Dynamic pressure reconstruction of shock tube based on inverse sensing network model identification

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (23) : 223-230.

LI Yongsheng,YAO Zhenjian,LIU Chen,DING Yifan

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Abstract

A reconstruction method of shock tube dynamic pressure is proposed based on inverse sensing network model identification. First, the dynamic response signal of pressure sensor is decomposed into a series of components with different frequency bands based on empirical mode decomposition. Then, the ringing component and trend component are identified by correlation coefficient and ring amplitude ratio indexes to construct the training set and test set of the inverse sensing network model. Finally, the inverse sensing network model of pressure sensor is established based on the training and testing of Bi-directional long short-term memory neural network, and the shock tube dynamic pressure is reconstructed. Simulation experiments and shock tube measurement experiments are conducted to verify the performance of the proposed method. The simulation results show that the RMSE and MAPE of the reconstructed dynamic pressure signal are far less than those obtained by the traditional trend estimation method, and the values are reduced by 2 and 5 times respectively compared with those obtained by the LSTM method. The robustness of the proposed method is verified in the simulation experiments of pressure sensors with different orders. The applicability of this method is verified by comparing the accuracy of dynamic pressure reconstruction for different pressure sensors. The experimental results show that the RMSE and MAPE of the model training and test output are 0.016V and 0.0036% as well as 0.0025V and 0.062%, respectively. The average relative error of the reconstructed dynamic pressure is about 2.14% in the stable interval.

Key words

shock tube / pressure sensor / Empirical Mode Decomposition / Bi-directional Long Short-Term Memory neural network / dynamic pressure

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LI Yongsheng,YAO Zhenjian,LIU Chen,DING Yifan. Dynamic pressure reconstruction of shock tube based on inverse sensing network model identification[J]. Journal of Vibration and Shock, 2023, 42(23): 223-230

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