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基于系统辨识方法的D-dot传感器的实验室校准

Laboratory Calibration of D-dot Sensor Based on System Identification Method.

作者信息

Wang Ke, Duan Yantao, Shi Lihua, Qiu Shi

机构信息

National Key Laboratory on Electromagnetic Environment Effects and Electro-Optical Engineering, Army Engineering University of PLA, Nanjing 210007, China.

出版信息

Sensors (Basel). 2019 Jul 24;19(15):3255. doi: 10.3390/s19153255.

DOI:10.3390/s19153255
PMID:31344862
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6696517/
Abstract

D-dot sensors can realize the non-contact measurement of transient electric fields, which is widely applied to electromagnetic pulse (EMP) measurements with characteristics of the wide frequency band, high linearity, and good stability. In order to achieve accurate calibration of D-dot sensors in the laboratory environment, this paper proposed a new calibration method based on system identification. Firstly, the D-dot sensor can be considered as a linear time-invariant (LTI) system under corner frequency, thus its frequency response can be characterized by the transfer function of a discrete output error (OE) model. Secondly, based on the partial linear regression of the transfer function curve, the sensitivity coefficient of the D-dot sensor is obtained. By increasing the influence weight of low-frequency components, this proposed method has better calibration performance when the waveform is distorted in the time domain, and can artificially adapt to the operating frequency range of the sensor at the same time.

摘要

D-dot传感器可以实现瞬态电场的非接触测量，广泛应用于具有宽频带、高线性度和良好稳定性等特点的电磁脉冲（EMP）测量中。为了在实验室环境中实现D-dot传感器的精确校准，本文提出了一种基于系统辨识的新校准方法。首先，在转折频率下，D-dot传感器可被视为线性时不变（LTI）系统，因此其频率响应可以用离散输出误差（OE）模型的传递函数来表征。其次，基于传递函数曲线的偏线性回归，得到D-dot传感器的灵敏度系数。通过增加低频分量的影响权重，该方法在时域波形失真时具有更好的校准性能，同时能人为适应传感器的工作频率范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/2a3c99163b96/sensors-19-03255-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/d7a2108d19f2/sensors-19-03255-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/843cadc7362b/sensors-19-03255-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/28241082e490/sensors-19-03255-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/08976a7c4e74/sensors-19-03255-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/85442f66f903/sensors-19-03255-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/7efa6a4a3bd3/sensors-19-03255-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/f640f4f17aa8/sensors-19-03255-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/335079900c60/sensors-19-03255-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/8dfd3b307b64/sensors-19-03255-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/2a3c99163b96/sensors-19-03255-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/d7a2108d19f2/sensors-19-03255-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/843cadc7362b/sensors-19-03255-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/28241082e490/sensors-19-03255-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/08976a7c4e74/sensors-19-03255-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/85442f66f903/sensors-19-03255-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/7efa6a4a3bd3/sensors-19-03255-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/f640f4f17aa8/sensors-19-03255-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/335079900c60/sensors-19-03255-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/8dfd3b307b64/sensors-19-03255-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b72/6696517/2a3c99163b96/sensors-19-03255-g010.jpg

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