Dimension stone shape classification method based on rapid PCA algorithm and K-means clustering algorithm

Abstract

The invention relates to a dimension stone shape classification method based on a rapid PCA algorithm and a K-means clustering algorithm, and the method comprises the following steps: (1), carrying out the statistics of coordinates and gravity center coordinates of all edge contour points of dimension stones according to an earth-rock mixture section CAD graph which is obtained through a digital image processing technology and only has contour information; (2) unifying the position, the size and the orientation of the dimension stones; (4) adopting a rapid PCA algorithm to reduce 360 radiusesof each dimension stone in a dimension stone contour radius statistical table obtained by the unification processing to two dimensions by taking the 360 radiuses as row vectors; (5) selecting a K-means clustering algorithm to cluster the matrix after dimension reduction, so that dimension stones with similar shape features are classified into one class; and (6) finely adjusting the result after partial classification according to the defined shape characteristic parameters, and classifying the dimension stones with generality into one class. The method can quickly and accurately perform combined operation such as movement, rotation, scaling and direction changing on a large number of dimension stones, and efficient classification of a large number of dimension stones with different shapesis achieved.

Description

technical field [0001] The invention relates to the technical field of numerical simulation of geotechnical engineering, in particular to a block shape classification method based on a fast PCA algorithm and a K-means clustering algorithm. Background technique [0002] Soil-rock mixture is a Quaternary accumulation / sediment that exists widely in nature, and is also a filling material for many geotechnical engineering. It is composed of relatively large-scale, high-strength block stones and relatively fine-grained weak "soil". Due to the large scale of rocks, the physical and mechanical properties of soil-rock mixtures are not easy to be measured by indoor small-scale tests, and it is also difficult to obtain through large-scale field tests. Therefore, numerical simulation has become an important means to study the mechanical properties of soil-rock mixture, and the precision of modeling determines the accuracy of simulation results. Therefore, the establishment of a numeric...

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Problems solved by technology

[0005] In view of this, the present invention provides a block shape classification method based on the fast PCA algorithm and the K-means clustering algorithm, which can solve the problem that the existing soil-rock mixture is insufficient for block classification.

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