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Proceedings Paper

Nonlinear calibration for petroleum water content measurement using PSO
Author(s): Mingbao Li; Jiawei Zhang
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Paper Abstract

To improve the measurement precision of the capacitance method for petroleum water content, this paper presents a nonlinear calibration technique based on neural networks. Consider that the traditional BP algorithm has shortcomings of converging slowly and easily trapping a local minimum value, a combination algorithm using particle swarm optimization (PSO) and back propagation (BP) is adopted to train the neural network. It will enable the calibration process with an overall accuracy and a higher converging speed. Simulation results show that this method can effectively eliminate the impact of non-target parameters to the sensor output and has certain project value.

Paper Details

Date Published: 13 October 2008
PDF: 6 pages
Proc. SPIE 7129, Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration, 71291W (13 October 2008); doi: 10.1117/12.807644
Show Author Affiliations
Mingbao Li, Northeast Forestry Univ. (China)
Jiawei Zhang, Northeast Forestry Univ. (China)


Published in SPIE Proceedings Vol. 7129:
Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration

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