CN110415283B - Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane - Google Patents

Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane Download PDF

Info

Publication number
CN110415283B
CN110415283B CN201910592284.0A CN201910592284A CN110415283B CN 110415283 B CN110415283 B CN 110415283B CN 201910592284 A CN201910592284 A CN 201910592284A CN 110415283 B CN110415283 B CN 110415283B
Authority
CN
China
Prior art keywords
anisotropic
variation
coefficient
size
fractal
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910592284.0A
Other languages
Chinese (zh)
Other versions
CN110415283A (en
Inventor
洪陈杰
黄曼
夏才初
罗战友
杜时贵
马成荣
张丹瑜
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Shaoxing
Original Assignee
University of Shaoxing
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Shaoxing filed Critical University of Shaoxing
Priority to CN201910592284.0A priority Critical patent/CN110415283B/en
Publication of CN110415283A publication Critical patent/CN110415283A/en
Application granted granted Critical
Publication of CN110415283B publication Critical patent/CN110415283B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture
    • G06T7/48—Analysis of texture based on statistical description of texture using fractals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Geometry (AREA)
  • Probability & Statistics with Applications (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)
  • Processing Or Creating Images (AREA)

Abstract

A fractal evaluation method for analyzing the characteristic of anisotropic size effect of rock mass structural plane is based on the anisotropic variation coefficient AVC3DThe fractal expression of the anisotropic coefficient of variation is provided by carrying out normalization processing on the anisotropic coefficient of variation and the sampling size and finding that the anisotropic coefficient of variation and the sampling size show a better linear function relationship
Figure DDA0002116454880000011
The method is used for reflecting the size effect rule of the structural surface anisotropy. The invention combines the AVC with the anisotropic variation coefficient3DObtaining a fractal dimension characteristic value to enable the research on the anisotropic fractal behavior of the structural plane to be more representative; AVC for analyzing different sample sizes by using dimension D which does not change along with scale3DAnd realizing the prediction evaluation of the size effect characteristics of the structural surface anisotropy.

