Abstract
Shock tube is a crucial device for the dynamic calibration of pressure sensors in aerospace and defense fields. Accurate measurement of the shock wave pressure (SWP) in the shock tube and reliable evaluation of the measurement uncertainty are the basis for improving the calibration accuracy of pressure sensors. However, the repeated measurement results of the SWP in shock tube have typical features of time-varying and small samples, leading to a poor reliability of the measurement uncertainty evaluation. To address this issue, an improved method is proposed to accurately evaluate the time-varying uncertainty of the SWP measurement results with small samples in an aerospace shock tube. The time-varying SWP measurement signals are firstly decomposed into four components by the multicomponent extraction based on signal decomposition algorithms. For the repeated SWP measurement data with small samples, a sample size expansion based on the bootstrap method is presented to reduce the mean estimation error of the four components. A time-varying uncertainty evaluation model of the four components is established based on the conjugate prior Bayesian theory. The reliable evaluation of the time-varying uncertainty of the SWP measurements is finally realized according to the uncertainty propagation principle. Simulations and the SWP measurement experiments in an aerospace shock tube are carried out to validate the performance of the proposed method. The results show that the proposed method works well in the time-varying uncertainty evaluation of the SWP measurements with small samples. Furthermore, the comparative experiments demonstrate the superiority of the proposed method over the Bessel method and the Bayesian method for the SWP measurement uncertainty evaluation in both accuracy and reliability.
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