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Stochastic modelling fatigue crack evolution and optimum maintenance strategy for composite blades of wind turbines

  • Chen, Hua-Peng (Department of Engineering Science, University of Greenwich) ;
  • Zhang, Chi (Department of Engineering Science, University of Greenwich) ;
  • Huang, Tian-Li (School of Civil Engineering, Central South University)
  • Received : 2017.01.07
  • Accepted : 2017.06.10
  • Published : 2017.09.25

Abstract

The composite blades of offshore wind turbines accumulate structural damage such as fatigue cracking due to harsh operation environments during their service time, leading to premature structural failures. This paper investigates various fatigue crack models for reproducing crack development in composite blades and proposes a stochastic approach to predict fatigue crack evolution and to analyse failure probability for the composite blades. Three typical fatigue models for the propagation of fatigue cracks, i.e., Miner model, Paris model and Reifsnider model, are discussed to reproduce the fatigue crack evolution in composite blades subjected to cyclical loadings. The lifetime probability of fatigue failure of the composite blades is estimated by stochastic deterioration modelling such as gamma process. Based on time-dependent reliability analysis and lifecycle cost analysis, an optimised maintenance policy is determined to make the optimal decision for the composite blades during the service time. A numerical example is employed to investigate the effectiveness of predicting fatigue crack growth, estimating the probability of fatigue failure and evaluating an optimal maintenance policy. The results from the numerical study show that the stochastic gamma process together with the proper fatigue models can provide a useful tool for remaining useful life predictions and optimum maintenance strategies of the composite blades of offshore wind turbines.