Description

Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane
Technical Field
The invention relates to a fractal evaluation method for analyzing the characteristic of the anisotropic size effect of a rock mass structural plane, which is suitable for objectively and really describing the anisotropic size effect rule of the structural plane according to a fractal dimension D.
Background
For the engineering rock mass structural plane, a stable and reasonable scale range is the key for accurately evaluating the mechanical property strength direction of the rock mass structural plane. The determination of the reasonable scale range of the structural surface needs to comprehensively analyze the size effect of the structural surface in each direction. However, the structural surface has complex anisotropy, and the roughness degrees in different directions are different, so that the size effect rule of the anisotropy is difficult to embody.
Considering that the fractal method has better adaptability to quantitatively describe irregular objects, physical quantities and natural phenomena, more scholars apply fractal dimensions to represent anisotropic characteristics of different scales of the structural surface. Wangjinan et al, Kulatilakake et al, reflect the change rule of anisotropy with scale by analyzing the difference of fractal dimension on different direction sections of the structural plane. However, the study of the anisotropic fractal based on the two-dimensional profile considers the local surface information of the structural plane, and the whole representativeness of the information is difficult to embody. Sunza et al propose a fractal description method of roughness of a joint surface based on a three-dimensional root-mean-square resistance angle to study the anisotropic fractal behavior of a structural surface, but the fractal dimension is still obtained through roughness, and anisotropy existing in the roughness can cause the anisotropic generation of the fractal dimension. Based on this, the structural plane anisotropy size effect characteristics should be further studied using a fractal dimension that is not affected by direction.
Recently, Hongchange et al proposed the anisotropic coefficient of variation AVC considering the three-dimensional roughness parameters in the orthogonal direction3DThis parameter provides a new approach to quantitative description of anisotropy.
Disclosure of Invention
In order to overcome the defect that the prior art can not realize fractal evaluation of the anisotropy size effect characteristics of the rock mass structural plane, the invention provides a fractal evaluation method for analyzing the anisotropy size effect characteristics of the rock mass structural plane, and the fractal dimension D objectively and truly reflects the anisotropy size effect rule of the structural plane.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a fractal evaluation method for analyzing anisotropy size effect characteristics of a rock mass structural plane comprises the following steps:
1) acquiring surface three-dimensional topography data of a structural surface with a large range of sizes by using a three-dimensional laser scanner, and then intercepting three-dimensional point cloud data of which the square plane size range of the structural surface to be researched is l multiplied by l;
2) structural plane initial sampling size l obtained based on progressive full-coverage statistical method1×l1And l2×l2Calculating to obtain a propulsion distance delta d and two sampling sizes l1×l1And l2×l2Respectively is
Figure BDA0002116454860000021
3) For a sample size of l1×l1N of1Each structural surface sample is AVC (automatic voltage control) according to the anisotropic coefficient of variation3DBy selecting three-dimensional topography parameters
Figure BDA0002116454860000022
Calculating to obtain the anisotropic variation coefficient of each structural surface sample, and obtaining the sampling size l1×l1All of1Of a sample of structural surfaces
Figure BDA0002116454860000023
Mean value;
4) repeating the step 3) to obtain a sampling size l2×l2Corresponding mean value of anisotropy coefficient of variation
Figure BDA0002116454860000024
And the obtained average value of the anisotropic variation coefficient and the corresponding sampling size area are subjected to logarithmic normalization processing to determine the fractal dimension D of the anisotropic variation coefficient,
Figure BDA0002116454860000025
5) evaluating and predicting other sample sizes l based on the obtained anisotropic coefficient of variation fractal dimension Di×liIs/are as follows
Figure BDA0002116454860000026
The average value of the average value is calculated,
Figure BDA0002116454860000027
wherein i is 1,2, n, which is used to reflect the size effect rule of the structure surface anisotropy.
The invention has the following beneficial effects: (1) AVC incorporating anisotropic coefficient of variation3DObtaining a fractal dimension characteristic value to enable the research on the anisotropic fractal behavior of the structural plane to be more representative; (2) AVC for analyzing different sample sizes by using dimension D which does not change along with scale3DAnd realizing the prediction evaluation of the size effect characteristics of the structural surface anisotropy.
Drawings
FIG. 1 is a flow chart of the method steps of the present invention.
FIG. 2 is a schematic representation of the three-dimensional topography of a 1000mm by 1000mm natural structural surface.
FIG. 3 is a structural plane
Figure BDA0002116454860000031
Schematic representation of variation with sample size.
Fig. 4 is an error analysis diagram of fractal calculation values of anisotropic variation coefficients and actual statistical values at different scales.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 to 4, a fractal evaluation method for analyzing anisotropy size effect characteristics of a rock mass structural plane comprises the following steps:
1) acquiring surface three-dimensional topography data of a structural surface with a large range of sizes by using a three-dimensional laser scanner, and then intercepting three-dimensional point cloud data of which the square plane size range of the structural surface to be researched is l multiplied by l;
2) structural plane initial sampling size l obtained based on progressive full-coverage statistical method1×l1And l2×l2Calculating to obtain a propulsion distance delta d and two sampling sizes l1×l1And l2×l2Respectively is
Figure BDA0002116454860000032
3) For a sample size of l1×l1N of1Each structural surface sample is AVC (automatic voltage control) according to the anisotropic coefficient of variation3DDetermining method, selecting three-dimensional shape parameters
Figure BDA0002116454860000033
Calculating to obtain the anisotropic variation coefficient of each structural surface sample, and obtaining the sampling size l1×l1All of1Of a sample of structural surfaces
Figure BDA0002116454860000034
Mean value;
4) repeating the step 3) to obtain a sampling size l2×l2Corresponding mean value of anisotropy coefficient of variation
Figure BDA0002116454860000035
And carrying out logarithmic normalization processing on the obtained anisotropic variation coefficient mean value and the corresponding sampling size area thereof to determine the fractal dimension of the anisotropic variation coefficient as
Figure BDA0002116454860000036
5) Evaluating and predicting other sample sizes l based on the obtained anisotropic coefficient of variation fractal dimension Di×liIs/are as follows
Figure BDA0002116454860000037
The average value of the average value is calculated,
Figure BDA0002116454860000038
wherein i is 1,2, n, which is used to reflect the size effect rule of the structure surface anisotropy.
This example is illustrated by the natural structure, the specific embodiment being as follows:
1) acquiring three-dimensional surface topography data of a structural surface with a large range of sizes by using a portable laser scanner (Metrascan 3D, Creaform, Canada), and then intercepting three-dimensional point cloud data of the structural surface to be researched, wherein the square plane size range of the structural surface is 1000mm multiplied by 1000mm, as shown in FIG. 2;
2) structural surface samples with the initial sampling sizes of 100mm multiplied by 100mm and 200mm multiplied by 200mm obtained based on a progressive full coverage statistical method are calculated to obtain the samples with the propulsion distance of 100mm and the two corresponding sampling sizes of N1＝100，N2＝81；
3) For 100 structural plane samples with the sampling size of 100mm multiplied by 100mm, AVC is adopted according to the anisotropic variation coefficient3DDetermining method, selecting three-dimensional shape parameters
Figure BDA0002116454860000041
Calculating the anisotropic coefficient of variation of each structural surface sample to obtain all 100 structural surface samples with the sampling size of 100mm multiplied by 100mm
Figure BDA0002116454860000042
The mean value is 0.474;
4) repeating the step 3) to obtain the mean value of the anisotropic variation coefficient corresponding to the sampling size of 200mm multiplied by 200mm
Figure BDA0002116454860000043
Is 0.466, and the obtained anisotropic coefficient of variation mean value and the corresponding sampling size area are subjected to logarithmic normalization processing, and the fractal dimension of the anisotropic coefficient of variation is determined to be-0.016.
5) AVC with other sample sizes of 300mm x 300mm, 400mm x 400mm,. cndot. cndot.3DThe mean values and the calculation results are shown in table 1.
Sample size AVC3D
100mm×100mm 0.474
200mm×200mm 0.466
300mm×300mm 0.461
400mm×400mm 0.457
500mm×500mm 0.454
600mm×600mm 0.452
700mm×700mm 0.450
800mm×800mm 0.448
900mm×900mm 0.447
1000mm×1000mm 0.446
TABLE 1
FIG. 3 is a structural plane AVC rendered from the data of Table 13DDimension effect profile. It is found from the figure that: change of anisotropyThe coefficient of variation decreases with increasing structural plane size. Obtaining AVC from fractal formulas for validation3DThe reliability of the method is shown in fig. 4, an error analysis graph of the fractal calculation value of the anisotropic coefficient of variation of different scales and the actual statistical value is shown, and the result shows that the fractal calculation value and the actual statistical value are nearly consistent. Therefore, the proposed fractal evaluation method for the anisotropic size effect has better applicability.
The embodiments described in this specification are merely illustrative of implementations of the inventive concepts, which are intended for purposes of illustration only. The scope of the present invention should not be construed as being limited to the particular forms set forth in the examples, but rather as being defined by the claims and the equivalents thereof which can occur to those skilled in the art upon consideration of the present inventive concept.

