[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()

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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

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

Keywords:

sensor;  Volterra model;  non-linearity

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.

References:

[1] Yeary M B, Griswold N C. Adaptive IIR filter design for single sensor applications [J]. IEEE Transactions on Instrumentation and Measurement, 2002, 51(2): 259-267.
[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.

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