Research On Displacement Measurement System Based On Eddy Current Sensor

The eddy current displacement sensor is according to the eddy current effect of the metal conductor in the dynamically changing magnetic field.The structure of the sensor is simple,the manufacturing cost is low,the sensor is sensitive to displacement,the resistance to oil is strong,and the object's surface will not be damaged.Therefore,eddy current displacement sensors are widely used in special fields such as aerospace and biomimetic environments.The application environment of eddy current displacement sensor is complicated,and many harsh environmental factors set high requirements for its accuracy and stability.Among them,temperature drift is the main factor of the eddy current displacement sensor's accuracy.In order to improve the accuracy of eddy current displacement sensor and reduce temperature error,this paper must compensate for temperature.The main research contents are as follows:?1?The basic structure and principle of eddy current sensor are introduced.The methods of multiple regression analysis,least squares support vector machine?LSSVM?and particle swarm optimization least squares support vector machine?PSO-LSSVM?are discussed respectively.?2?In order to solve the problem that the eddy current displacement sensor is greatly affected by temperature,the multi-sensor fusion technology is used to compensate the temperature.According to the experimental data,the zero temperature coefficient before uncompensation is1.35x10^-2/?,the temperature coefficient of sensitivity before uncompensation is 1.35x10^-2/?,and the temperature error is 40.43%.?3?Establishing the multivariate regression compensation model,the LSSVM model and the PSO-LSSVM model to compensate the eddy current displacement sensor measurement data,and comparing with the difference of compensation effects between several data fusion algorithms.?4?This paper uses a STM32 single-chip microcomputer to design a displacement measurement system with wireless transmission function,including signal acquisition,amplification circuit,A/D signal conversion,alarm circuit,nRF2401 short-range wireless communication transmission and LCD display.The software section includes the core temperature compensation algorithm and individual module subroutines.After the design of the whole MCU system,tcontinuous debugging is carried out,so that the modules can cooperate with each other and work normally.The results show that in the zero temperature coefficient,the binary regression algorithm's data is increased to 8.181x10-4/°C,the LSSVM's data is increased to 6.958x10-4/°C,and the PSO-LSSVM's data is increased to 1.81x10-4/°C.In the sensitivity temperature coefficient,the binary regression algorithm's data is increased to 3.035x10-3/°C,the LSSVM's data is increased to3.696x10-3/°C,and the PSO-LSSVM's data is increased to 5.59x10-4/°C.On the temperature additional error,the binary regression algorithm's data is improved to 9.10%,LSSVM's data is increased to 11.09%,and PSO-LSSVM's data is increased to 1.71%.After comparison,the three methods improve the performance,but the particle swarm optimization least squares support vector machine?PSO-LSSVM?algorithm has the best compensation effect on temperature.