Unlock instant, AI-driven research and patent intelligence for your innovation.

PCA-KNN-based TBM construction surrounding rock comprehensive grading prediction method

A technology of surrounding rock classification and prediction method, applied in prediction, CAD numerical modeling, data processing applications, etc., can solve the problem that it is difficult to see the specific situation of the surrounding rock of the tunnel face, achieve rich evaluation information, and solve the disaster of dimensionality , the effect of high accuracy

Active Publication Date: 2020-06-02
SHANDONG UNIV
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The TBM model is larger and will block the face of the tunnel, making it difficult to see the specific conditions of the surrounding rock in front of the tunnel;

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • PCA-KNN-based TBM construction surrounding rock comprehensive grading prediction method
  • PCA-KNN-based TBM construction surrounding rock comprehensive grading prediction method
  • PCA-KNN-based TBM construction surrounding rock comprehensive grading prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0058] This embodiment discloses such as figure 1 As shown, a comprehensive classification prediction method for TBM construction surrounding rock based on principal component analysis and k-nearest neighbor algorithm (PCA-KNN), the working steps are as follows:

[0059] Step 1. Using the actual construction speed of TBM as an indicator, combined with domestic and foreign TBM construction statistics, the construction surrounding rock is divided into four levels: Ⅰ, Ⅱ, Ⅲ, Ⅳ. The larger the number of levels, the slower the TBM construction;

[0060] Step 2. Based on the conditions of the rock mass itself, the interaction of rock machines and domestic and foreign engineering data examples, determine all the influencing factor indicators for the comprehensive classification of surrounding rock in TBM construction;

[0061] Step 3. Collect the index data of the influencing factors in the work area that need to be predicted and the corresponding comprehensive surrounding rock grade ...

Embodiment 2

[0095] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, the following steps are implemented, including:

[0096] Use the actual construction speed of TBM as an index to classify the construction surrounding rock;

[0097] Determine all the influencing factor indicators for the comprehensive classification of surrounding rock in TBM construction;

[0098] Obtain the index data of the influencing factors in the work area that need to be predicted and the corresponding comprehensive surrounding rock classification data classified according to the construction speed, and normalize the mean and variance of the index values ​​of the influencing factors;

[0099] The principal component analysis method is used to conduct principal component analysis on the influencing factors obtained from the excavation, and several prin...

Embodiment 3

[0104] The purpose of this embodiment is to provide a computer-readable storage medium.

[0105] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are performed:

[0106] Use the actual construction speed of TBM as an index to classify the construction surrounding rock;

[0107] Determine all the influencing factor indicators for the comprehensive classification of surrounding rock in TBM construction;

[0108] Obtain the index data of the influencing factors in the work area that need to be predicted and the corresponding comprehensive surrounding rock classification data classified according to the construction speed, and normalize the mean and variance of the index values ​​of the influencing factors;

[0109] The principal component analysis method is used to conduct principal component analysis on the influencing factors obtained from the excavation, and several principal compon...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a PCA-KNN-based TBM construction surrounding rock comprehensive grading prediction method, and the method comprises the steps: carrying out the training and learning of a plurality on obtained principal component variables and corresponding comprehensive surrounding rock grades by employing a k-nearest neighbor algorithm, and building a mathematic model of each index-comprehensive surrounding rock grade; extracting principal components from the detection data based on the training data and verifying the accuracy of the established model by using the established mathematical model; and obtaining influence factor index values near an unexcavated tunnel face, carrying out principal component analysis based on the average value, standard deviation and the like of the training data, obtaining corresponding principal components, and then carrying out TBM construction surrounding rock comprehensive grading prediction by using the obtained mathematical model. Accordingto the method, difficulties caused by uncertainty of rock mass conditions, complexity of rock-machine interaction and the like are overcome, main influence factors of TBM performance and surrounding rock prediction are effectively selected, the FPI can be used as a link for linking tunneling parameters and geological parameters, and the selected geological factors are also main influence factors influencing the TBM performance.

Description

technical field [0001] The invention belongs to the technical field of comprehensive grading prediction of surrounding rocks, in particular to a method for comprehensive grading prediction of surrounding rocks in TBM construction based on PCA-KNN. 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] In tunnels constructed with TBM (Tunnel Boring Machine), since TBM is sensitive to geological changes and the initial investment is large, it is difficult to judge the feasibility of TBM construction, TBM type selection, TBM construction schedule and cost estimation according to geological conditions. very important. [0004] At present, the traditional tunnel surrounding rock classification methods at home and abroad mostly serve the traditional construction methods such as drill and blast method, and cannot effectively guide the construction of ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/08G06F30/20G06F111/10
CPCG06Q10/04G06Q10/06393G06Q50/08
Inventor 薛翊国李广坤邱道宏公惠民张贯达
Owner SHANDONG UNIV