Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Small fault strike extension length detecting method

A detection method and technology of small faults, applied in the direction of prediction, instrumentation, data processing applications, etc., can solve the problem of low accuracy of prediction models

Inactive Publication Date: 2015-01-07
SHANDONG UNIV OF SCI & TECH
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the defects existing in the prior art, aiming at the problem that the accuracy of the prediction model of the existing small fault strike extension length is not high, the design provides a small fault strike extension length prediction method based on genetic algorithm optimization SVM, which can Effectively improve the prediction accuracy

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
  • Small fault strike extension length detecting method
  • Small fault strike extension length detecting method
  • Small fault strike extension length detecting method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] The specific technical solution of the prediction method involved in this embodiment includes the following steps:

[0034] (1) Statistical fault element data: Take the coal seam excavation engineering plan as the base map, and conduct statistics and analysis on the five fault elements of strike extension, strike, inclination, dip and drop of small coal seam faults;

[0035] (2) Determine the relevant factors for the extension length of small faults: use the grey correlation analysis method to determine the correlation between the extension length of the small fault strike and the four elements of the fault direction, inclination, dip and drop, and select the element with a correlation greater than 0.5 as the small fault For the correlation factor of the length of the trend extension, the steps of the gray correlation analysis method are as follows:

[0036] ① Construct the original data matrix, and set the statistical data of the extension length of the small fault to form th...

Embodiment 2

[0057] In this embodiment, according to the steps of embodiment 1, the length of the strike extension of the small fault in the 7th coal seam of a certain coal mine is predicted. figure 2 Is a schematic diagram of the optimization result of the genetic algorithm in this embodiment, image 3 It is a schematic diagram of the experimental results of the training set prediction of this embodiment. Table 1 is the statistical fault element data:

[0058] Table 1 Statistical sample table of fault elements

[0059]

[0060]

[0061] Use the data in Table 1 to perform grey correlation analysis to determine the correlation between the strike extension length of the small fault and the four elements of fault strike, inclination, dip and drop. The results are shown in Table 2. It can be seen that the fault strike, inclination, dip, drop and the extension of the fault strike The correlation degree of the length is greater than 0.75, and the correlation is relatively large. Therefore, the fault...

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 belongs to the technical field of mine fault parameter element detection, and relates to a small fault strike extension length detecting method. The method comprises the steps that statistics and analysis are carried out on fault elements at first, the degree of association between the small fault strike extension length and other fault elements is determined by means of the gray relative analysis method, normalization preprocessing is carried on the correlation factor data of the small fault strike extension length, a dataset is generated, a training set and a testing set are selected, the training set and the genetic algorithm are utilized for optimizing an SVM model, the SVM model is built, and finally the testing set is utilized for testing the SVM module. According to the small fault strike extension length detecting method, the overall design principle is reliable, the computing method is mature, the modeling technology is safe, the prediction data are accurate, and the detection environment is good.

Description

Technical field: [0001] The invention belongs to the technical field of mine fault zone parameter element detection, and relates to a small fault strike extension length prediction method, in particular to a small fault strike extension length detection method based on genetic algorithm optimization support vector machine (SVM). Background technique: [0002] With the continuous improvement of the mechanization and automation of coal mining, the mining department’s requirements for engineering design and layout, selection of mining methods, etc., have increasingly paid attention to the accuracy of geological detection. The extension of the fault direction and the fall are the fault predictions. Two important parameters, the greater the strike length and drop of the fault, the greater the impact of the fault on coal production; in reality, with mine exploration, roadway excavation and face stoping, it is easier to find the drop and dip of a small fault , Tendency and strike, but i...

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
IPC IPC(8): G06Q10/04G06Q50/02G06N3/12
CPCG06Q10/04G06N3/12G06Q50/02
Inventor 于小鸽施龙青邱梅韩进
Owner SHANDONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com