Research On Intelligent Displacement Measurement System Based On Differential Iuductance Sensor

Displacement measurement has been widely used and indispensable in most industrial scenarios.With the advent of the era of industrial automation and the improvement of technology,the current traditional displacement measuring equipment can not meet the current needs,so this paper designs an intelligent displacement measuring system based on differential inductance displacement sensor.The system should have the advantages of high precision,self-calibration and strong anti-interference ability.At the same time,it should have the display,communication and control functions to meet the requirements of industrial automation.Differential inductance displacement sensor has been widely used in the field of displacement measurement with its characteristics of high precision,long life and high stability,but it still has the problems of zero residual voltage,temperature drift and large nonlinear error,so this paper analyzes these problems in detail and gives the solution,the main content is as follows:(1)Aiming at the problem of zero residual voltage.In this paper,the working principle and characteristics of differential inductance displacement sensor are studied.Firstly,the material selection,process and structural parameters of the sensor are designed.Secondly,the transformer bridge is selected as the acquisition circuit,and the 100-ω potentiometer is connected in series on a bridge arm to reduce the fundamental wave component of the signal,and then the two coils are connected in parallel to the 1kΩ resistor and the 200-ω potentiometer to reduce the high-order harmonic component,and the circuit is improved.The transformer is redesigned and manufactured again.Finally,the secondary measurement circuit(conditioning circuit)and oscillation circuit design,inhibit the power supply of high harmonic components,conditioning signal.The above method greatly reduces the zero residual voltage of the measuring system.(2)In view of the nonlinear errors existing in the measurement system,this paper adopts a nonlinear compensation algorithm model based on the least square curve fitting method,and uses the model to process the static calibration data.The linearity before and after processing is used to measure the index evaluation model effect.The experimental results show that the nonlinear degree decreases from 4% to 1.33% after the nonlinear correction model based on the curve fitting method,and the linearity of the measurement system is improved well.(3)In view of the problem that the measurement system is easy to be affected by temperature and result in temperature drift,This paper proposes a temperature compensation Algorithm model based on Sparrow Search Algorithm(SSA)to optimize Least Squares Support Vector Machine(LSSVM).Firstly,the static calibration experiment of differential inductance sensor is carried out to obtain the calibration data and draw the static curve of input and output.Then the calibration data is used to train the algorithm model.After the training is completed,the displacement prediction data can be obtained by inputting the test data into the model,and the input and output curves after compensation are drawn.Finally,zero temperature coefficient and sensitivity temperature coefficient were used to measure the model effect.The experimental results show that the zero temperature coefficient increases by two orders of magnitude from to and the temperature sensitivity coefficient increases by one order of magnitude from to.The model effectively inhibits the influence of temperature on the measurement system.(4)Design and build an intelligent displacement measurement system based on STM32.After the completion of the system construction,the overall debugging,to ensure stable operation,at the same time with high precision and good temperature interference resistance characteristics.