# GNSS-Based Monitoring Methods for Mining Headframes
## 5 Conclusions  
This study, conducted at the Liuzhuang Mine in Anhui Province, developed a comprehensive technical framework encompassing \"data preprocessing, risk assessment, and early warning\", effectively addressing the fragmentation in data collection, processing, and decision-support workflows within the context of safety monitoring for mine shaft frames. Through on-site evaluations of the Liuzhuang Mine shaft frame, a distributed monitoring network was implemented, comprising one reference station and eight monitoring stations strategically positioned in stable regions and critical points around the frame. This implementation successfully achieved, for the first time, the decoupled monitoring of the shaft frame and the sheave system, thereby bridging a technical gap in specialized GNSS monitoring. Utilizing nearly two months of 3D deformation monitoring data gathered using the \"BeiDou + Geological Disaster Cloud Platform\", processes such as data cleaning, spatiotemporal big data modeling, and mathematical statistical analysis were conducted. This facilitated the development of a correlation model that links height, sheave distance, and deformation volume, and confirmed the reliability of risk threshold estimation. The study further proposed a multi-source data fusion framework predicated on the BIMRWP platform, which integrates inertial navigation, temperature-compensated sensors, and deep learning algorithms. This integration markedly enhanced millimeter-level accuracy and adaptability to complex environments at monitoring points. Building upon this foundation, a three-dimensional visualization early-warning model was developed utilizing an air-ground-space collaborative monitoring network, thereby providing an extensible technical solution for mines situated in diverse geological conditions. Future research endeavors will concentrate on the dynamic response characteristics of GNSS monitoring systems under seismic conditions, in conjunction with numerical simulations to analyze damage evolution mechanisms. Using localized parameter calibration and dynamic optimization algorithms, the study aspires to transition mine structural safety monitoring from generalized models to precise early-warning paradigms, thereby offering standardized technical frameworks and references for engineering practices in global mining operations. Conceptualization, X.Y. ([PERSON]), Z.Z. and Y.Y. ; methodology, X.Y. ([PERSON]), Z.Z. and Y.Y. ; software, X.Y. ([PERSON]), Z.Z. and Y.Y. ; validation, Z.Z., Y.Y. and X.Y. ([PERSON]); formal analysis, Z.Z., Y.Y. and C.L. ; investigation, Z.Z., Y.Y. and X.Y. ([PERSON]); resources, Z.Z., Y.Y., X.Y. ([PERSON]), L.L. and S.X. ; data curation, Z.Z. and X.Y. ([PERSON]); writing--original draft preparation, X.Y. ([PERSON]), Z.Z. and Y.Y. ; writing--review and editing, X.Y. ([PERSON]), Z.Z. and X.Y. ([PERSON]); visualization, X.Y. ([PERSON]), Z.Z. and Y.Y. ; supervision, X.Y. ([PERSON]), C.L., S.X. and L.L. ; project administration, X.Y. ([PERSON]) and Z.Z. ; funding acquisition, X.Y. ([PERSON]). All authors have read and agreed to the published version of the manuscript. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by Open Foundation of the Key Laboratory of Universities in Anhui Province for Prevention of Mine Geological Disasters (No. 2022-MGDP-08), National Natural Science Foundation of China (No. 42304050), Engineering Research Center of Mining Area Environmental and Disaster Cooperative Monitoring (Anhui University of Science and Technology) (No. KSCJTJC202403), and Anhui Province Natural Science Foundation (No. 2208085 QD115). Not applicable. The data used to support the findings of this study are available from the corresponding author upon request. **Acknowledgments:** The authors gratefully acknowledge the relevant data and products provided by the \"Liu Zhuang Coal Mine Hoisting Equipment and Operating Environment Health Monitoring System\" project.