Claims (1)

1. A fractal evaluation method for analyzing anisotropy size effect characteristics of a rock mass structural plane is characterized by comprising the following steps:
1) acquiring surface three-dimensional topography data of a structural surface with a large range of sizes by using a three-dimensional laser scanner, and then intercepting three-dimensional point cloud data of which the square plane size range of the structural surface to be researched is l multiplied by l;
2) structural plane initial sampling size l obtained based on progressive full-coverage statistical method1×l1And l2×l2Calculating to obtain a propulsion distance delta d and two sampling sizes l1×l1And l2×l2Respectively is
Figure FDA0003459573370000011
3) For a sample size of l1×l1N of1Each structural surface sample is AVC (automatic voltage control) according to the anisotropic coefficient of variation3DDetermining method, selecting three-dimensional shape parameters
Figure FDA0003459573370000012
Calculating to obtain the anisotropic variation coefficient of each structural surface sample, and obtaining the sampling size l1×l1All of1Of a sample of structural surfaces
Figure FDA0003459573370000013
Mean value;
4) repeating the step 3) to obtain a sampling size l2×l2Corresponding mean value of anisotropy coefficient of variation
Figure FDA0003459573370000014
And the obtained average value of the anisotropic variation coefficient and the corresponding sampling size area are subjected to logarithmic normalization processing to determine the fractal dimension D of the anisotropic variation coefficient,
Figure FDA0003459573370000015
5) evaluating and predicting other sample sizes l based on the obtained anisotropic coefficient of variation fractal dimension Di×liIs/are as follows
Figure FDA0003459573370000016
The average value of the average value is calculated,
Figure FDA0003459573370000017
wherein i is 1,2, n, which is used to reflect the size effect rule of the structure surface anisotropy.
CN201910592284.0A 2019-07-03 2019-07-03 Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane Active CN110415283B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910592284.0A CN110415283B (en) 2019-07-03 2019-07-03 Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910592284.0A CN110415283B (en) 2019-07-03 2019-07-03 Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane

Publications (2)

Publication Number Publication Date
CN110415283A CN110415283A (en) 2019-11-05
CN110415283B true CN110415283B (en) 2022-04-01

Family

ID=68358783

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910592284.0A Active CN110415283B (en) 2019-07-03 2019-07-03 Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane

Country Status (1)

