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Sensors, Networks, Control Systems and Information Processing




Vol. 20, Special Issue, April 2013, pp.1-5



Application of Partial Least Squares Regression to Static Magnetic Grid Displacement Sensor


QIAO Shuang

Wuhan University of Technology, School of Information Engineering, Wuhan, 430070, China

Key Laboratory of Fiber Optic Sensing Technology and Information Processing,
Wuhan, 430070, China

E-mail: yuji6@126.com



Received: 1 February 2013   /Accepted: 30 April 2013   /Published: 11 May 2013

Digital Sensors and Sensor Sysstems


Abstract: In this paper, the author successfully proposed a new magnetic grid displacement data fitting model, based on partial least squares regression. Firstly, sinusoidal voltage is generated by the movement of magnetic sense hall on top of alnicos array. Then, handle the experimental data by the partial least squares fitting, obtained the relationship between values of Hall and displacement, and finally finish the displacement measure. The experiment results indicated that: this design can achieve displacement fitting goodness 99.98 % and maximum deviation of 0.1 mm. This method largely simplifies the production process of magnetic grid displacement sensor, reduces costs and achieves mass production. It has important implications in some special environment such as high temperature, low temperature, underwater and so on.


Keywords: Static magnetic grid, Sensor, Partial least squares regression (PLSR), Linear fitting


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