Application of Morlet wavelet in the stress-time history editing of horizontal axis wind turbine blades

This article presents a novel method in extracting fatigue damage from the stress-time history of the horizontal axis wind turbine blades. A novel method based on wavelet transform (WT) is proposed to shorten the length of the stress-time history. Based on Morlet wavelet (Morl), WT is taken to the stress-time history to generate a plot of accumulative power spectral density (AccPSD) distribution with time. The variation of fatigue damage with AccPSD levels is studied to determine the cutoff level which is controlled by the differences in the global signal statistics (mean stress, root-mean-square and kurtosis). WT uses the cutoff level as a criterion in identifying fatigue damage parts at time locations of the stress-time history. Then, the fatigue damage parts are extracted from the original stress-time history and concatenated to form the edited stress-time history. In addition, Time Correlated Fatigue Damage (TCFD), which is an existing used by commercial software, is used to study the effectiveness of WT. The comparison of the differences in fatigue damage and stress-time history length produced by TCFD and WT is performed. It is found that the differences in fatigue damage of TCFD and Morl are +0.076% and +0.013%. The lengths of the edited stress-time history provided by TCFD and Morl are 89.8% and 82.3% of the original length, respectively. The results suggest that not only does WT improve accuracy of fatigue damage retained in the edited stress-time history, but also it provides the length of the edited stress-time history shorter than TCFD does. Also, the results suggest that WT is a useful method for performing accelerated fatigue tests. Finally, WT is suggested as an alternative technique in fatigue durability study, especially for the field of wind turbine engineering.