkarni VG (2005) Outsourcing prioritized warranty repairs. Int J Qual Reliab Manag 22(7):699–714
19.
Byington CS, Roemer MJ, Galie T (2002) Prognostic enhancements to diagnostic systems for improved condition-based maintenance. In: IEEE aerospace conference proceedings
20.
Campbell JD, Jardine AKS (2001) Maintenance excellence. Marcel Dekker, New York
21.
Caselitz P, Giebhardt J (1999) Advanced condition monitoring for wind energy converters. In: Proceedings of the European wind energy conference, Nizza, France, 1–5 Mar 1999
22.
Caselitz P, Giebhardt J, Mevenkamp M (1994) On-line fault detection and prediction in wind energy converters. In: Proceedings of the European wind energy conference, Thessaloniki, Greece, 10–14 Oct 1994, pp 623–627
23.
Caselitz P, Giebhardt J, Mevenkamp M (1997) Application of condition monitoring systems in wind energy converters. In: Proceedings of the European wind energy conference, Dublin, Ireland, 6–9 Oct 1997, pp 579–582
24.
Caselitz P, Giebhardt J, Krüger T, Mevenkamp M (1996) Development of a fault detection system for wind energy converters. In: Proceedings of the European wind energy conference, Goteborg, Sweden, 20–24 May 1996, pp 1004–1007
25.
Chen C, Sun C, Zhang Y, Wang N (2005) Fault diagnosis for large-scale wind turbine rolling bearing using stress wave and wavelet analysis. In: Proceedings of 8th international conference on electrical machines and systems, vol 3, pp 2239–2244
26.
Chenglong M, Bin D (2011) Design and application of wind farm fault diagnosis system. In: Proceedings of IEEE power energy engineering conference (APPEEC), Asia-Pacific, pp 1–4
27.
Chow EY, Willsky AS (1984) Analytical redundancy and the design of robust failure detection systems. IEEE Trans Autom Control 29(7):603–614MATHMathSciNet
28.
Chow MY, Mangum PM, Yee SO (1991) A neural network approach to real time condition monitoring of induction motors. IEEE Trans Industr Electron 38(6):448–454
29.
Cigolini R, Fedele L, Garetti M, Macchi M (2008) Recent advances in maintenance and facility management. Prod Plan Control 19(4):279–286
30.
Clayton BR, Dutton AG, Aftab N, Bond LJ, Irving AD, Lipman NH (1990) Development of structural condition monitoring techniques for composite wind turbine blades. In: Proceedings of European community wind energy conference, Madrid, Spain, 10–14 Sept 1990, pp 10–14
31.
Crespo A, Moreu P, Gómez JF, Parra C, López M (2009) The maintenance management framework: a practical view to maintenance management. J Qual Maint Eng 15(2):167–178
32.
Cua KO, McKone KE, Schroeder RG (2001) Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. J Oper Manage 19(6):675–694
33.
Davies A (1998) Handbook of condition monitoring. Chapman & Hall, London
34.
Dekker R, Scarf PA (1998) On the impact of optimization models in maintenance decision making: the state of the art. Reliab Eng Syst Saf 60(2):111–119
35.
36.
Duffuaa SO, Raouf A, Campbell JD (1999) Planning and control of maintenance system: modeling and analysis. Wiley, Hoboken
37.
Eisinger S, Rakowsky UK (2001) Modeling of uncertainties in reliability centered maintenance—a probabilistic approach. Reliab Eng Syst Saf 71(2):159–164
38.
EN 13306: 2001 (2010) Maintenance Terminology (Replaced by EN 13306: 2010)
39.
Endrenyi J, Aboresheid S et al (2001) The present status of maintenance strategies and the impact of maintenance on reliability. IEEE Trans Power Syst 16(4):638–646
40.
Endrenyi J, Anders GJ et al (1998) Probabilistic evaluation of effect of maintenance on reliability—an application. IEEE Trans Power Syst 13(2):576–583
41.
42.
Farrar CR, Lieven NAJ (2007) Damage prognosis: the future of structural health monitoring. Philos Trans R Soc A 365:623–632
43.
Franzén A, Bertling L (2007) State of the art—life time modeling and management of transformers. Royal Institute of Technology, KTH, Stockholm
44.
Gabbar HA, Yamashita H, Suzuki K, Shimada Y (2003) Computer-aided RCM-based plant maintenance management system. Robot Comput-integr Manufact 19(5):449–458
45.
