Advantages of the non-stationary approach: test on eddy current signals

Conventional signal processing is often unsuitable for the interpretation of intrinsically non-stationary signals, such as surveillance or non destructive testing signals. In these cases, ''advanced'' methods are required. This report presents two applications of non-stationary signal processing methods to the complex signals obtained in eddy current non destructive testing of steam generator tubes. The first application consists in segmenting the absolute channel, which can be likened to a piecewise constant signal. The Page-Hinkley cumulative sum algorithm is used, enabling detection of unknown mean amplitude jumps in a piecewise constant signal disturbed by a white noise. Results are comparable to those obtained with the empirical method currently in use. As easy to implement as the latter, the Page-Hinkley algorithm has the added advantage of being well formalized and of identifying whether the jumps in mean are positive or negative. The second application concerns assistance in detecting characteristic fault transients in the differential channels, using the continuous wavelet transform. The useful signal and noise spectra are fairly close, but not strictly identical. With the continuous wavelet transform, these frequency differences can be turned to account. The method was tested on synthetic signals obtained by summing noise and real defect signals. Using the continuous wavelet transform reduces the minimum signal-to-noise ratio by 5 dB for detection of a transient as compared with direct detection on the original signal. Finally, a summary of non-stationary methods using our data is presented. The two investigations described confirm that non-stationary methods may be considered as interesting signal and image analysis tools, as an efficient complement to conventional methods. (author). 24 figs., 13 refs