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Rockburst grade prediction method and system based on principal component analysis and BP neural network

A BP neural network and principal component analysis technology, applied in the field of level prediction, can solve the problem of redundant data calculation burden and other problems, and achieve the effects of rich evaluation information, reduced calculation amount, and high result accuracy.

Pending Publication Date: 2020-03-17
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In the current multi-index comprehensive prediction method, there is a certain correlation between most rockburst prediction indicators, resulting in redundant data and computational burden.

Method used

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  • Rockburst grade prediction method and system based on principal component analysis and BP neural network
  • Rockburst grade prediction method and system based on principal component analysis and BP neural network
  • Rockburst grade prediction method and system based on principal component analysis and BP neural network

Examples

Experimental program
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Embodiment 1

[0048] This embodiment discloses a rockburst grade prediction method based on principal component analysis and BP neural network, which specifically includes the following steps:

[0049] Step 1: Divide the rockburst grade into four grades based on domestic and foreign construction statistics and rockburst intensity data. The higher the grade, the stronger the rockburst;

[0050] Step 2: Based on the physical and mechanical properties of rock mass and domestic and foreign engineering data examples, determine all the influencing factor indicators for rockburst classification in high geostress areas;

[0051] Step 3: Collect the index variables and corresponding actual rockburst level data in the actual project, and normalize the mean variance of the index variable values;

[0052] Step 4: adopt principal component analysis (PCA) to carry out principal component analysis to the index variable that has been excavated, obtain several principal component variables, and correspond t...

Embodiment 2

[0087] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the program, the following steps are implemented, including:

[0088] Classify the strength of the rockburst and the grade of the rockburst;

[0089] Determine all the influencing factor indicators of rockburst classification in high geostress areas;

[0090] Obtain the index variables and the corresponding actual rockburst level data in the actual project, and normalize the mean variance of the index variable values;

[0091] Using the principal component analysis method to conduct principal component analysis on the index variables obtained from the excavation, a number of principal component variables are obtained, which correspond to the rockburst grade determined according to the strength of the rockburst;

[0092] The obtained index variables are used as input indic...

Embodiment 3

[0095] The purpose of this embodiment is to provide a computer-readable storage medium.

[0096] 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:

[0097] Classify the strength of the rockburst and the grade of the rockburst;

[0098] Determine all the influencing factor indicators of rockburst classification in high geostress areas;

[0099] Obtain the index variables and the corresponding actual rockburst level data in the actual project, and normalize the mean variance of the index variable values;

[0100] Using the principal component analysis method to conduct principal component analysis on the index variables obtained from the excavation, a number of principal component variables are obtained, which correspond to the rockburst grade determined according to the strength of the rockburst;

[0101] The obtained index variables are used as input indicators, and t...

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Abstract

The invention discloses a rockburst grade prediction method and system based on principal component analysis and a BP neural network. The rockburst grade prediction method comprises the steps: gradingrockburst according to rockburst strength degrees; determining all influence factor indexes of rockburst grading in the high ground stress area; obtaining index variables in actual engineering and corresponding actual rockburst grade data, and performing mean variance normalization on index variable values; carrying out principal component analysis on the excavated index variables by adopting a principal component analysis method to obtain a plurality of principal component variables, and enabling the principal component variables to correspond to the rockburst grade determined according to the rockburst strength degree; taking the plurality of obtained index variables as input indexes, taking the corresponding rockburst levels as output values, carrying out training learning on the databy adopting a BP neural network algorithm, and establishing a mathematical model of each index-rockburst level; and obtaining an index variable value near an unexcavated tunnel face, carrying out principal component analysis based on the average value, the standard deviation and the like of the training data, extracting a corresponding principal component variable, obtaining a principal component,and then carrying out rockburst grade prediction by using the obtained mathematical model.

Description

technical field [0001] The invention belongs to the technical field of rockburst prediction, in particular to a rockburst level prediction method and system based on principal component analysis and BP neural network. 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] Rockburst is one of the most common geological disasters in deep buried tunnels with high ground stress. Rockburst is the process of underground engineering excavation under high ground stress conditions. The hard and brittle surrounding rock causes the stress differentiation of the cave wall due to excavation and unloading, so that the elastic strain energy stored in the rock mass is suddenly released, resulting in bursting, loosening and spalling. , ejection or even throwing phenomenon, which seriously threatens the safety of construction personnel and equipment and affects ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/2135
Inventor 薛翊国李广坤邱道宏苏茂鑫公惠民
Owner SHANDONG UNIV
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