|Table of Contents|

[1] Zhuang Zhemin, Zhang Jing, Huang Weiyi,. Adaptive Volterra series model for nonlinear sensor compensation [J]. Journal of Southeast University (English Edition), 2004, 20 (3): 286-288. [doi:10.3969/j.issn.1003-7985.2004.03.005]
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Adaptive Volterra series model for nonlinear sensor compensation()
基于Volterra模型的非线性传感器补偿研究
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
20
Issue:
2004 3
Page:
286-288
Research Field:
Automation
Publishing date:
2004-09-30

Info

Title:
Adaptive Volterra series model for nonlinear sensor compensation
基于Volterra模型的非线性传感器补偿研究
Author(s):
Zhuang Zhemin1;  Zhang Jing2;  Huang Weiyi3
1Department of Electronics Engineering, Shantou University, Shantou 515063, China
2Department of Electrical Engineering, Southeast University, Nanjing 210096, China
3Department of Instrument Science and Technology, Southeast University, Nanjing 210096, China
庄哲民1;  张靖2;  黄惟一3
1汕头大学电子工程系, 汕头 515063; 2东南大学电气工程系, 南京 210096; 3东南大学仪器科学与工程系, 南京 210096
Keywords:
sensor;  Volterra model;  non-linearity
传感器;  Volterra 模型;  非线性
PACS:
TP212
DOI:
10.3969/j.issn.1003-7985.2004.03.005
Abstract:
A novel performance enhancement method of nonlinear sensor based on the Volterra series model is proposed. The Volterra series model, which is considered a nonlinear filter that can reduce sensor noise, presents an effective way for modeling and compensating a nonlinear sensor. In the experiment, the low accuracy pressure sensor MPX10 was used as the actual object, and higher accuracy sensor MPX2010 was used as the reference to provide the necessary teaching data for training the Volterra model. The simulation shows that the accuracy of MPX10 changes from 0. 354-0. 42 to 0. 041-0. 053 after the Volterra filter has been applied. Obviously this scheme can effectively improve the sensor performance. Moreover, the scheme provides greater accuracy and environmental suitability for a nonlinear sensor.
提出了一种基于Volterra系数模型, 用于提高非线性传感器性能的新方法. Volterra模型可作为一个非线性滤波器用于降低传感器的噪声, 并可对传感器进行非线性补偿. 在实验中, 采用精度较低的压力传感器MPX10作为实验传感器, 采用具有较高精度的传感器MPX2010产生构建Volterra模型的训练学习数据. 仿真实验表明, 利用Volterra 模型进行滤波, 传感器MPX10的精度由原来的0. 354~0. 42 变为 0. 041~0. 053. 由此可见该方法可有效地提高传感器的性能与精度, 并具有较高的环境适应能力.

References:

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[2] Mikulik Pavol, Saliga Jan. Volterra filtering for integrating ADC error correction based on an a priori error model [J]. IEEE Transactions on Instrumentation and Measurement, 2002, 51(4): 870-875.
[3] Broersen Piet M T. Automatic spectral analysis with time series model[J]. IEEE Transactions on Instrumentation and Measurement, 2002, 51(2): 211-216.
[4] Takeichi Kaichiro, Furukawa Toshihiro. A fast algorithm of Volterra adaptive filters[A]. In: IEEE International Conference on Acoustics, Speech and Signal Processing[C]. Orlando, Florida, 2002, 4: 4167-4171.
[5] Fang Y W, Jiao L C, Zhang X D, et al. On the convergence of Volterra filter equalizers using a pth-order inverse approach [J]. IEEE Transactions on Signal Processing, 2001, 49(8): 1734-1744.
[6] Nemeth J G, Kollar I, Schoukens J. Identification of Volterra kernels using interpolation[J]. IEEE Transactions on Instrumentation and Measurement, 2002, 51(4): 770-775.

Memo

Memo:
Biography: Zhuang Zhemin(1965—), male, doctor, associate professor, zmzhuang@stu.edu.cn.
Last Update: 2004-09-20