Optimal Design of Magnetic Sensor Arrays for Tunnel Transmission Lines Based on Noncontact Measurement and Differential Evolution Method

Electric power transmission by tunnel transmission technology resolves limitations of overhead transmission lines restricted by complex terrain, geological conditions, and environmental protection. A tunnel transmission method involves a sophisticated line-laying procedure within a smaller measurement space. However, it remains a challenging task to monitor their real-time operational status. It is anticipated that monitoring by utilizing magnetic measurement can be a promising solution. In this article, we propose a method of optimizing magnetic sensor arrays using a differential evolution (DE) algorithm. The current reconstruction technique based on noncontact magnetic measurements for different laying topologies is presented. A novel condition number-based approach is proposed for the current measurement error assessment. Then, the DE algorithm is utilized for optimization of condition number index for optimal sensor array arrangement. Random noise is introduced in magnetic field to emulate real-world scenarios. The root-mean-square error (RMSE) of reconstructed current in the presence of magnetic noise is reduced from 8.867% to 1.267% for vertical line configuration by the proposed method. In comparison to other optimization methods, the proposed technique yields accurate and reliable results.

Automated summary

This article presents a method for optimizing magnetic sensor arrays using a differential evolution algorithm in tunnel power transmission to monitor real-time operational status. The technique involves current reconstruction based on noncontact magnetic measurements and evaluation of current measurement errors using a novel condition number-based approach. The proposed method reduces the root-mean-square error (RMSE) of reconstructed current from 8.867% to 1.267% for vertical line configuration in the presence of magnetic noise. Compared to other optimization methods, the proposed technique yields accurate and reliable results.