The necessity of the green transition is today more extensive than ever before. Consequently, wind turbines along with wind farms are compelled to grow rapidly to encounter the obliga- tion of a sustainable source of energy. Facing extensive expenses associated with maintenance, the exploration of a well-functional Structural Health Monitoring (SHM) system is crucial. Hence, by utilizing data from a laboratory-scale wind turbine blade in a controlled environ- ment, numerous Damage Sensitive Features (DSFs) along with several techniques to mitigate the effect of Environmental and Operational Variability (EOV) are investigated. In this work, we consider DSFs originating from Vector Auto-Regressive (V AR) models, including natural frequencies and damping ratios as a physical quantity, and the parameters of the models as a non-physical quantity. The inevitable obscuring of the DSFs caused by EOV is mitigated by utilizing two distinct approaches. Bayesian non-linear regression models and the Princi- pal Component Analysis (PCA) methodology, designated as an explicit and implicit approach respectively. In addition, a novel approach combining the implicit and explicit methodology is proposed. Through a comparative analysis, various considerations of interest were derived. The applicability of the various DSFs was measured in terms of correctly detected damages utilizing the multivariate squared Mahalanobis distance as a one-class classifier. The derivation was that the usage of the non-physical quantity did show prominent applicability. Generally, the combined implicit-explicit methodology showed superior efficiency. Despite the acknowl- edgement regarding complicating aspects entering an uncontrolled environment, the conviction of efficiency is preserved yet reduced to some extent. ii Contents Preface i Abstract ii Introduction 1 1 Methodology 6 1.1 Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 Damage Sensitive Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.2.1 Vector Auto-Regressive models . . . . . . . . . . . . . . . . . . . . . 10 1.2.1.1 Selection of suitable model structure . . . . . . . . . . . . . 13 1.2.1.2 Extracting the natural frequencies of interest . . . . . . . . . 15 1.3 Mitigating the effect of Environmental and Operational Variability . . . . . . . 18 1.3.1 Explicit method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.3.1.1 Bayesian regression . . . . . . . . . . . . . . . . . . . . . . 18 1.3.1.2 Assessing the performance . . . . . . . . . . . . . . . . . . 21 1.3.1.3 Regression matrix . . . . . . . . . . . . . . . . . . . . . . . 22 1.3.1.4 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 1.3.2 Implicit method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.3.2.1 Principal Component Analysis . . . . . . . . . . . . . . . . 27 1.3.2.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.3.3 Combined method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.4 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 1.5 Damage detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 iii 2 Results 35 2.1 Natural Frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 2.1.1 Explicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 36 2.1.2 Implicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.1.3 Combined compensation . . . . . . . . . . . . . . . . . . . . . . . . . 42 2.1.4 No compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2.2 Damping Ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 2.2.1 Explicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 47 2.2.2 Implicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.2.3 Combined compensation . . . . . . . . . . . . . . . . . . . . . . . . . 52 2.2.4 No compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2.3 AR coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 2.3.1 Explicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 56 2.3.2 Implicit compensation . . . . . . . . . . . . . . . . . . . . . . . . . . 59 2.3.3 Combined compensation . . . . . . . . . . . . . . . . . . . . . . . . . 62 2.3.4 No compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 2.4 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3 Discussion 68 3.1 Natural frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.2 Damping ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 3.3 AR coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.4 Common discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Conclusion 75 Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Bibliography 79 A Appendix 84 A.1 Natural frequency