TBM operation parameter decision-making method and system based on deep learning

A deep learning and operating parameter technology, applied in neural learning methods, data processing applications, forecasting, etc., can solve the problems of slow excavation, poor adaptability, and rapid wear of cutterheads, reducing energy costs, ensuring construction speed, and miniaturizing The effect of construction energy consumption

Active Publication Date: 2020-05-12
SHANDONG UNIV
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Problems solved by technology

[0004] At the same time, many engineering practices have shown that the adaptability of tunnel boring machines to geological conditions is poor. Geological disasters such as water and mud inrush and landslides, as well as major accidents such as machine jams and even machine crashes caused by this, have seriously affected the safety of tunnel boring machines. Construction presents major challenges
On the other hand, during the excavation proc

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  • TBM operation parameter decision-making method and system based on deep learning

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[0033] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0035] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

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Abstract

The invention provides a TBM operation parameter decision-making method and system based on deep learning. The TBM operation parameter decision-making method comprises the steps of: receiving TBM tunneling real-time mechanical parameter information; constructing a real-time mapping relationship between the total propulsive force and the total torque of the cutter head and the propulsive speed andthe rotating speed of the cutter head by utilizing a deep learning neural network; and on the basis of the obtained mapping relation, setting a tunneling speed set value and a cutterhead rotating speed set value which are matched with each other according to the requirements of a construction site to form a TBM operation parameter decision scheme. The problems that at present, when a driver drivesthe TBM, the relation between rock mass changed along with forward tunneling of the TBM and the mechanical interaction of the TBM cannot be quantitatively known, blind decision making is conducted onTBM operation parameters, and various kinds of efficiency and safety are caused are solved. The optimal strategy of tunneling is efficiently and timely calculated only according to the machine data recorded by the TBM under the condition that a coring experiment does not need to be carried out on the rock mass in the tunnel, and contributions are made to efficient and safe tunneling of the TBM.

Description

technical field [0001] The disclosure belongs to the technical field of TBM real-time intelligent decision-making, and relates to a method and system for decision-making of TBM operating parameters based on deep 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] Compared with the traditional drilling and blasting method, tunnel boring machine construction has significant advantages such as "fast excavation speed, high hole quality, high comprehensive economic benefits, and safe and civilized construction". Developed countries such as Japan, the United States, and Europe use roadheaders for construction. The proportion of tunnels in my country exceeds 80%, and with the continuous development of tunnel construction in China, tunnel boring machines will also be used more and more. [0004] At the same time, many engineering practices ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/08G06N3/04G06N3/08
CPCG06Q10/04G06Q10/0637G06Q50/08G06N3/08G06N3/045
Inventor 刘斌朱颜王亚旭王瑞睿高博洋赵光祖王滨
Owner SHANDONG UNIV
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