Aug 2026· Structural Health Monitoring· 0 citations· 29 references
Abstract
Wind turbine towers in coastal environments are exposed to geometric misalignment and surface corrosion, yet these condition indicators are commonly assessed separately and without a consistent reference across inspection epochs. This study develops a reference-consistent structural health monitoring framework that integrates total-station surveying and multi-temporal unmanned aerial vehicle imagery for concurrent monitoring of view-dependent image-space inclination indicators and visible corrosion. A baseline lower-segment reference axis is established in a fixed geodetic coordinate system. The geodetically controlled baseline image configuration is transferred to subsequent epochs through covariance-weighted control-image constraints, while RTK-GNSS and inertial observations support exterior-orientation estimation. The angular difference between the projected reference axis and an image-derived visual symmetry axis defines the inclination indicator. The combined single-view standard uncertainty is 0.041°, the expanded uncertainty is 0.082°, and the engineering monitoring threshold is 0.098°. Five UAV epochs acquired between October 2024 and June 2025 yield first-to-final angular-change magnitudes of 0.030° to 0.074° across eight fixed viewing directions. These values remain below the single-view expanded-uncertainty reference magnitude and are therefore interpreted as monitoring-level observations rather than statistically confirmed structural deformation. An independent total-station re-survey at the final epoch yields validation residuals from −0.032° to +0.044°, with a mean absolute residual of 0.017° and a root-mean-square residual of 0.023°, supporting monitoring-level consistency between the UAV-derived and projected total-station changes. Visible corrosion is segmented using YOLO11-seg and normalized with respect to the valid, observable tower-surface region. The independent test set yields a precision of 79.6%, a recall of 88.0%, and an F1 score of 0.84. The visible corrosion extent index increases from 0.04 to 0.12%, corresponding to a descriptive transition from ASTM D610 grade 8 to grade 7. The framework provides a reference-consistent and uncertainty-aware basis for maintenance-oriented monitoring of slender tubular towers.
Underground mining operations depend heavily on vertical shafts for access, ventilation, and ore transport, making their structural integrity and safety critical to overall mine performance. Traditional shaft inspections, though rigorous, are limited by human accessibility, environmental hazards, and subjective evaluation. This study presents the development and initial testing of a novel unmanned aerial vehicle (UAV) system designed specifically for shaft inspections in deep mining environments. The research focuses on the GG-1 shaft in Kwielice, Poland—the country’s deepest operational shaft—where challenging conditions such as high ventilation airflow, confined geometry, and absence of GNSS signals necessitated innovative solutions. A custom-built hexacopter equipped with high-resolution cameras and photogrammetric capabilities was deployed to capture detailed visual and spatial data. This article presents complementary path of UAV evolution, from concept, early development stage and results without positioning system through to the description of final results including positioning system and all six cameras until results of high-altitude flights. Results demonstrate that UAV-based inspection can deliver sufficient precision for identifying structural irregularities, documenting shaft infrastructure, and enhancing safety monitoring. The findings highlight the potential of UAV technology as a complementary tool to conventional inspections, offering improved data quality, reduced risk to personnel, and a new approach to shaft maintenance.
Wojciech Rutkowski, Jędrzej Szczepaniak, Tomasz Lipecki et al.· Remote Sensing· 0 citations
Repeated non-equidistant unmanned aerial vehicle (UAV) inspections of slope-road cracks require measurements from different distances, poses, and image scales to remain comparable and sufficiently precise for engineering-state decisions. Existing studies rarely integrate cross-view physical conversion, measurement uncertainty, and a project-defined minimum detectable change. We develop an engineering-detectability framework that defines cross-period criteria for crack width and displacement and derives equivalent widths for ideal, representative non-standard, and arbitrary viewpoints. First-order error propagation and reliability allocation convert the minimum detectable change into accuracy requirements for range, field of view, and normalized image coordinates. Crack-boundary coordinates and localization uncertainties provide a common interface for interchangeable detection and photogrammetric modules. Validation combines a controlled fixed-camera sequence with a close-range field-camera multiview test of seven physical openings under local coplanarity. All six determinate stages in the controlled sequence agreed with the digital image correlation (DIC) comparison, while one borderline stage required review. Across the seven openings, the four-view means gave a mean absolute error (MAE) of 0.196 mm and a root mean square error (RMSE) of 0.270 mm, with cross-view coefficients of variation (CVs) of 0.33–4.93%. An illustrative error budget demonstrates reverse screening of system configurations from project thresholds. The framework therefore connects viewpoint-equivalent measurements, uncertainty constraints, and engineering-state decisions in an auditable chain.
