Surrounding rock category acquisition method based on slag piece image recognition

An image recognition and surrounding rock level technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of surrounding rock classification lag, relying too much on human experience, etc., and achieve the effect of improving accuracy and speed.

Active Publication Date: 2018-06-19
CHINA RAILWAY ENGINEERING EQUIPMENT GROUP CO LTD
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Problems solved by technology

[0003] Aiming at the deficiencies described in the above-mentioned prior art, the present invention provides a method for obtaining the category of surrounding rock based on s

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  • Surrounding rock category acquisition method based on slag piece image recognition
  • Surrounding rock category acquisition method based on slag piece image recognition
  • Surrounding rock category acquisition method based on slag piece image recognition

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Embodiment Construction

[0047] A method for obtaining the category of surrounding rock based on slag chip image recognition, the steps are as follows:

[0048] S1, acquiring the image of the slag slice.

[0049] S2, transmit the slag image to the TBM main control room for processing, and obtain the processed slag image.

[0050] S2.1, extracting the color component of the color photo taken;

[0051] S2.2, perform smoothing and filtering according to the grayscale relationship of the image and the Gaussian function;

[0052] S2.3, performing adaptive histogram equalization on the image to improve the contrast of the image;

[0053] S2.4, calculate the gradient of the color image at multiple scales, and select the optimal value;

[0054] S2.5, perform morphological processing on the grayscale image to highlight the features of image extraction;

[0055] S2.6, the image is subjected to extreme value marking and watershed segmentation to obtain a segmented image;

[0056] S2.7, define merging and st...

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Abstract

The invention discloses a surrounding rock category acquisition method based on slag piece image recognition. The method comprises the following steps that S1, a slag piece image is acquired; S2, theprocessed slag piece image is obtained; S3, the surrounding rock grade associated sensitive feature set of the processed slag piece image is calculated; S4, the data sample is divided into k clustersby using an AP clustering method; S5, weight fusion of a Gaussian kernel function and a polynomial kernel function is performed, and LSSVM regression is performed on each cluster of the step S4 so asto obtain k submodules; and S6, weight fusion of the obtained k submodules is performed so as to obtain the surrounding rock category value. The real-time image is acquired and processed without manual participation so that excessive dependence on human experience can be avoided and the surrounding rock grading accuracy and rapidity can be enhanced.

Description

technical field [0001] The invention belongs to the technical field of tunnel surrounding rock image processing, and in particular relates to a method for obtaining the category of surrounding rock based on slag chip image recognition. Background technique [0002] The grade classification of tunnel surrounding rock plays a vital role in tunnel construction, and is an important factor in determining the stability of tunnel after excavation and selecting corresponding support measures. The traditional surrounding rock classification is based on the strength of the rock, the integrity of the rock mass, the filling of the fissure, the groundwater and the ground stress, etc. Due to the large workload and difficulty in obtaining it, the classification of the surrounding rock in the preliminary investigation is relatively rough. Therefore, in the process of TBM excavation, it often occurs that the exposed rock mass is inconsistent with the above-mentioned rock mass surrounding roc...

Claims

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Application Information

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IPC IPC(8): G06K9/44G06K9/46G06K9/62
CPCG06V10/34G06V10/443G06F18/2321G06F18/2411
Inventor 杨晨荆留杰陈帅刘恒超张娜李鹏宇
Owner CHINA RAILWAY ENGINEERING EQUIPMENT GROUP CO LTD
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