García MC (2004) Planificación y Medida de la Efectividad del Mantenimiento predictivo aplicado a un proceso industrial basándose en el uso de técnicas de modelado de su comportamiento y inteligencia artificial. In: Tesis del departamento de electrónica y automática, Universidad Pontificia Comillas, Madrid
46.
García MC, Sanz-Bobi MA (2003) Planificación dinámica del mantenimiento industrial mediante algoritmos genéticos. Mantenimiento 161(42):49
47.
García MC, Sanz-Bobi MA, Pico J (2006) Técnicas de inteligencia artificial aplicadas al mantenimieto predictivo de aerogeneradores. Mantenimiento 137:5–16
48.
Garg A, Deshmukh SG (2006) Maintenance management: literature review and directions. J Qual Maint Eng 12(3):205–238
49.
Gebraeel N, Lawley MA (2008) A neural network degradation model for computing and updating residual life distributions. IEEE Trans Autom Sci Eng 5:154–163
50.
Gertler J (1988) Survey of model-based failure detection and isolation in complex plants. IEEE Control Syst Mag 8(6):3–11
51.
Gertler J (1991) Analytical redundancy methods in fault detection and isolation. In: IFAC fault detection, supervision and safety for technical process
52.
Grimmelius H, Meiler TP, Maas H et al (1999) Three state-of-the-art methods for condition monitoring. IEEE Trans Ind Electron 46(2):407–416
53.
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):1–39
54.
Han T, Yang B-S (2006) Development of an e-maintenance system integrating advanced techniques. In: Comput Ind [special issue on e-maintenance] 57(6):569–80
55.
Hao Q, Xue Y, Shen W, Jones B, Zhu J (2010) A Decision support system for integrating corrective maintenance, preventive maintenance, and condition-based maintenance
56.
Hassanain MA, Froese TM, Vanier DJ (2003) Framework model for asset maintenance management. J Perform Constructed Facil 17:51
57.
Hassanain MA, Froese TM, Vanier DJ (2003) Implementation of distributed model-based integrated asset management system. J Inf Technol Constr 8:119–134
58.
Haykin S (1994) Neural networks: a comprehensive foundation. IEEE Press, New YorkMATH
59.
Hilber P (2008) Maintenance optimization for power distribution systems. Royal Institute of Technology, KTH, Stockholm
60.
Huang J, Miller CR, Okogbaa OG (1995) Optimal preventive-replacement intervals for the Weibull life distribution: solutions and applications. In: Proceedings of annual reliability and maintainability, pp 370–377
61.
Huang Q, Jiang D, Hong L, Ding Y (2008) Application of wavelet neural networks on vibration fault diagnosis for wind turbine gearbox. Lecture notes in computer science, vol 5264, LNCS, n PART 2, advances in neural networks. In: Proceedings of 5th international symposium on neural networks, pp 313–320
62.
Huang S, Kok KT (2009) Fault detection and diagnosis based on modeling and estimation methods. IEEE Trans Neural Netw 20(5):872–881
63.
Hyers RW, McGowan JG, Sullivan KL, Manwell JF, Syrett BC (2006) Condition monitoring and prognosis of utility scale wind turbines. Energy Mater 1(3):187–203
64.
Ip WH, Kwong CK, Fung R (2000) Design of maintenance system in MRPII. J Qual Maint Eng 6(3):177–191
65.
Iravani SMR, Duenyas I (2002) Integrated maintenance and production control of a deteriorating production system. IIE Trans 34(5):423–435
66.
Isermann R (1984) Process fault detection based on modeling and estimation methods—a survey. Int Fed Autom Control 20(4):387–404MATH
67.
Isermann R (1993) Fault diagnosis of machines via parameter estimation and knowledge processing-tutorial paper. Automatica 29(4):815–835MATHMathSciNet
68.
Isermann R (1997) Supervision, fault-detection and fault-diagnosis methods-an introduction. Control Eng Pract 5(5):639–652
69.
Isermann R (2005) Model-based fault-detection and diagnosis—status and applications. Ann Rev Control 29(1):71–85
70.
Iung B (2003) From remote maintenance to MAS-based E-maintenance of an industrial process. J Intell Manuf 14(1):59–82
71.
Jardine AK, Tsang AH (2006) Maintenance, replacement, and reliability: theory and applications. CRC Taylor & Francis, Boca Raton
72.
Jardine A, Lin D, Banjevic D (2006) A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech Syst Sig Process 20(7):1483–1510
73.
