scholarly journals In-Flight Isolation of Degraded Engine Components by Shape Comparison of Transient Outputs

Author(s):  
Jeffrey C. Simmons ◽  
Kourosh Danai

A direct method of aircraft engine health monitoring is introduced that can isolate a degraded engine component in-flight. The method utilizes continuous wavelet transformations of transient engine sensory data to represent their shape attributes in the time scale domain. This enables contrasting the shapes of the current engine outputs with those previously collected from the engine. Continuous wavelet transforms also provide enhanced delineation of the engine transients in the time scale domain. This enables identification of minute differences between the outputs affected by component degradations and between the sensitivities of modeled outputs with respect to the health parameters or components. The presence of these differences is used in this method as evidence of degradation effects on the outputs and/or parameters or components effects on the outputs. The effectiveness of the proposed method is evaluated in engine simulations. The results indicate that with the suite of outputs currently available on-board 70% to 96% of the degraded components simulated can be isolated for new and older engines.

Author(s):  
Da Jun Chen ◽  
Wei Ji Wang

Abstract As a multi-resolution signal decomposition and analysis technique, the wavelet transforms have been already introduced to vibration signal processing. In this paper, a comparison on the time-scale map analysis is made between the discrete and the continuous wavelet transform. The orthogonal wavelet transform decomposes the vibration signal onto a series of orthogonal wavelet functions and the number of wavelets on one wavelet level is different from those on the other levels. Since the grids are unevenly distributed on the time-scale map, it is shown that a representation pattern of a vibration component on the map may be significantly altered or even be broken down into pieces when the signal has a shift along the time axis. On contrary, there is no such uneven distribution of grids on the continuous wavelet time-scale map, so that the representation pattern of a vibration signal component will not change its shape when the signal component shifts along the time axis. Therefore, the patterns in the continuous wavelet time-scale map are more easily recognised by human visual inspection or computerised automatic diagnosis systems. Using a Gaussian enveloped oscillation wavelet, the wavelet transform is capable of retaining the frequency meaning used in the spectral analysis, while making the interpretation of patterns on the time-scale maps easier.


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

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