| As manufacturing continues to develop towards intelligent,automated,and precisionoriented directions,higher requirements have been placed on the most basic measurement displacement methods used in manufacturing.Precision sensors,as a way of measuring precise displacement,also have increasingly high requirements for the measurement accuracy of sensors.Currently,due to the advantages of inductive linear displacement sensors in terms of measurement environment and non-contact measurement displacement,inductive linear displacement sensors are widely used in military,aerospace,and manufacturing fields.However,compared with traditional grid-type linear displacement sensors such as gratings,capacitive gratings,and magnetic gratings,the newly developed electromagnetic induction linear displacement sensors based on PCB technology have a larger grid pitch,which makes it easy to cause displacement measurement errors in the manufacturing and assembly processes of the sensors.As a type of linear displacement sensor based on PCB technology,the bilateral sensing inductive linear displacement sensor suppresses long-term and short-term errors to a certain extent,but still has regular shortperiod errors.Among the types of short-period displacement errors,the 1-order,2-order,and4-order errors are the most obvious and common in this sensor.In view of this situation,this article takes the double-sided sensing electromagnetic induction linear displacement sensor as the research object,carries out research on the sources and generation mechanisms of short-period errors,as well as corresponding error compensation methods,to improve the measurement accuracy of the sensor.The main research process,content,and results are as follows:(1)Through studying the working principle and signal processing method of the bilateral sensing electromagnetic induction linear displacement sensor,the sources of shortperiod displacement errors in its measurement were analyzed,and the mechanism of error generation was explored and discussed.The research on the dominant error frequency source and the mechanism of error generation of short-period displacement errors has laid a theoretical foundation for the establishment of subsequent error suppression models.(2)In order to achieve online suppression of short-period errors of bilateral sensing electromagnetic induction linear displacement sensors,this study has developed an error correction method that does not rely on external reference.Based on the original induction signal output by the sensor,the Fourier decomposition method is used to analyze the original induction signal data,obtain the accurate functional relationship between the short-period error and the original induction signal data,and establish an accurate short-period error compensation model.Therefore,based on the error compensation model,the sensor can achieve short-period error correction through software.(3)Due to the insufficient strength of the induction signal output by the sensor,which affects the analysis results of the signal,this study carried out optimization work on the sensor sensing unit structure to improve the output strength of the induction signal.Based on the preliminary experimental results of the prototype,the way to enhance the induction signal is obtained: by reasonably configuring the sensing unit in the moving ruler base to obtain the best magnetic coupling efficiency of the sensing unit.The feasibility of the moving ruler structure improvement plan was first verified by finite element simulation.According to the improvement plan,a three-dimensional model of the sensor was established,and electromagnetic simulation was performed on the sensor model.The simulation results showed that the optimized sensor model produced a significantly enhanced induced electromotive force amplitude on the moving ruler.(4)Based on the research on the short-period error compensation model and the induction signal enhancement method,error correction verification experiments were carried out on the prototype of the bilateral sensing electromagnetic induction linear displacement sensor.The software-based error correction experiment includes error correction effect verification experiment and comparative experiment.The experimental results show that the self-correction method studied in this study can achieve good error suppression effect under different operating conditions,such as different linear movement speeds of the moving ruler and different gaps from the fixed ruler.In addition,a comparative experiment was conducted between the original error correction method and the error correction method studied in this study,and the experimental results showed that the latter can correct more types of errors and achieve better error correction effect.The sensor unit optimization experiment of the prototype includes preliminary verification experiment and error correction effect experiment.The experimental results show that the peak-to-peak values of the 1-order,2-order,and 4-order short-period errors of the sensor prototype after the sensing unit structure is optimized are significantly reduced,verifying the feasibility and effectiveness of the hardware sensing unit structure optimization method.After the signal-to-noise ratio is enhanced,the error frequency is clear,and the short-period error suppression effect is more significant,and the error peak-to-peak value is reduced by about 78%.Finally,the 1-order,2-order,and 4-order short-period errors of the sensor prototype are 0.58μm,0.28μm,and0.93μm,respectively,and the peak-to-peak error values are 5.8μm.In summary,based on the bilateral sensing electromagnetic induction linear displacement sensor,this study conducted research on the sources and mechanisms of shortperiod displacement errors and proposed an error self-correction method that does not rely on external reference.Through theoretical analysis,simulation experiments based on sensor structure optimization,and prototype experiments,the error correction method studied in this study has important significance for improving the measurement performance of the sensor. |
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