Jayabalan V, Chaudhuri D (1992) Cost optimization of maintenance scheduling for a system with assured reliability. IEEE Trans Rel R-41:21–25
74.
Jonsson P (1999) Company-wide integration of strategic maintenance: an empirical analysis. Int J Prod Econ 60–61:155–164
75.
Kaplan RS, Norton DP (1992) The balanced scorecard—measures that drive performance. Harv Bus Rev 70(1):71–79
76.
Khan FI, Haddara MM (2003) Risk based maintenance: a quantitative approach for maintenance/inspection scheduling and planning. J Loss Prev Process Ind 16(6):563–573
77.
Koc M, Ni J, Lee J, Bandyopadhyay P (2003) Introduction of e-manufacturing. In: Proceedings of the 31st North American manufacturing research conference (NAMRC), Hamilton, Canada
78.
Kusiak A, Li WY (2011) The prediction and diagnosis of wind turbine faults. Renew Energy 36(1):16–23
79.
Kusiak A, Verma A (2011) Prediction of status patterns of wind turbines: a data-mining approach. ASME J. Solar Eng 133(1):011008-1–011008-10
80.
Kutucuoglu KY, Hamali J, Irani Z, Sharp JM (2001) A framework for managing maintenance using performance measurement systems. Int J Oper Prod Manag 21(1):173–194
81.
Kyle BR, Vanier DJ, Kosovac B, Froese TM (2000) Information needs towards service life asset management. In: Proceedings of 17th international conference of the committee on data for science and technology, CODATA, Baveno, Italy, pp 15–19
82.
Lapira E, Brisset D, Davari Ardakari H, Siegel D, Lee J (2012) Wind turbine performance assessment using multi-regime modeling approach. Renew Energy 45:86–95
83.
Lebold M, Thurston M (2001) Open standards for condition-based maintenance and prognostic systems. In: 5th annual maintenance and reliability conference (MARCON 2001), Gatlinburg, USA
84.
Lee J (2001) A framework for next-generation E-maintenance system. In: Proceedings of the second international symposium on environmentally conscious design and inverse manufacturing, Tokyo, Japan
85.
Lee J (2010) Design of self-maintenance and engineering immune systems for smarter machines and manufacturing systems. In: 1st IFAC workshop on advanced maintenance engineering, services and technology, Lisbon, Portugal, 1–2 July 2010
86.
Lee J, Elmeligy S, Ghaffari M (2010) Transformation from prognostics to engineering immune systems. In: 1st IFAC workshop on advanced maintenance engineering, services and technology, Lisbon, Portugal, 1–2 July 2010
87.
Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and e-maintenance. Comput Ind Spec issue e-maint 57(6):476–489
88.
89.
Lekou DJ, Mouzakis F, Anastasopoulos A, Kourousis D (2009) Emerging techniques for health monitoring of wind turbine gearboxes and bearings. In: Proceedings of EWEC 2009, scientific track—operation and maintenance, Marseille, France, pp 16–19
90.
Levitt J (2009) Handbook of maintenance management. Industrial Press, South Norwalk
91.
Li S, O’Hair E, Giesselmann MG (1997) Using neural networks to predict wind power generation. In: Proceedings of the international solar energy conference, Washington, DC, pp 415–420
92.
Lie CH, Chun YH (1986) An algorithm for preventive maintenance policy. IEEE Trans Rel R-35(1):71–75
93.
Lin D, Zuo M, Yam R (2001) Sequential imperfect preventive maintenance models with two categories of failure models. Naval Res Logistics 48:172–183MATHMathSciNet
94.
Lofsten H (2000) Measuring maintenance performance—in search for a maintenance productivity index. Int J Prod Econ 63(1):47–58
95.
Lu B, Li Y, Wu X, Yang Z (2009) A review of recent advances in wind turbine condition monitoring and fault diagnosis. In: Power electronics and machines in wind applications. PEMWA 2009. IEEE, p 1
96.
MaCalley J, Jiang Y et al (2006) Automated integration of condition monitoring with an optimized maintenance scheduler for circuit breakers and power transformers. In: Power systems engineering research center, PSERC
97.
McArthur SDJ, Booth CD, McFadyen IT (2005) An Agent based anomaly detection architecture for condition monitoring. IEEE Trans Power Syst 20(4):1675–1682
98.
Mobley RK, Higgins LR, Wikoff DJ (2008) Maintenance engineering handbook. Mc-Graw-Hill, New York
99.
Moubray J (1997) Reliability centred maintenance, 2nd edn. Butterworth-Heinemann, Boston
100.
