A High Precision Software Compensation Algorithm for Silicon Piezoresistive Pressure Sensor

WU Tianshu; CHEN Shuyu; WU Peng; NIE Shaozhong

doi:10.1049/cje.2019.05.001

Volume 28 Issue 4

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WU Tianshu, CHEN Shuyu, WU Peng, et al., “A High Precision Software Compensation Algorithm for Silicon Piezoresistive Pressure Sensor,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 748-753, 2019, doi: 10.1049/cje.2019.05.001

Citation:

WU Tianshu, CHEN Shuyu, WU Peng, et al., “A High Precision Software Compensation Algorithm for Silicon Piezoresistive Pressure Sensor,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 748-753, 2019, doi: 10.1049/cje.2019.05.001

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A High Precision Software Compensation Algorithm for Silicon Piezoresistive Pressure Sensor

doi: 10.1049/cje.2019.05.001

1.
College of Computer Science, Chongqing University, Chongqing 400044, China;
2.
Chongqing Chuanyi Automation Co., Ltd., Chongqing 401121, China

Funds: This work is supported by the National Key R&D Program of China (No.2018YFB2003900), the National High Technology Research and Development Program of China (No.2012AA041201), and the National Natural Science Foundation of China (No.61272399, No.61572090).

More Information

Corresponding author: NIE Shaozhong (corresponding author) was born in 1965. He received the B.sc. degree in control science from Shenyang University of Technology. He is a senior engineer in Chongqing Chuanyi Automation Co., Ltd. His research interests include pressure sensor and intelligent instrument. (Email:nszsic@126.com)
Received Date: 2018-05-18
Rev Recd Date: 2018-08-11
Publish Date: 2019-07-10

Abstract

Abstract

There are generally zero drift, sensitivity drift and nonlinear error in silicon piezoresistive pressure sensors due to the inherent characteristics of semiconductor materials. It is necessary to compensate and correct the errors produced so as to meet the requirements of measurement accuracy. In order to further improve the compensation precision, based on the research of various basic software compensation methods, a surface fitting compensation algorithm based on least square method is designed, and the software is implemented on the Visual Basic platform. The experimental results show that the zero drift, sensitivity drift and nonlinear error is effectively eliminated, and the output precision of the sensor is greatly improved.
- High precision compensation algorithm,
- Least square method,
- Surface fitting

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References(18)

References

Z.Y. Hua and D.C. Xu, “Realization of error correction method by FPGA for Si piezoresistive pressure sensor”, Transducer and Microsystem Technologies, Vol.36, No.2, pp.101–106, 2017.

S.Z. He, “Research on overload protection and temperature drift compensation of high-precision MEMS silicon differential pressure sensor”, Ph.D. Thesis, South China University of Technology, Guangzhou, China, 2015. (in Chinese)

J.Y. GUO, X.T. CHANG and Q. Yue, “Study on curved fitting model using GPS and leveling in local area”, Transactions of Nonferrous Metals Society of China, Vol.15, No.S1, pp.140–144, 2005.

M. Mese and P.P. Vaidyanathan, “Look-up table (LUT) method for inverse halftoning and for image halftoning”, IEEE Transactions on Image Processing, Vol.10, No.10, pp.1566–1578, 2001.

C.X. Ouyang, “Research on high precision temperature compensation technology of silicon piezoresistive pressure sensor”, Ph.D. Thesis, University of Electronic Science and technology, Chengdu, China, 2015. (in Chinese)

M. Zeng, Y. Zhang and J. Huan, “A New Linear Interpolation Algorithm”, proc. of International Conference on Computer Engineering, Information Science & Application Technology, Guilin, China, pp.163–170, 2016.

H.W. Ji and Y.Q. Wen, “Study on bilinear interpolation preisach model of piezoelectric actuator”, Advanced Materials Research, Vol.443–444, pp.437-441, 2012.

L. Xiao and R.B. Lu, “A Fully Complex-Valued Gradient Neural Network for Rapidly Computing Complex-Valued Linear Matrix Equations”, Chinese Journal of Electronics, Vol.26, No.6, pp.1194–1197, 2017.

T.S. Wu, S.Y. Chen, S. Tareen, et al., “Stress Wave Analysis Based Prognostic Health Management”, Chinese Journal of Electronics, Vol.27, No.3, pp.565–572, 2018.

Q. LI and K.X. ZHOU, “The research of the pressure sensor temperature compensation based on PSO-BP algorithm”, Acta electronica sinaca, Vol.43, No.2, pp.412–416, 2015. (in Chinese)

Y.F. Zhang, Y.C. Sun and X.H. Xing, “The temperature compensation for pressure sensor based on artificial neural network”, Acta Electronica Sinica, Vol.36, No.2, pp.358–361, 2008. (in Chinese)

Y.T. Dong, “Research on micro differential pressure transmitter and Realization of temperature compensation”, Ph.D. Thesis, Shanghai Jiao Tong University, Shanghai, China, 2014. (in Chinese)

Y.F. Zhang and J.M. Yan, “Compensation method of pressure sensor base on least square principle”, Computer Measurement & Control, Vol.15, No.12, pp.1870–1873, 2007

D.D. Yang and K.R. Wang, Numerical Analysis, Science Press, Beijing, China, 2013.

N. Qin, “The surface fitting base on total least squares and its application in GPS elevation fitting”, M.Sc. Thesis, Southwest Jiaotong University, Chengdu, China, 2015.

Z.L. Yu and Y. Zhang, “The equivalent definition of Haar’s condition in the best uniform approximation theory”, Acta Scientiarum Naturalium Universitatis Nankaien, Vol.39, No.3, pp.101–103, 2006.

C.H. Santos, B.P.B. Silva and J.Y. Yuan, “Block SOR methods for rank-deficient least-squares problems”, Journal of Computational and Applied Mathematics. Vol.100, No.1, pp.1–4, 1998.

C. Zhang, Z. Xue and S. Luo. “A convergence analysis of SOR iterative methods for linear systems with weak H-matrices”, Open Mathematics, Vol.14, No.1, pp.747–760, 2016.

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