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

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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.

Key words： shock wave pressure sensor assembly dynamic characteristic BP neural network segment modeling

Received: 29 March 2016 Published: 15 August 2017

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	Articles by authors
	Yang Fan1
	Kong De-ren1
	Kong Lin2
	Wang Fang1

Cite this article:

Yang Fan1,Kong De-ren1,Kong Lin2, et al. Study on Segment Modeling Method for the Dynamic Characteristics of Shock Wave Pressure Sensor Assembly Based on BP Neural Network[J]. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(16): 155-158.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2017/V36/I16/155

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