Muller A, Crespo A, Iung B (2008) On the concept of e-maintenance: review and current research. Reliab Eng Syst Saf 93(8):1165–1187
101.
Muñoz A, Sanz-Bobi MA (1998) An incipient fault detection system based on the probabilistic radial basis function network: application to the diagnosis of the condenser of a coal power plant. Neurocomputing 23:177–194
102.
Murthy DN, Asgharizadeh E (1999) Optimal decision making in a maintenance service operation. Eur J Oper Res 116(2):259–273MATH
103.
Murthy DNP, Atrens A, Eccleston JA (2002) Strategic maintenance management. J Qual Maint Eng 8(4):287–305
104.
Nakagawa T (1988) Sequential imperfect preventive maintenance policies. IEEE Trans Reliab 37:295–298MATHMathSciNet
105.
Nakajima S (1988) Introduction to TPM, 1st edn. Productivity Press, Cambridge
106.
Nguyen DG, Murthy DN (1981) Optimal preventive maintenance policies for repairable systems. Oper Res 29(6):1181–1194MATHMathSciNet
107.
Nikolopoulos K, Metaxiotis K, Lekatis N, Assimakopoulos V (2003) Integrating industrial maintenance strategy into ERP. Ind Manag Data Syst 103(3):184–191
108.
Nilsson J (2006) Maintenance management of wind power systems—cost effect analysis of condition monitoring systems. Master’s thesis, KTH, Stockholm, Sweden
109.
Nilsson J, Bertling L (2007) Maintenance management of wind power systems using condition monitoring systems—life cycle cost analysis for two case studies. IEEE Trans Energy Convers 22(1):223–229
110.
Ostergaard J, Jensen AN (2001) Can we delay the replacement of this component?—an asset management approach to the question. In: CIRED, paper no. 482, Amsterdam
111.
Patton RJ, Frank PM, Clark RN (2000) Issues of fault diagnosis for dynamic systems. Springer, Berlin
112.
Penman CM, Yin J (1994) Feasibility of using unsupervised learning, artificial neural networks for the condition monitoring of electrical machines. IEE Proc Electr Power Appl 141(6):317–323
113.
Penman J, Tavner TJ (1989) Condition monitoring of electrical machines. Research Studies Press Ltd., Wiley, New York
114.
Peters F, Meissner U (1995) Object-oriented composition of a framework for integrative facility management. In: Proceedings of CIB-W78/TG10: modeling of buildings through their life cycle, Stanford University, Palo Alto, California, CIB Publication No. 180, CIB, Rotterdam, The Netherlands, pp 111–118
115.
Petersen KE (1993) Reliability based maintenance systems; a knowledge based approach. In: Proceedings of the 4th Scandinavian conference on artificial intelligence electrum, Stockholm, Sweden, 4–7 May 1993, pp 409–410
116.
Pintelon L, Puyvelde FV (1997) Maintenance performance reporting systems: some experiences. J Qual Maint Eng 3(1):4–15
117.
Pouliezos A, Stavrakakis G, Lefas C (1989) Fault detection using parameter estimation. Qual Reliab Eng Int 5:283–290
118.
Provan G. (2003) Prognosis and condition-based monitoring: an open systems architecture. In: 5th IFAC symposium on fault detection, supervision and safety of technical processes, Washington, USA, pp 57–62
119.
Pun K, Chin K, Chow M, Lau HCW (2002) An effectiveness-centered approach to maintenance management: a case study. J Qual Maint Eng 8(4):346–368
120.
Raouf A, Ben-Daya M (1995) Total maintenance management: a systematic approach. J Qual Maint Eng 1(1):6–14
121.
Ribrant J, Bertling LM (2007) Survey of failures in wind power systems with focus on Swedish wind power plants during 1997–2005. IEEE Trans Energy Convers 22(1):167–173
122.
Sanchez-Ubeda EF, Wehenkel L (1998) The Hinges model: a one-dimensional continuous piecewise polynomial model. In: IPMU’98, Paris, France, pp 878–885
123.
Sanz-Bobi MA (1992) Metodología de mantenimiento predictivo basada en análisis espectral y temporal de la historia de los equipos industriales y enfoque de su aplicación a un sistema experto. In: E.T.S. de Ingenieros Industriales, Universidad Politécnica de Madrid, Madrid
124.
Sanz-Bobi MA, Andrade Vieira RJ (2011) A method for estimating stress of a failure mode in a component due to abnormal behavior observed in a wind turbine. In: Proceedings of 24th international congress condition monitoring diagnostics engineering management, Stavanger, Norway, pp 989–998
125.