Keywords

References

  1. Avramidis, A.N. and L'Ecuyer, P. (2006), "Efficient Monte Carlo and quasi-Monte Carlo option pricing under the variance gamma model", Manage. Sci., 52(12), 1930-1944. https://doi.org/10.1287/mnsc.1060.0575
  2. Blanco, N., Gamstedt, E.K., Asp, L.E. and Costa, J. (2004), "Mixed-mode delamination growth in carbon-fibre composite laminates under cyclic loading", Int. J. Solid. Struct., 41(15), 4219-4235. https://doi.org/10.1016/j.ijsolstr.2004.02.040
  3. Chen, H.P. (2015), "Monitoring-based reliability analysis of aging concrete structures by bayesian updating", J. Aerosp. Eng., B4015004.
  4. Chen, H.P. and Alani, A.M. (2012), "Reliability and optimised maintenance for sea defences", Proceedings of the Institution of Civil Engineers-Maritime Engineering, 165(2), 51-64. https://doi.org/10.1680/maen.2010.37
  5. Chen, H.P. and Alani, A.M. (2013), "Optimized maintenance strategy for concrete structures affected by cracking due to reinforcement corrosion", ACI Struct. J., 110(2), 229-238.
  6. Chen, H.P. and Huang, T.L. (2012), "Updating finite element model using dynamic perturbation method and regularization algorithm", Smart Struct. Syst., 10(4-5), 427-442. https://doi.org/10.12989/sss.2012.10.4_5.427
  7. Chen, H.P. and Nepal, J. (2015), "Stochastic modelling and lifecycle performance assessment of bond strength of corroded reinforcement in concrete", Struct. Eng. Mech., 54(2), 319-336. https://doi.org/10.12989/sem.2015.54.2.319
  8. Chen, H.P. and Xiao, N. (2015), "Symptom-based reliability analyses and performance assessment of corroded reinforced concrete structures", Struct. Eng. Mech., 53(6), 1183-1200. https://doi.org/10.12989/sem.2015.53.6.1183
  9. Degrieck, J. and Van Paepegem, W. (2001), "Fatigue damage modeling of fibre-reinforced composite materials: Review", Appl. Mech. Rev., 54(4), 279-300. https://doi.org/10.1115/1.1381395
  10. DiLorenzo, E., Petrone, G., Manzato, S., Peeters, B., Desmet, W. and Marulo, F. (2016), "Damage detection in wind turbine blades by using operational modal analysis", Struct. Hlth. Monit., 15(3), 289-301. https://doi.org/10.1177/1475921716642748
  11. Esteban, M.D., Diez, J.J., Lopez, J.S. and Negro, V. (2011), "Why offshore wind energy", Renew. Energy, 36(2), 444-450. https://doi.org/10.1016/j.renene.2010.07.009
  12. Florian, M. and Sorensen, J.D. (2015), "Wind turbine blade life-time assessment model for preventive planning of operation and maintenance", J. Marine Sci. Eng., 3(3), 1027-1040. https://doi.org/10.3390/jmse3031027
  13. Guida, M. and Penta, F. (2015), "A gamma process model for the analysis of fatigue crack growth data", Eng. Fract. Mech., 142(2), 21-49. https://doi.org/10.1016/j.engfracmech.2015.05.027
  14. Hu, W., Choi, K.K. and Cho, H. (2016a), "Reliability-based design optimization of wind turbine blades for fatigue life under dynamic wind load uncertainty", Struct. Multidisc. Optim., 54(4), 953-970. https://doi.org/10.1007/s00158-016-1462-x
  15. Hu, W., Choi, K.K., Zhupanska, O. and Buchholz, J.H. (2016b), "Integrating variable wind load, aerodynamic and structural analyses towards accurate fatigue life prediction in composite wind turbine blades", Struct. Multidisc. Optim., 53(3), 375-394. https://doi.org/10.1007/s00158-015-1338-5
  16. Hu, W., Park, D. and Choi, D. (2013), "Structural optimization procedure of a composite wind turbine blade for reducing both material cost and blade weight", Eng. Optim., 45(12), 1469-1487. https://doi.org/10.1080/0305215X.2012.743533
  17. Huang, T.L., Zhou, H., Chen, H.P. and Ren, W.X. (2016), "Stochastic modelling and optimum inspection and maintenance strategy for fatigue affected steel bridge members", Smart Struct. Syst., 18(3), 569-584. https://doi.org/10.12989/sss.2016.18.3.569
  18. Jureczko, M.E.Z.Y.K., Pawlak, M. and Mezyk, A. (2005), "Optimisation of wind turbine blades", J. Mater. Pr. Technol., 167(2), 463-471. https://doi.org/10.1016/j.jmatprotec.2005.06.055
  19. Kim, S., Frangopol, D.M. and Soliman, M. (2013), "Generalized probabilistic framework for optimum inspection and maintenance planning", J. Struct. Eng., 139(3), 435-447. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000676
  20. Li, S. and Lu, Z.R. (2015), "Multi-swarm fruit fly optimization algorithm for structural damage identification", Struct. Eng. Mech., 56(3), 409-422. https://doi.org/10.12989/sem.2015.56.3.409
  21. Liu, Y. and Shu, D.W. (2015), "Effects of edge crack on the vibration characteristics of delaminated beams", Struct. Eng. Mech., 53(4), 767-780. https://doi.org/10.12989/sem.2015.53.4.767
  22. Marquez-Dominguez, S. and Sorensen, J.D. (2012), "Fatigue reliability and calibration of fatigue design factors for offshore wind turbines", Energ., 5(6), 1816-1834. https://doi.org/10.3390/en5061816
  23. McMillan, D. and Ault, G.W. (2007), "Quantification of condition monitoring benefit for offshore wind turbines", Wind Eng., 31(4), 267-285. https://doi.org/10.1260/030952407783123060
