Mathematical Model and Simulation Based on ANSYS Maxwell of the Magnetic Fluid Differential Transformer Inclination Sensor

Wang Xing *

School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.

Xu Haitao

School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.

Lu Kuo

School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.

*Author to whom correspondence should be addressed.


Abstract

A mathematical model of a mutual inductance magnetic fluid inclination sensor is established. The sensing element of the sensor is magnetic fluid. The composite magnetic core suspended in the magnetic fluid increases the permeability of the medium in the winding. The total magnetic induction intensity B in the winding is composed of two parts: the excitation magnetic induction intensity Bl and the additional magnetic induction intensity Ba generated by the magnetization of pure iron. The sensitivity S of the sensor and its influencing factors are derived. The output characteristics of the sensor are analyzed using ANSYS Maxwell simulation software. The results show that the variable resistance of the measuring circuit can eliminate the residual voltage at zero point, and the output voltage carrier after filtering and rectification is positive half cycle; The addition of pure iron to the magnetic core greatly increases the mutual inductance variation between the primary and secondary windings, and the inclination angle in a small range is linear with the mutual inductance variation; The recovery force of the composite core is proportional to the displacement.

Keywords: Magnetic fluid, sensor, simulation, composite core, measuring circuit, restoring force


How to Cite

Xing, Wang, Xu Haitao, and Lu Kuo. 2023. “Mathematical Model and Simulation Based on ANSYS Maxwell of the Magnetic Fluid Differential Transformer Inclination Sensor”. Journal of Engineering Research and Reports 24 (3):1-9. https://doi.org/10.9734/jerr/2023/v24i3803.

Downloads

Download data is not yet available.