Sanz-Bobi MA, Andrade Vieira RJ, Montilla X (2011) Failure risk analysis and maintenance effectiveness in a wind turbine according to its history of unavailability and applied maintenance. In: Proceedings of European safety and reliability association conference—ESREL 2011, Troyes, France, pp 853–860
126.
Sanz-Bobi MA, del Pico J, Garcia MC (2006) SIMAP: intelligent system for predictive maintenance application to the health condition monitoring of a wind turbine gearbox. Comput Ind 57(6):552–568
127.
Sanz-Bobi MA, Garcia AC, Palacios R, Villar J, Rolan J, Moran B (1997) Experiences learned from the on-line internal monitoring of the behaviour of a transformer. In: IEEE—IEMDC’97 international electric machines and drive conference, USA
128.
Sanz-Bobi MA, Palacios R, Pérez EM (2009) Estado actual y tendencias de la Gestión de activos (asset management) en las empresas de transporte y distribución de energía eléctrica. Mantenimiento 229:30–38
129.
Sanz-Bobi MA, Palacios R, Muñoz A, García-Escudero R, Pérez M, Matesanz AL (2002) ISPMAT: intelligent system for predictive maintenance applied to trains. In: Proceedings of EUROMAINTENANCE, Helsinki, Finland
130.
Sanz-Bobi MA, Palacios R, Vieira RJA, Nicolau G, Ferrarons P (2010) Assisting tools for a new maintenance planning in a power distribution system. In: IEEE power engineering society general meeting, USA
131.
Sanz-Bobi MA, Vieira RJA, Brighenti C, Palacios R, Nicolau G, Ferrarons P, Vieira P (2010) Component stress evaluation in an electrical power distribution system using neural networks. In: 23rd international conference on industrial, engineering and other applications of applied intelligent systems, Spain
132.
Scarf PA (2007) A framework for condition monitoring and condition based maintenance. Qual Technol Quant Manag 4(2):301–312MathSciNet
133.
Schlechtingen M (2013) A global condition monitoring system for wind turbines. In: PhD thesis, Department of Mechanical Engineering—Solid Mechanics, Technical University of Denmark, Denmark
134.
Schneider J, Gaul A, Neumann C, Hogräfer J, Wellssow W, Schwan M, Schnettler A (2006) Asset management techniques. Electr Power Energy Syst 28(9):643–654
135.
Sheliga DJ (1981) Calculation of optimum preventive maintenance intervals for electric equipment. IEEE Trans Ind Appl 1A-17(5)
136.
Shulian Y, Wenhai L, Canlin W (2008) The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network. In: Proceedings of IEEE international conference on condition monitoring diagnosis (CMD 2008), pp 1327–1330
137.
Sorsa T, Koivo HN (1991) Application of artificial neural networks in process fault diagnosis. Proc Saveprocess 91(2):133–138
138.
Sturm A, Billhardt S (1991) Envelope curve analysis of machines with rolling-element bearings. Proc Saveprocess 91(2):275–279
139.
Sumereder C (2008) Statistical lifetime of hydro generators and failure analysis. IEEE Trans Dielectr Electr Insul 15(3):678–685
140.
Swanson L (2001) Linking maintenance strategies to performance. Int J Prod Econ 70(3):237–244
141.
Tam ASB, Price JWH (2006) A generic maintenance optimization framework. In: 7th Asia pacific industrial engineering and management systems conference, Bangkok, Thailand
142.
Tao B, Ding H, Xion YL (2003) IP sensor and its distributed networking application in e-maintenance. In: Proceedings of the 2003 IEEE international conference on systems, man and cybernetics, vol 4. Washington, DC, USA, pp 3858–63
143.
Thomas E, Levrat E, Iung B, Cocheteux P (2009) Opportune maintenance and predictive maintenance decision support. In: 13th IFAC symposium on information control problems in manufacturing, Moscow, Russia
144.
Tian Z (2009) An artificial neural network approach for remaining useful life prediction of equipments subject to condition monitoring. In: 8th international conference on reliability, maintainability and safety, pp 143–148
145.
Tor O, Shahidephpour M (2006) Power distribution asset management. In: IEEE power engineering society general meeting
146.
Tsang AHC, Jardine AKS, Kolodny H (1999) Measuring maintenance performance: a holistic approach. Int J Oper Prod Manag 19(7):691–715
147.
