Abstract：Affected by the parasitic in explosion field, appropriate measures need to be taken to reform the shock wave pressure sensor. To research the dynamic characteristics of shock wave pressure sensor assembly, based on double-diaphragm shock tube, the pressure sensor assembly of the shock wave can be calibrated and give a step response signal; Then the dynamic characteristics of the sensor assembly’s nonparametric model can be obtained by differential method; According to the non-parametric model’s variation of the shock wave pressure sensor assembly’s dynamic characteristics, the dynamic characteristics should be reasonably segmented in frequency domain, and each part of the dynamic characteristics can be modeled based on BP neural network; Through analysis and comparison of an examples, it can be proved that segment modeling method based on BP neural network can effectively improve the accuracy and efficiency of modeling.
杨凡1，孔德仁1，孔霖2，王芳1. 基于BP神经网络的冲击波压力传感器组件动态特性分段建模方法研究[J]. 振动与冲击, 2017, 36(16): 155-158.
Yang Fan1, Kong De-ren1, Kong Lin2, Wang Fang1. Study on Segment Modeling Method for the Dynamic Characteristics of Shock Wave Pressure Sensor Assembly Based on BP Neural Network. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(16): 155-158.
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