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激波管是一种关键的压力传感器动态校准装置,但是由于其输出的不稳定性,使得被校准压力传感器的输出数据常常难以直接用于动态建模,且所建模型的准确性也难以表征.提出一种用于激波管校准压力传感器的动态参数估计方法.首先使用基于信息方法处理被校准压力传感器在阶跃激励下的输出数据,得到最优估计值序列、上界序列和下界序列;然后,对所得最优估计值序列、上界序列和下界序列分别进行白化滤波和差分建模,得到最优估计模型、上界模型和下界模型;之后对各个模型进行求解,最优估计模型得出被校准压力传感器的最优特征指标,上界模型和下界模型所得结果构成最优性能指标的估计区间.选用恩德福克200系列压阻传感器进行激波管校准实验,得出时域动态指标的相对误差小于8.17%,频域动态指标相对误差小于9.15%;所有指标均100%位于求得的估计区间内.
Shock tube is a key dynamic calibration device of pressure sensor, but due to the instability of its output, the output data of the calibrated pressure sensor is often difficult to use directly for dynamic modeling, and the accuracy of the model is difficult to characterize A dynamic parameter estimation method for shock tube calibration pressure sensor is proposed.Firstly, the output data of the calibrated pressure sensor under step excitation is processed based on information method to obtain the optimal estimation sequence, the upper bound sequence and the lower bound sequence Then, the optimal estimation sequence, the upper bound sequence and the lower bound sequence are respectively subjected to whitening filtering and differential modeling to obtain the optimal estimation model, the upper bound model and the lower bound model; and then the models are solved and the optimal estimation model The optimal characteristic index of the calibrated pressure sensor is obtained, and the results of the upper bound model and the lower bound model form the estimation interval of the optimal performance index.Experiments of shock tube calibration with 200 series piezoresistive sensors are carried out, and the time domain dynamics The relative error of the indicator is less than 8.17% and the relative error of the frequency domain dynamic indicator is less than 9.15%. All the indicators are 100% within the obtained estimation Intra.