Abstract
The optimization of electric field distributions in the optical voltage sensor (OVS) are mostly based on the finite element calculations and the exhaustive search method. It is unable to map complicated and nonlinear relationships between the electric field distribution and the sensing structure. Moreover, these methods turn out to be time-consuming, inefficient, and easy to fall into local traps. A hybrid optimization algorithm based on particle swarm optimization (PSO) and support vector machine (SVM) is developed to fix these issues in which the PSO-SVM establishes an electric field model for the electro-optic crystal and then the model is modulated by the PSO to achieve optimization. The medium attaching structure is taken as an example to test and verify the job, and the simulations and experiments show that the uniformity of electric field distributions is improved by 58% and the training time is saved by 87%.
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