Parameters optimization for GECDS using response surface methodology and genetic algorithms

In this paper, we propose a method to optimize the design parameters of the grating eddy current displacement sensor (GECDS) and minimize the nonlinearity error by combining FE, response surface method (RSM) and genetic algorithm (GA). This kind of sensor can be used in waterproof electronic caliper to realize long range displacement measurement with high accuracy in harsh environment. Finite-element (FE) is used to calculate nonlinearity error of the sensor in numerical experiments according to a definite scheme firstly. Secondly, these experimental data are used to construct a second-order polynomial model with RSM. Finally, the optimal combination of the design parameters is calculated with GA and the constructed model. The measurement accuracy for this combination of parameters is verified by the real measurement of the caliper prototype. The experimental results show that the combination of FE, RSM and GA obtains higher prediction accuracy and reduces computation cost.