scholarly journals Detection of Damage in OperatingWind Turbines by Signature Distances

Author(s):  
Dylan D. Chase ◽  
Kourosh Danai ◽  
Mathew A. Lackner ◽  
James F. Manwell

Wind turbines operate in the atmospheric boundary layer and are subject to complex random loading. This precludes using a deterministic response of healthy turbines as the baseline for identifying the effect of damage on the measured response of operating turbines. In the absence of such a deterministic response, the stochastic dynamic response of the tower to a shutdown maneuver is found to be affected distinctively by damage in contrast to wind. Such a dynamic response, however, cannot be established for the blades. As an alternative, the estimate of blade damage is sought through its effect on the third or fourth modal frequency, each found to be mostly unaffected by wind. To discern the effect of damage from the wind effect on these responses, a unied method of damage detection is introduced that accommodates different responses. In this method, the dynamic responses are transformed to surfaces via continuous wavelet transforms to accentuate the effect of wind or damage on the dynamic response. Regions of signicant deviations between these surfaces are then isolated in their corresponding planes to capture the change signatures. The image distances between these change signatures are shown to produce consistent estimates of damage for both the tower and the blades in presence of varying wind eld proles.

2005 ◽  
Vol 162 (5) ◽  
pp. 843-855 ◽  
Author(s):  
M. Kulesh ◽  
M. Holschneider ◽  
M. S. Diallo ◽  
Q. Xie ◽  
F. Scherbaum

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. G81-G92
Author(s):  
P. Cavalier ◽  
D. W. O’Hagan

Potential field characterization aims at determining source depths, inclination, and type, preferably without a priori information. For ideal sources, the type is often defined from the field’s degree of homogeneity, derived from its expression in the space domain. We have developed a new shape descriptor for potential field source functions, stemming from spectral-domain parameters, which manifest clearly when using continuous wavelet transforms (CWTs). We generalize the use of the maximum wavelet coefficient points in the CWT diagram for the analysis of all types of potential fields (gravity, magnetic, and self-potential). We interpret the CWT diagram as a similarity diagram between the wavelet and the analyzed signal, which has fewer limitations than its interpretation as a weighted and upward-continued field projection. We develop new formulas for magnetic source depth prediction, as well as for effective inclination estimation, using various kinds of wavelets. We found that the potential field source functions exhibit precise behaviors in the CWT analysis that can be predicted using a single parameter [Formula: see text], which is related to their Fourier transforms. This parameter being scale and rotation-invariant can be used as a source-body shape descriptor similar to the commonly used structural index (SI). An advantage of the new descriptor is an increased level of discrimination between sources because it takes different values to describe the horizontal or the vertical cylinder structures. Our approach is illustrated on synthetic examples and real data. The method can be applied directly with the native form of the CWT without scaling factor modification, negative plane diagram extension, or downward plotting. This framework offers an alternative to existing wavelet-like projection methods or other classic deconvolution techniques relying on SI for determining the source depth, dip, and type without a priori information, with an increased level of differentiation between source structures thanks to the new shape descriptor.


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