Machine learning-based tunnel rock quartz content test system and method

A technology of quartz content and machine learning, which is applied in the direction of instruments, measuring devices, scientific instruments, etc., can solve the problems of continuous and rapid testing of TBM, complicated process, high cost, etc., and achieve the effect of saving workload, continuous testing and saving time

Active Publication Date: 2019-04-12
SHANDONG UNIV
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Problems solved by technology

Although the above quartz content test method is relatively mature, it requires laboratory conditions, and the process of preparing samples and preparing related solutions is complicated, so the cost is also high. Obvi

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  • Machine learning-based tunnel rock quartz content test system and method
  • Machine learning-based tunnel rock quartz content test system and method
  • Machine learning-based tunnel rock quartz content test system and method

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[0038] The disclosure will be further described below in conjunction with the drawings and embodiments.

[0039] It should be pointed out that the following detailed descriptions are all illustrative and are intended to provide further explanations for the application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0040] It should be noted that the terms used here are only for describing specific implementations, and are not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate There are features, steps, operations, devices, comp...

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Abstract

The invention provides a machine learning-based tunnel rock quartz content test system and method. The system comprises an information acquisition system and a learning system, wherein the informationacquisition system is borne on a mechanical arm, approaches to surrounding rocks along with the movement of the mechanical arm and is used for learning indoor rock sample images and rock sample images practically observed via well logging according to received acquired data, recognizing texture features of different rocks through a local binary pattern feature extraction algorithm so as to different differences of different rocks in the aspects of color, structure and construction, integrating feature amounts through a support vector machine algorithm, and establishing a response informationquartz content prediction model so as to calculate contents of quartz in front rocks in TBM tunneling projects.

Description

Technical field [0001] The present disclosure relates to a system and method for testing the quartz content of tunnel rock based on machine learning. Background technique [0002] The statements in this section merely provide background information related to the present disclosure, and do not necessarily constitute prior art. [0003] TBM, also known as Tunnel Boring Machine (Tunnel Boring Machine), has been widely used in tunnel construction. It has the advantages of reduced labor intensity, convenient construction organization, fast construction speed, low environmental disturbance, and high safety. In the TBM tunneling process, the quartz content of the front rock mass affects the degree of wear of the cutter head, so it is decisive for the rock tunneling machine to adjust the tunneling parameters and ensure smooth tunneling. At present, the determination of quartz content in rocks mainly includes chemical methods and phase analysis methods. Chemical methods mainly include vol...

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Application Information

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IPC IPC(8): G01N21/21G01N21/84G06K9/62
CPCG01N21/21G01N21/84G06F18/2411G06F18/214
Inventor 薛翊国陈清张立龙孔凡猛邱道宏陶宇帆李广坤崔久华
Owner SHANDONG UNIV
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