  24. Miner, M.A. (1945), "Cumulative damage in fatigue", J. Appl. Mech., 12(3), 159-164.
  25. Montesano, J., Chu, H. and Singh, C.V. (2016), "Development of a physics-based multi-scale progressive damage model for assessing the durability of wind turbine blades", Compos. Struct., 141(6), 50-62 https://doi.org/10.1016/j.compstruct.2016.01.011
  26. Nielsen, J.J. and Sorensen, J.D. (2011), "On risk-based operation and maintenance of offshore wind turbine components", Reliab. Eng. Syst. Saf., 96(1), 218-229. https://doi.org/10.1016/j.ress.2010.07.007
  27. Paris, P.C. and Erdogan, F. (1963), "A critical analysis of crack propagation laws", J. Bas. Eng., 85(4), 528-533. https://doi.org/10.1115/1.3656900
  28. Pugno, N., Ciavarella, M., Cornetti, P. and Carpinteri, A. (2006), "A generalized Paris' law for fatigue crack growth", J. Mech. Phys. Solid., 54(7), 1333-1349. https://doi.org/10.1016/j.jmps.2006.01.007
  29. Reifsnider, K.L. (2012), Fatigue of Composite Materials, Vol. 4, Elsevier, Blacksburg, VA, USA.
  30. Shafiee, M., Finkelstein, M. and Berenguer, C. (2015), "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks", Reliab. Eng. Syst. Saf., 142(44), 463-471. https://doi.org/10.1016/j.ress.2015.05.001
  31. Shi, W., Han, J., Kim, C., Lee, D., Shin, H. and Park, H. (2015), "Feasibility study of offshore wind turbine substructures for southwest offshore wind farm project in Korea", Renew. Energy, 74(44), 406-413. https://doi.org/10.1016/j.renene.2014.08.039
  32. Sierra-Perez, J., Torres-Arredondo, M.A. and Guemes, A. (2016), "Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison", Compos. Struct., 135(15), 156-166. https://doi.org/10.1016/j.compstruct.2015.08.137
  33. Sorensen, J.D. (2009), "Framework for risk-based planning of operation and maintenance for offshore wind turbines", Wind Energy, 12(5), 493-506. https://doi.org/10.1002/we.344
  34. Sun, Q., Dui, H.N. and Fan, X.L. (2014), "A statistically consistent fatigue damage model based on Miner's rule", Int. J. Fatig., 69(2), 16-21. https://doi.org/10.1016/j.ijfatigue.2013.04.006
  35. Van Noortwijk, J.M. (2009), "A survey of the application of gamma processes in maintenance", Reliab. Eng. Syst. Saf., 94(1), 2-21. https://doi.org/10.1016/j.ress.2007.03.019
  36. Van Noortwijk, J.M. and Frangopol, D.M. (2004), "Two probabilistic life-cycle maintenance models for deteriorating civil infrastructures", Probab. Eng. Mech., 19(4), 345-359. https://doi.org/10.1016/j.probengmech.2004.03.002
  37. Van Noortwijk, J.M., van der Weide, J.A., Kallen, M.J. and Pandey, M.D. (2007), "Gamma processes and peaks-over-threshold distributions for time-dependent reliability", Reliab. Eng. Syst. Saf., 92(12), 1651-1658. https://doi.org/10.1016/j.ress.2006.11.003
  38. Wu, F. and Yao, W. (2010), "A fatigue damage model of composite materials", Int. J. Fatig., 32(1), 134-138. https://doi.org/10.1016/j.ijfatigue.2009.02.027
  39. Yang, J., Peng, C., Xiao, J., Zeng, J., Xing, S., Jin, J. and Deng, H. (2013a), "Structural investigation of composite wind turbine blade considering structural collapse in full-scale static tests", Compos. Struct., 97(2), 15-29. https://doi.org/10.1016/j.compstruct.2012.10.055
  40. Yang, W., Court, R. and Jiang, J. (2013b), "Wind turbine condition monitoring by the approach of SCADA data analysis", Renew. Energy, 53(44), 365-376. https://doi.org/10.1016/j.renene.2012.11.030
  41. Yu, L. and Zhu, J.H. (2015), "Nonlinear damage detection using higher statistical moments of structural responses", Struct. Eng. Mech., 54(2), 221-237. https://doi.org/10.12989/sem.2015.54.2.221
  42. Zhang, C. and Chen, H.P. (2016a), "A stochastic model for damage evolution of mode II delamination fatigue of composite wind turbine blades", The Fifth International Symposium on Life-Cycle Civil Engineering (IALCCE), Delft, Netherlands, October.
  43. Zhang, C. and Chen, H.P. (2016b), "Structural health monitoring for fatigue analysis of wind turbine composite blades under wind load uncertainty", The Sixth workshop on Civil Structural Health monitoring (CSHM-6), Belfast, UK, June.
  44. Zhang, C., Chen, H.P. and Huang, T.L. (2016a), "Stochastic modelling of lifecycle delamination damage evolution of composite blades of wind turbines", International Conference on Smart Infrastructure and Construction (ICSIC 2016), Cambridge, UK, May.
  45. Zhang, M., Tan, B. and Xu, J. (2016b), "Smart fatigue load control on the large-scale wind turbine blades using different sensing signals", Renew. Energy, 87(10), 111-119. https://doi.org/10.1016/j.renene.2015.10.011
  46. Zhou, H.F., Dou, H.Y., Qin, L.Z., Chen, Y., Ni, Y.Q. and Ko, J.M. (2014), "A review of full-scale structural testing of wind turbine blades", Renew. Sustain. Energy Rev., 33(17), 177-187. https://doi.org/10.1016/j.rser.2014.01.087