Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.
A new addition to the statistical Hermite moment model of extremes is introduced for use on processes with high skewness and near-Gaussian kurtosis. The monotone limits of the existing model are expressed as ellipses in response moment space and a new methodology is introduced that combines hardening and softening models to overcome these limits. The result is that any fractile of a distribution described by its first four statistical moments can be transformed to or from the Gaussian. An example application to a tension leg platform is presented.
The air gap response of a specific semi-submersible platform subjected to irregular waves is considered. Detailed model tests for this structure are studied in depth. Using time-histories of both motions and air gap, statistical analyses both for the absolute near-structure wave elevation (with respect to a fixed observer), and the relative wave elevation (with respect to the moving structure) are performed. Statistics of wave crest amplification, due to diffraction, are established. Corresponding amplification factors are derived from linear diffraction theory, and the results of theory and observations are critically compared.
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