Imagen de Portada

Tilt Monitoring of Super High-Rise Industrial Heritage Chimneys Based on LiDAR Point Clouds

Guardado en:
Publicado en:Buildings vol. 15, no. 17 (2025), p. 3046-3068
Autor principal: Zhou Mingduan
Otros Autores: Qin Yuhan, Xie Qianlong, Song, Qiao, Lin, Shiqi, Lu, Qin, Zhou Zihan, Wu Guanxiu, Peng, Yan
Publicado:
MDPI AG
Materias:
Structural engineering
Accuracy
Monitoring methods
Data acquisition
Photogrammetry
Structural safety
Algorithms
Parameter identification
Lidar
Chimneys
Urban renewal
Data processing
Unmanned aerial vehicles
Monitoring
Verticality
Cultural resources
Preservation
Adaptive algorithms
Construction
Masonry
Spatial data
Fourier transforms
Image segmentation
Sensors
Deviation
Adaptive slicing
High rise buildings
Finite element analysis
Azimuth
Deformation
Acceso en línea:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:The structural safety monitoring of industrial heritage is of great significance for global urban renewal and the preservation of cultural heritage. However, traditional tilt monitoring methods suffer from limited accuracy, low efficiency, poor global perception, and a lack of intelligence, making them inadequate for meeting the tilt monitoring requirements of super-high-rise industrial heritage chimneys. To address these issues, this study proposes a tilt monitoring method for super-high-rise industrial heritage chimneys based on LiDAR point clouds. Firstly, LiDAR point cloud data were acquired using a ground-based LiDAR measurement system. This system captures high-density point clouds and precise spatial attitude data, synchronizes multi-source timestamps, and transmits data remotely in real time via 5G, where a data preprocessing program generates valid high-precision point cloud data. Secondly, multiple cross-section slicing segmentation strategies are designed, and an automated tilt monitoring algorithm framework with adaptive slicing and collaborative optimization is constructed. This algorithm framework can adaptively extract slice contours and fit the central axes. By integrating adaptive slicing, residual feedback adjustment, and dynamic weight updating mechanisms, the intelligent extraction of the unit direction vector of the central axis is enabled. Finally, the unit direction vector is operated with the x- and z-axes through vector calculations to obtain the tilt-azimuth, tilt-angle, verticality, and verticality deviation of the central axis, followed by an accuracy evaluation. On-site experimental validation was conducted on a super-high-rise industrial heritage chimney. The results show that, compared with the results from the traditional method, the relative errors of the tilt angle, verticality, and verticality deviation of the industrial heritage chimney obtained by the proposed method are only 9.45%, while the relative error of the corresponding tilt-azimuth is only 0.004%. The proposed method enables high-precision, non-contact, and globally perceptive tilt monitoring of super-high-rise industrial heritage chimneys, providing a feasible technical approach for structural safety assessment and preservation.
ISSN:2075-5309
DOI:10.3390/buildings15173046
Fuente:Engineering Database