Analysis of characteristic parameters in nonideal shock wave data: wavelet thresholds

Qiang Xu; Cong Jin

doi:10.1117/12.484813

1 April 2003 Analysis of characteristic parameters in nonideal shock wave data: wavelet thresholds

Qiang Xu, Cong Jin

Proceedings Volume 5102, Independent Component Analyses, Wavelets, and Neural Networks; (2003) https://doi.org/10.1117/12.484813
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

A set of experiment was conducted to study the initial shock wave, which is generated in early launching stage and harmful to human and equipment. Profile of pressure-time history consists of shock wave and rocket noise, which are the two inherent flow features of rocket exhaust flow. This makes it difficult to calculate the typical parameters such as peak overpressure, positive duration and waveform coefficient. Thus the intensity of shock wave is hard to determine by traditional methods. Wavelet threshold de-noise is used in this paper to detect shock wave profile from noise. Daubechies and Symlets wavelet families are compared in threshold treating of shock wave data. Wavelet threshold plus a priori knowledge makes the initial shock wave well detected from rocket noise. Three characteristic parameters of shock wave are determined and compared in the study. The results show that low order wavelet with small support width can keep singularity of shock wave better.This helps to understand the performence of initial shock wave of rocket jet in engineering application.

Citation Download Citation

Qiang Xu and Cong Jin "Analysis of characteristic parameters in nonideal shock wave data: wavelet thresholds", Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); https://doi.org/10.1117/12.484813

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