An efficient semi-automated characterization of rock mass discontinuities from 3D point clouds based on Nutcracker Optimization Algorithm-improved probabilistic neural network
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引用次数: 0
Abstract
Discontinuities in rock masses significantly influence their mechanical properties and are critical for engineering applications, making it essential to thoroughly understand their geometric parameters. 3D point clouds serve as fundamental data for efficiently and accurately analyzing discontinuity orientations. In this context, a novel semi-automated method that employs a Nutcracker Optimization Algorithm-improved Probabilistic Neural Network (NOA-PNN) is proposed. The NOA enables the PNN to quickly identify the optimal smoothing factor, balancing both accuracy and efficiency. This method utilizes not only normal vectors, but also point coordinates, curvature, and density, incorporating a broader set of features to accurately identify points on discontinuities. The NOA-PNN model, trained on manually selected samples, swiftly identifies discontinuity sets while efficiently filtering out noise. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is then used to extract single discontinuities within each set. Each discontinuity is fitted to a plane using a Principal Component Analysis (PCA)-based least squares method, facilitating the measurement of their spatial geometric parameters. Validation through two cases demonstrated that the proposed method achieved an average deviation of less than 5° in both dip direction and dip angle, exhibiting potential advantages in terms of accuracy and efficiency when compared to other important studies or software. This method significantly improves computational efficiency and achieves satisfactory results with only a small number of randomly selected samples. Its low requirements for sample quality and operator expertise make it highly operable and easily adaptable for practical engineering applications.
期刊介绍:
Engineering geology is defined in the statutes of the IAEG as the science devoted to the investigation, study and solution of engineering and environmental problems which may arise as the result of the interaction between geology and the works or activities of man, as well as of the prediction of and development of measures for the prevention or remediation of geological hazards. Engineering geology embraces:
• the applications/implications of the geomorphology, structural geology, and hydrogeological conditions of geological formations;
• the characterisation of the mineralogical, physico-geomechanical, chemical and hydraulic properties of all earth materials involved in construction, resource recovery and environmental change;
• the assessment of the mechanical and hydrological behaviour of soil and rock masses;
• the prediction of changes to the above properties with time;
• the determination of the parameters to be considered in the stability analysis of engineering works and earth masses.