Tu PVL, Yam R, Tse P, Sun AO (2001) An integrated maintenance management system for an advanced manufacturing company. Int J Adv Manuf Technol 17(9):692–703
148.
Vanier DJ (2001) Why industry needs asset management tools. J Comput Civ Eng 15(1):35–43
149.
Vatland S, Gundersen LS, Sande G, Bugge J, Asbjomsen T, Lund T (2004) Utility systems integration. In: Distribution and asset management conference
150.
Velasquez J (2011) Intelligent monitoring and diagnosis of power transformers in the context of an asset management model. In: Universitat Politècnica de Catalunya UPC, Barcelona
151.
Venkatasubramanian V, Rengaswamy R, Kavuri SN, Yin K (2003) A review of process fault detection and diagnosis. Part III. Process history based methods. Comput Chem Eng 27(3):327–346
152.
Venkatasubramanian V, Rengaswamy R, Kavuri SN (2003) A review of process fault detection and diagnosis. Part II. Qualitative models and search strategies. Comput Chem Eng 27(3):313–326
153.
Venkatasubramanian V, Rengaswamy R, Yin K, Kavuri SN (2003) A review of process fault detection and diagnosis. Part I. Quantitative model-based methods. Comput Chem Eng 27(3):293–311
154.
Verbruggen TW (2003) Wind turbine operation and maintenance based on condition monitoring. In: ECN-C-03-047
155.
Waeyenbergh G, Pintelon L (2002) A framework for maintenance concept development. Int J Prod Econ 77(3):299–313
156.
Wang FK, Lee W (2001) Learning curve analysis in total productive maintenance. Omega 29(6):491–499MathSciNet
157.
Wang H (2002) A survey of maintenance policies of deteriorating systems. Eur J Oper Res 139(3):469–489MATH
158.
Wang P, Vachtsevanos G (1999) Fault prognosis using dynamic wavelet neural networks. In: AAAI spring symposium in equipment maintenance service and support, Polo Alto, USA
159.
Wenxian Y, Tavner PJ, Wilkinson M (2008) Wind turbine condition monitoring and fault diagnosis using both mechanical and electrical signatures. In: Proceedings of IEEE/ASME international conference on advanced intelligent mechatronics, pp 1296–1301
160.
Wessels RW (2003) Cost optimized scheduled maintenance interval for reliability centered maintenance. In: Proceedings annual reliability and maintainability symposium, IEEE, pp 412–416
161.
Wilkinson MR, Spinato F, Tavner PJ (2007) Condition monitoring of generators and other subassemblies in wind turbine drive trains. In: Proceedings of 2007 IEEE international symposium on diagnostics for electric machines, power electronics and drives, pp 388–392
162.
Wireman T (2004) Total productive maintenance. Industrial Press, South Norwalk
163.
Wu S, Gebraeel N, Lawley MA (2007) A neural network integrated decision support system for condition-based optimal predictive maintenance policy. IEEE Trans Syst Man Cybern 37(2):226–236
164.
Yang S, Li W, Wang C (2008) The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network. In: Proceedings of international conference on condition monitoring and diagnosis, pp 1327–1330
165.
Yang W, Jiang J (2011) Wind turbine condition monitoring and reliability analysis by SCADA information. In: Second international conference on mechanic automation and control engineering (MACE), Blyth, UK, 15–17 July 2011, pp 1872–1875
166.
Yang W, Tavner PJ, Wilkinson MR (2009) Condition monitoring and fault diagnosis of a wind turbine synchronous generator drive train. IET Renew Power Gener 3(1):1–11
167.
Yoshikawa H (1995) Manufacturing and the 21st century—intelligent manufacturing systems and the renaissance of the manufacturing industry. Technol Forecast Soc Change 49(2):165–213
168.
Zaher AS, McArthur SDJ (2007) A multi-agent fault detection system for wind turbine defect recognition and diagnosis. In: Proceedings of IEEE Lausanne POWERTECH, pp 22–27
169.
Zhang X, Gockenbach E (2008) Reliability centered asset management for power distribution systems. In: Proceedings of IEEE international symposium on electrical insulation—ISEI
Metadaten
Titel
Condition Monitoring and Maintenance Methods in Wind Turbines
verfasst von
Rodrigo J. A. Vieira
Miguel A. Sanz-Bobi
Copyright-Jahr
2014
Buch
Use, Operation and Maintenance of Renewable Energy Systems

Print ISBN: 978-3-319-03223-8

Electronic ISBN: 978-3-319-03224-5

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-03224-5_1