Country Link
CN (1) CN110415283B (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104834806A (en) * 2015-03-09 2015-08-12 绍兴文理学院 Joint roughness coefficient size effect sampling representativeness evaluation method
CN107036561A (en) * 2016-11-14 2017-08-11 绍兴文理学院 The anisotropic approximate expression method of structural plane roughness based on middle intelligence number function
CN107239629A (en) * 2017-06-15 2017-10-10 内蒙古科技大学 The Analysis of Fractal Dimension method that a kind of rock structural face laboratory reasonable size is determined
CN107292017A (en) * 2017-06-15 2017-10-24 内蒙古科技大学 The multi-fractal parameters analysis method that a kind of rock structural face laboratory reasonable size is determined
CN109859301A (en) * 2019-03-04 2019-06-07 浙江大学 A kind of rock structural face roughness value fining characterizing method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104834806A (en) * 2015-03-09 2015-08-12 绍兴文理学院 Joint roughness coefficient size effect sampling representativeness evaluation method
CN107036561A (en) * 2016-11-14 2017-08-11 绍兴文理学院 The anisotropic approximate expression method of structural plane roughness based on middle intelligence number function
CN107239629A (en) * 2017-06-15 2017-10-10 内蒙古科技大学 The Analysis of Fractal Dimension method that a kind of rock structural face laboratory reasonable size is determined
CN107292017A (en) * 2017-06-15 2017-10-24 内蒙古科技大学 The multi-fractal parameters analysis method that a kind of rock structural face laboratory reasonable size is determined
CN109859301A (en) * 2019-03-04 2019-06-07 浙江大学 A kind of rock structural face roughness value fining characterizing method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Characterization of Anisotropy of Joint Surface Roughness and Aperture by Variogram Approach Based on Digital Image Processing Technique;S. J. Chen et al.;《Rock Mech Rock Eng》;20150730;第855-876页 *
岩体结构面粗糙度各向异性特征及尺寸效应分析;陈世江 等;《岩石力学与工程学报》;20150131;第34卷(第1期);第57-66页 *
结构面粗糙度系数分形评价与采样间距的关联性研究;马文会 等;《科技通报》;20171231;第33卷(第12期);第30-34、113页 *

Also Published As

Publication number Publication date
CN110415283A (en) 2019-11-05

Similar Documents

Publication Publication Date Title
AU2017239499B2 (en) Digital rock analysis systems and methods that reliably predict a porosity-permeability trend
AU2013240570B2 (en) An efficient method for selecting representative elementary volume in digital representations of porous media
Tomutsa et al. Analysis of chalk petrophysical properties by means of submicron-scale pore imaging and modeling
US9285301B2 (en) Digital rock analysis systems and methods with reliable multiphase permeability determination
Liu et al. Reconstruction of 3-D digital cores using a hybrid method
Kandroodi et al. Detection of natural gas pipeline defects using magnetic flux leakage measurements
US20210182597A1 (en) Process parameter prediction using multivariant structural regression
Shell et al. Demonstration of model-based inversion of electromagnetic signals for crack characterization
Tan et al. An innovative method to evaluate hydraulic conductivity of a single rock fracture based on geometric characteristics
Chen et al. Intelligent adaptive sampling guided by Gaussian process inference
Hajizadeh et al. An algorithm for 3D pore space reconstruction from a 2D image using sequential simulation and gradual deformation with the probability perturbation sampler
Aldrin et al. Model-based inverse methods for bolt-holt eddy current (BHEC) inspections
CN110415283B (en) Fractal evaluation method for analyzing anisotropic size effect characteristics of rock mass structural plane
Mukherjee et al. A kriging-based magnetic flux leakage method for fast defect detection in massive pipelines
CN110516281B (en) Evaluation method for quantitatively representing anisotropic size effect of rock mass structural plane
CN107340159B (en) Method for selecting representative sample of shear strength of three-dimensional structural surface
Boyle Kriging neighbourhood analysis by slope of regression and weight of mean–evaluation with the Jura data set
Falque et al. From the skin-depth equation to the inverse RFEC sensor model
Gyimóthy Optimal sampling for fast eddy current testing inversion by utilising sensitivity data
Chen et al. Size effect characteristics of structural surfaces by improved projective covering method
Packulak et al. Evaluating characterization methods for joint surface roughness
Zou et al. 2D and 3D evaluation of joint roughness exposed by rock cores
Mukherjee et al. A Kriging based fast and efficient method for defect detection in massive pipelines using magnetic flux leakages
Aldrin et al. Model-based inverse methods for sizing cracks of varying shape and location in bolt-hole eddy current (BHEC) inspections
CN112577450B (en) Engineering rock mass structural surface roughness coefficient determination method based on multiple regression analysis

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant