@article{WANG2026, 
author = {Chao WANG and Linhan CHENG and Yanzhang WANG and Yunxia WAN},
title = {Teaching experimental design of magnetic anomaly detection based on a rotor UAV platform},
year = {2026},
journal = {Experimental Technology and Management},
volume = {43},
number = {6},
pages = {183-190},
keywords = {rotor UAV, magnetic anomaly detectio, modular instrument system, scenario-based, experimental teaching},
url = {https://www.sciopen.com/article/10.16791/j.cnki.sjg.2026.06.023},
doi = {10.16791/j.cnki.sjg.2026.06.023},
abstract = {ObjectiveIn the talent training system for geophysical exploration and instrumentation majors, the integration of professional theory and engineering practice is a core requirement. The magnetic anomaly detection experiment serves as an important link between theory and practice, laying a solid foundation for subsequent professional learning and engineering applications. This paper presents the design of a full-process teaching experiment scheme for magnetic anomaly detection, covering “instrument system integration—instrument performance testing—target information acquisition—data preprocessing—result demonstration.”MethodsUsing a uniformly magnetized sphere as the research object, this study simulates the spatial distribution of magnetic anomalies. An experimental teaching system capable of synchronously acquiring magnetic field and spatial position data was designed and integrated, comprising an optically pumped magnetometer, a positioning module, a multichannel data acquisition instrument, and a UAV. Field experiments, including sensor performance testing, sensor placement testing, dynamic flight consistency testing, and regional magnetic anomaly surveys, were conducted to collect magnetic anomaly data.ResultsDue to differences between the field experimental environment and ideal working conditions, and because manually placed small vehicles cannot fully replicate standard uniformly magnetized spheres, certain numerical deviations exist between the measured data and the simulation results. However, both exhibit overall variation trends in the spatial distribution of the magnetic field that are highly consistent, thereby verifying the reliability and trend accuracy of the detected data.ConclusionsThe teaching demonstration and practical training mode designed in this paper, which combines “modular” instrument system integration, “process-based” instrument performance testing, and “scenario-based” field magnetic anomaly detection, effectively improves the cognitive level of students majoring in instrumentation on the design concept of advanced specialized instrument systems. It also deepens the understanding of students majoring in geophysical exploration-related disciplines regarding the fundamental principles of magnetic anomaly detection, and comprehensively tempers students’ comprehensive application capabilities in real-world engineering scenarios.}
}