A study on the application of unsupervised clustering algorithms in GNSS-RTK data analysis for cable-stayed bridges monitoring
Email:
gianglk@utc.edu.vn
Keywords:
GNSS-RTK, HAC clustering, Gaussian Mixture Model (GMM), Silhouette index, unsupervised machine learning, cable-stayed bridge monitoring
Abstract
GNSS-RTK satellite positioning technology has been widely applied in structural health monitoring (SHM) of cable-stayed bridges due to its ability to provide accurate and continuous displacement data. However, a major challenge is that the monitoring data often contain noise, outliers, and lack labels, which makes early detection of abnormal structural states difficult. This study focuses on analyzing vertical GNSS-RTK displacement time series from the Nhat Tan cable-stayed bridge (Hanoi) using two unsupervised clustering algorithms: Hierarchical Agglomerative Clustering (HAC) and the Gaussian Mixture Model (GMM). The analysis procedure includes data preprocessing (outlier removal using the Hampel filter, interpolation, segmentation, and z-score normalization) and cluster validation through the Silhouette index. The results show that both HAC and GMM identify the optimal number of clusters as k = 2, representing two distinct displacement states, with GMM achieving better clustering performance (Silhouette ≈ 0.596) compared to HAC (≈ 0.520). These findings confirm the feasibility of applying unsupervised clustering for early detection of abnormal states in cable-stayed bridges, thereby enhancing proactive maintenance efficiency and operational safetyReferences
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[16] Bộ GTVT, Tài liệu thiết kế và lắp đặt hệ thống quan trắc cầu Nhật Tân.
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[3]. A. Guo, A. Jiang, J. Lin, X. Li, Data mining algorithms for bridge health monitoring: Kohonen clustering and LSTM prediction approaches, Journal of Supercomputing, 76 (2020) 932–947. https://doi.org/10.1007/s11227-019-03045-8.
[4]. A. Diez, N.L.D. Khoa, M.M. Alamdari, Y. Wang, F. Chen, P. Runcie, A clustering approach for structural health monitoring on bridges, Journal of Civil Structural Health Monitoring, 6 (2016) 429–445. https://doi.org/10.1007/s13349-016-0160-0.
[5]. S. Aghabozorgi, A.S. Shirkhorshidi, T.Y. Wah, Time-series clustering – A decade review, Information Systems, 53 (2015) 16–38. https://doi.org/10.1016/j.is.2015.04.007.
[6]. Geo Matching, Which is Better Among Static Survey, RTK or PPK? https://geo-matching.com/articles/which-is-better-among-static-survey-rtk-or-ppk, 2022 (truy cập ngày 5 tháng 8 năm 2025).
[7]. P.N. Tan, M. Steinbach, A. Karpatne, V. Kumar, Introduction to data mining, Second edition, Pearson, New York, 2019.
[8]. A.K. Jain, Data clustering: 50 years beyond K-means, Pattern Recognition Letters, 31 (2010) 651-666. https://doi.org/10.1016/j.patrec.2009.09.011.
[9]. J.O. Palacio-Niño, F. Berzal, Evaluation Metrics for Unsupervised Learning Algorithms, (2019). https://doi.org/10.48550/arXiv.1905.05667.
[10]. D. Müllner, Modern hierarchical, agglomerative clustering algorithms, 2011. https://doi.org/10.48550/ARXIV.1109.2378.
[11]. L. Kaufman, P.J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley & Sons, 2009.
[12]. D. Reynolds, Gaussian Mixture Models, in Encyclopedia of biometrics, Springer, Boston, MA, 2015.
[13] Lê Khánh Giang, Hồ Thị Lan Hương, Đỗ Văn Mạnh, Trần Quang Học, Applying a two-step cluster algorithm in traffic accident data analysis, Transport and Communications Science Journal, 75 (2024) 1673-1687. https://doi.org/10.47869/tcsj.75.4.16
[14] P.J. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of computational and applied mathematics, 20 (1987) 53–65. https://doi.org/10.1016/0377-0427(87)90125-7.
[15] Cầu Nhật Tân, https://vi.wikipedia.org/w/index.php?title=C%E1%BA%A7u_Nh%E1%BA%ADt_T%C3%A2n&oldid=73707273, 2015 (truy cập ngày 4 tháng 8 năm 2025).
[16] Bộ GTVT, Tài liệu thiết kế và lắp đặt hệ thống quan trắc cầu Nhật Tân.
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Received
19/08/2025
Revised
11/10/2025
Accepted
13/10/2025
Published
15/10/2025
Type
Research Article
How to Cite
Trần Đức, C., Hồ Thị Lan, H., Lê Khánh, G., & Lê Văn, H. (1760461200). A study on the application of unsupervised clustering algorithms in GNSS-RTK data analysis for cable-stayed bridges monitoring. Transport and Communications Science Journal, 76(8), 1138-1150. https://doi.org/10.47869/tcsj.76.8.8
