华南地震2025，Vol.45Issue(4)：17-27,11.DOI:10.13512/j.hndz.2025.04.03
地磁台站观测数据铁路运营干扰识别与数据重构
Railway Operation Interference Identification and Data Reconstruction Based on Observation Data from Geomagnetic Stations—Taking the Lushi Geomagnetic Station as an Example
摘要
Abstract
As Haoji Railway is only 130 m away from Lushi Geomagnetic Station,the geomagnetic observation data of Lushi Station has been seriously disturbed during construction and operation,resulting in unavailable data.The purpose of this paper is to conduct in-depth analysis on the typical events that caused the change of the second sampled geomagnetic data of Lushi Station during the operation of Haoji Railway.Based on the analysis of the characteristics of the time domain and frequency domain of the geomagnetic data of Lushi Station,the FFT observation anomaly recognition method based on the triple mean square error principle is proposed to distinguish the observation anomaly caused by the railway operation from the normal magnetic disturbance for identification.The actual reconstruction effect of spatial weighting method,BP neural network algorithm and XGBoost strong machine learning algorithm in data processing is verified by data reconstruction for the disturbed observation data and missing data of Lushi Station.The results show that when the XGBoost strong machine learning algorithm is applied to the data reconstruction of observation anomalies and missing records.,through data simulation,the reconstructed data has a high degree of coincidence with the original data in a small time scale,achieving good results.关键词
地磁观测/数据重构/机器学习/空间加权/BP神经网络/GBDT算法Key words
Geomagnetic observation/Data reconstruction/Machine learning/Spatial weighting/BP neural network/GBDT algorithm分类
天文与地球科学引用本文复制引用
谢佳兴,侯博文,张翰博,成娜,秦浦,梁向东..地磁台站观测数据铁路运营干扰识别与数据重构[J].华南地震,2025,45(4):17-27,11.基金项目
中国地震局监测、预报、科研三结合课题(3JH-202401091) （3JH-202401091）
河南省地震局第四批科技创新团队"地磁二级固定观测网观测站(地表型基本站)标准化建设运行探索"联合资助. （地表型基本站）
