Differential optimization measurement technique for magnetic gradient tensors in magnet positioning
Year: 2025
Type: article
Abstract: The magnetic gradient tensor provides more information about the magnetic source in anomaly detection. However, approximation errors inevitably arise from the differential measurement method. Therefore, a differential optimization measurement method based on sensor positions fine-tuning is proposed in this study. This method introduces offset coefficients to establish a theory-measurement discrepancy model. Also, a minimum-overall-discrepancy optimization strategy is used to guide the hybrid PSO-Dogleg algorithm in parameter searching. Thus, the differential approximation closely estimates the gradient. The numerical simulation shows the proposed method is applicable across various detection regions, magnetic moments, and noise levels. Furthermore, the correlation between tensor measurement errors and positioning performance was analyzed, and positioning experiments were conducted. As a result, the root mean square error of the tensor component is reduced by 7.1 %, while the average positioning error is reduced from 0.244 m to 0.136 m, which effectively improves the positioning accuracy of the magnetic gradient tensor.
Source: Ain Shams Engineering Journal
Authors: Jinzhe Wang, Kai Li, Wenhui Jia, Xinqiang Liu, Qin Shi, Xuanqi Wu, Jinbao Li, Jialong Wang, Guang Yang, Na Shi
Institution: North University of China
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Award: G554056258
OpenAlex ID: W4414572732
