CN106769276B - Three-dimensional structure face aliquot part choosing method based on Dice similarity measure - Google Patents
Three-dimensional structure face aliquot part choosing method based on Dice similarity measure Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/02—Devices for withdrawing samples
Abstract
A kind of three-dimensional structure face aliquot part choosing method based on Dice similarity measure, comprising the following steps: (1) obtain structural plane three-dimensional point cloud coordinate data；(2) interception is in the test structural plane coordinate data of different location；(3) horizontal centre of interception test structural plane is found out, the intersection of vertical plane and structural plane three-dimensional contoured surface is the topography line of structural plane different directions；(4) roughness value of the structural fece sample different directions of all interceptions is calculated；(5) statistical analysis of JRC is carried out by different measurement directions；(6) feature vector of structural plane roughness anisotropy assembly average is calculated；(7) feature vector of structural plane roughness anisotropy statistics measured result is calculated；(8) similitude for comparing the feature vector of each test structural plane and assembly average, using the highest sample of similarity as the aliquot part under the size condition.Energy accurate evaluation typical sample of the present invention instructs structural fece sample to choose.
Description
Technical field
The invention belongs to field of engineering technology, are related to a kind of optimum option side of structural face shear strength aliquot part
Method, specifically the present invention is based on the laser scanning datas of structural plane surface undulation form, are extracted on large scale sample
The structural plane roughness statistical data of different location, different directions passes through structural plane roughness system using assembly average as standard
The similarity measure of number measured data and statistical result is analyzed, and determines aliquot part.This method solve artificial in direct shear test
The random problem of sampling realizes the quantitative accurate selection of rock mass discontinuity sample.
Background technique
Direct shear test is the important method of determining structural face shear strength, has all been referred in different tests specification or regulation
Close requirement that structural fece sample prepares, such as sampling method, sample quantities, preservation means of transportation etc..However, structural plane is certainly
The product of right earth history process, development characteristics have apparent heterogencity and anisotropy.Even in same big ruler
The structural plane that the different location of very little structural fece sample is chosen, configuration of surface often have biggish otherness.Work for a long time
Cheng personnel suffer from how to judge whether selected structural fece sample is representative always, often by subjective experience to survey
Examination structural fece sample is judged and is screened.Forefathers are studies have shown that structural plane roughness is the pass for influencing mechanical property of structural plane
Key factor.When wall rock intensity is essentially identical, structural face shear strength is determined by roughness value.Therefore, carry out and be based on structure
The shearing strength sample of surface roughness analysis, which is preferably studied, has highly important theory significance and engineering application value.
2006, Du Shigui etc. disclosed a kind of representative evaluation method of structural fece sample, and this method passes through in rock mass
It is evenly arranged survey section on structural plane, the different statistical analysis for surveying segment structure surface roughness coefficient are then carried out, by assembly average
As the characteristic value of roughness value, judge that structure is interviewed by the otherness of the roughness value of each sample and characteristic value
The representativeness of sample.
2013, Huang Man etc. disclosed a kind of subsize rock model structural structural fece sample representative based on stratified probability sampling
Property sampling method, technological core is to acquire total sample size with Stratified Sampling formula, and the classification according to layer power determine it is each
The sample size of layer, to meet the statistical accuracy requirement of test.
2015, Du Shigui etc. disclosed a kind of structural plane roughness coefficient dimensional effect sample representation evaluation method,
This method mainly passes through the serial mesostructure surface roughness coefficient probability density function maximum value of calculating, with each structural fece sample
Roughness value carry out relative deviation analysis, come judge sample selection representative degree.
2016, Du Shigui etc. disclosed a kind of evaluation of structural plane roughness coefficient based on Dice Similarity Measures
Method, this method judge two by the nominal contour curve of analysis Barton and the similitude of test profile curvilinear characteristic vector
The interval range for tieing up the roughness value of structural plane contour curve, is not related to the selection of structural plane aliquot part.
However, the complex three-dimensional attribute of structural plane surface undulation form is ignored in the studies above, using two-dimensional structure
The statistical measurements in face analyze typical sample, ignore roughness anisotropic character, and then affect structural fece sample
Representativeness evaluation is chosen with accurate.
Summary of the invention
In order to overcome the influence, existing method that artificial subjective factor chooses structural face shear strength sample in the prior art
Can not accurate evaluation sample representativeness and selecting structure interview sample representativeness it is insufficient the problems such as, the present invention is from structural plane table
The complex three-dimensional attribute of face rolling shape sets out, and proposes a kind of structural face shear strength generation based on the analysis of Dice similarity measure
The choosing method of table sample.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of three-dimensional structure face aliquot part choosing method based on Dice similarity measure, the choosing method include with
Lower step:
(1) large-scale structure interview sample is scanned using three-dimensional laser instrument, obtains structural plane three-dimensional point cloud number of coordinates
According to；
(2) it according to the experimental design size of structural fece sample, intercepts and is within the scope of the three-dimensional coordinate of large-scale structure face
The structural plane coordinate data of different location；
(3) horizontal centre for finding out intercepted test structural plane, using the normal by the horizontal centre as rotation axis, with
Set angle deflection is interval, makees the vertical plane of the horizontal plane of structural plane, the plane and structural plane three-dimensional contoured surface
Intersection is the topography line of structural plane different directions, and profile line length is equal to the lab design size of structural fece sample；
(4) according to the surface coordinate information of structural plane contour line, all sections are calculated using Barton straight flange method simplicity formula
The roughness value JRC of the structural fece sample different directions taken；
(5) statistical analysis of JRC is carried out by different measurement directions, is determined respectively to statistical result according to the JRC of all samples
Maximum, minimum value, and solve assembly average；
(6) feature vector of structural plane roughness anisotropy assembly average is calculated；
(7) the JRC value according to each test structural plane all directions actual measurement, calculates structural plane roughness anisotropy statistics
The feature vector of measured result；
(8) according to Dice similarity measure, the similitude of the feature vector of each test structural plane and assembly average is compared,
Using the highest sample of similarity as the aliquot part under the size condition.
