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Adaptation of methods for cyclo-stationary processes for noisy structural health data
Fischer, Cyril ; Bayer, Jan ; Náprstek, Jiří ; Urushadze, Shota
In structural health analysis, various techniques, including indirect measurement via monitoring vehicles, often yield data with significant randomness and insufficient frequency separation. Conversely, the desired attributes under scrutiny are periodic in nature. Thus, methodologies designed to identify cyclo-stationary properties within noisy data can be adapted for such scenarios, assuming an adequate length of the recorded data.

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