Abstract. High-resolution airborne remote sensing increasingly requires the coordinated acquisition of geometric and thermal information for applications such as urban infrastructure inspection, environmental monitoring, and emergency response. However, conventional airborne systems typically operate optical and thermal sensors as loosely coupled subsystems, leading to temporal misalignment, unstable geometric relationships, and limited consistency in fused products. This paper presents EagleFrame IR-VM28K, a tightly coupled airborne MWIR–visible–GNSS/IMU integrated system designed for high-resolution thermal–optical observation. The system integrates a cooled mid-wave infrared (MWIR) imaging subsystem, a high-resolution visible dual-camera subsystem, and an AP+30 GNSS/IMU navigation unit under a unified mechanical structure, electrical control, and timing framework. A resolution-aware imaging strategy based on sweeping acquisition is adopted to enhance the effective thermal representation capability of the MWIR subsystem. A unified processing workflow is established, including hardware synchronization, trajectory post-processing, installation-parameter calibration using POSPAC CalQC, MWIR radiometric correction, geometric reconstruction, cross-modal co-registration, and fusion. Furthermore, a multi-temporal thermal analysis framework is introduced to characterize thermal inertia and temporal thermal evolution of urban surfaces. Flight experiments over Wujin District demonstrate that the proposed system achieves strong spatial consistency between visible and MWIR imagery and effectively represents thermal characteristics of roofs, pavements, and water bodies. Comparative analysis shows that tightly coupled integration and calibration significantly improve cross-modal alignment and fusion quality. The results confirm that the proposed system provides a robust solution for high-resolution airborne thermal–optical remote sensing and offers a foundation for thermal anomaly detection and urban thermal process analysis.
Yanning Wang· The International Archives o...· 0 citations
UAV bridge inspection requires centimeter-level global positioning in the engineering coordinate frame to associate detected defects with BIM component IDs and mileage stakes. Intermittent GNSS outages beneath beams, inside box girders, and in pier-dense regions cause conventional navigation methods to accumulate drift or produce discontinuous pose estimates. This paper presents BCEF-Nav, a BIM-constrained elastic fusion navigation framework for UAV bridge inspection. The framework adaptively adjusts GNSS constraints according to signal availability and replaces degraded GNSS references with semantic–geometric constraints from a high-precision as-built BIM model within a sliding-window optimizer. Semantic-guided feature matching suppresses false correspondences in repetitive bridge structures. BCEF-Nav uses only low-cost commercial sensors and is compatible with mainstream inspection UAVs. Digital twin simulations and field experiments achieved an ATE RMSE of 5.7 cm after 120 s of complete GNSS occlusion and a 100% positioning success rate with positioning errors below 10 cm, outperforming seven recent state-of-the-art baselines.
Accurate bathymetric data are essential for the design and monitoring of coastal structures, but conventional multibeam surveys are costly and often impractical in shallow or confined areas. We evaluate a single-beam echosounder (SBES, ECT400) suspended beneath an unmanned aerial vehicle (UAV) as a rapid method with low logistical requirements for bathymetric monitoring of coastal infrastructure. Fieldwork was performed in an operational dry dock that was alternately drained and filled, enabling direct geometric validation against an ultra-high-resolution photogrammetric DEM (0.55 cm GSD). The co-registered dataset comprises N = 16,137 sonar returns to depths of ≈ 8 m. The UAV-mounted SBES produced a mean depth difference of 0.15 m (SD = 0.58 m) relative to the photogrammetric reference. From these residuals we estimate a 95% Minimum Detectable Change (MDC95) of ≈ 0.5 m when changes are assessed by aggregating repeated co-located passes. These results indicate that the UAV-SBES workflow is suitable as a Tier-1 screening tool for structural-health monitoring, effective for detecting metre- to decimetre-scale changes and triaging sites for targeted high-precision follow-up, but not for micrometre/mm-scale deformation monitoring. The method’s portability and vessel-free operation make it especially useful for frequent inspections in shallow, confined coastal settings.
Bethsaide Souza-Santos, M. Arza-García, J. Ortiz-Sanz et al.· Journal of Civil Structural...· 0 citations
Bridge infrastructure in sub-Saharan Africa is often monitored with limited resources, leaving many ageing structures without a reliable geometric baseline for tracking deterioration. This paper reports on a UAV photogrammetric inspection campaign conducted on the Old Cotonou Bridge, a two-lane reinforced concrete structure crossing the coastal lagoon of Cotonou (Benin), with the aim of establishing a quantitative geometric reference for deck deformation monitoring. A flight of 573 images was captured at 56.1 m altitude using a DJI Mavic 2 Pro equipped with a Hasselblad L1D-20c 20 Mpx sensor (GSD: 1.28 cm/px), and the dataset was processed with Agisoft Metashape Professional 2.3.1 following a Structure-from-Motion and Multi-View Stereo workflow. Processing yielded a dense point cloud of 26.8 million points at 383 pts/m
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, a DEM at 5.11 cm/px, and a georeferenced orthomosaic in WGS 84 / UTM zone 31N; six thematic classes were identified by automatic classification, followed by manual verification of the Road and Building classes. Deck deformation was then quantified through 2D polynomial regression of the deck surface, revealing seven statistically significant depression zones (D1–D7) with amplitudes ranging from −17.3 cm to −79.4 cm relative to the reference surface, over areas of 2 to 30 m
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. The vertical accuracy achieved (RMSE Z = 0.44 cm) confirms that UAV photogrammetry can reliably serve as a quantitative tool for structural deformation detection on bridge decks, despite the use of only three Ground Control Points. The geometric reference dataset (T
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) produced here places at the disposal of asset managers a georeferenced database that is immediately usable for prioritising maintenance interventions on this and comparable structures.
Kora Yarou, V. Doko, Boris Ganmavo et al.· Journal of Civil, Constructi...· 0 citations