Beneficial effects of the present invention are mainly manifested in: accurate representation evaluation and selecting structure interview sample.
Detailed description of the invention
Fig. 1 is example structure face surface three dimension coordinate data figure；
Fig. 2 be structural plane surface three dimension coordinate data interception schematic diagram under the conditions of test size (with upper right corner 50cm ×
For 50cm structural plane)；
Fig. 3 be structural plane surface three dimension coordinate data interception top view under the conditions of test size (with upper right corner 50cm ×
For 50cm structural plane)；
Fig. 4 is the schematic diagram for testing structural plane surface profile line (by taking 165 ° of azimuths as an example).
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Referring to Fig.1~Fig. 4, a kind of three-dimensional structure face aliquot part choosing method based on Dice similarity measure are described
Choosing method the following steps are included:
(1) large-scale structure interview sample is scanned using high-precision three-dimensional laser scanner, it is three-dimensional obtains structural plane
Point cloud coordinate data；
(2) it according to the experimental design size of structural fece sample, intercepts and is within the scope of the three-dimensional coordinate of large-scale structure face
The structural plane coordinate data of different location；
(3) horizontal centre for finding out intercepted test structural plane, using the normal by the horizontal centre as rotation axis, with
Direction initialization angle is interval, makees the vertical plane of the horizontal plane of structural plane, the intersection of the plane and structural plane three-dimensional contoured surface
For the topography line of structural plane different directions, profile line length is equal to the lab design size of structural fece sample；
(4) according to the surface coordinate information of structural plane contour line, all sections are calculated using Barton straight flange method simplicity formula
The roughness value JRC of the structural fece sample different directions taken；
(5) statistical analysis of JRC is carried out by different measurement directions, is determined respectively to statistical result according to the JRC of all samples
Maximum, minimum value, and solve assembly average；
(6) feature vector of structural plane roughness anisotropy assembly average is calculated；
(7) the JRC value according to each test structural plane all directions actual measurement, calculates structural plane roughness anisotropy statistics
The feature vector of measured result；
(8) according to Dice similarity measure, the similitude of the feature vector of each test structural plane and assembly average is compared,
Using the highest sample of similarity as the aliquot part under the size condition.
A kind of example: three-dimensional structure face aliquot part choosing method based on Dice similarity measure, comprising the following steps:
(1) field condition select large scale granite structure face (1m × 1m), using high-precision three-dimensional laser scanner into
Row scanning, obtains complicated topography three-dimensional coordinate data, and point cloud data is as shown in Figure 1；
(2) specimen size used in joint straight shear test obtains big for 50cm × 50cm in 3 D laser scanning
On the basis of dimensional structure interviews sample coordinate data, 100 test structural planes are intercepted with step pitches such as 50cm × 50cm, test structure
Interview the entire coarse scale structures face of sample uniform fold；Fig. 2 cuts for upper right corner 50cm × 50cm structural plane surface three dimension coordinate data
Schematic diagram is taken, Fig. 3 is the top view of structural plane interception；
(3) horizontal centre for finding out intercepted test structural plane, using the normal of the horizontal centre as rotation axis, 15 ° of sides
It is interval to angle, makees the vertical plane of the horizontal plane of structural plane respectively, the intersection of the plane and structural plane three-dimensional contoured surface is
The topography line of structural plane different directions, profile line length are equal to 50cm, by taking 165 ° of azimuths as an example, corresponding structural plane
Contour line is as shown in Figure 4；
(4) according to the surface coordinate information of structural plane contour line, all sections are calculated using Barton straight flange method simplicity formula
The roughness value JRC of the structural fece sample different directions taken, expression formula are
In formulaFor the convex amplitude ident value of structural plane surface outline curves tooth, L is structural plane contour curve length, tiFor knot
The feature vector of structure face JRC measured value.
Table 1 is the JRC number of 10 typical structure face all directions in the test structural plane intercepted at 100 different locations
According to.
Table 1
(5) statistical analysis of JRC is carried out by different measurement directions, is determined respectively to statistical result according to the JRC of all samples
Each direction JRC greatest measurementWith minimum measured valueAssembly average m is solved, the feature of assembly average is obtained
Vector mi=[9.9,11.4,12.1,10.8,12.4,12.7,7.0,10.3,7.5,4.2,4.5,7.3,9. 9,11.4,12.1,
10.8,12.4,12.7,7.0,10.3,7.5,4.2,4.5,7.3].Table 2 be it is all test structural plane JRC assembly averages with
Standard deviation；
Table 2
(6) according to all directions JRC assembly average as a result, and be normalized, obtain the assembly average of JRC
Feature vector M:
Table 3 is that all directions of structural plane JRC assembly average normalize as a result, MiFor all directions JRC assembly average
Feature vector miNormalized value, Mi=[0.48,0.60,0.50,0.48,0.32,0.63,0.25,0.45,0.38,0.29,
0.32,0.26,0.48,0.60,0.50,0.48,0.32,0.63,0.25,0.45,0.38,0.29,0.32,0.26]；
Table 3
(7) the JRC value according to each test structural plane all directions actual measurement, determines its feature vector T
TiFor all directions JRC measured value feature vector tiNormalized value.
Table 4
(8) according to Dice Similarity Measures, respectively determine all directions actual measurement JRC and statistical average JRC value tag to
The similarity of amount, formula are as follows:
Similarity measure test result is as shown in table 5, it is found that similarity corresponding to specimen coding 56 is maximum, value is
0.9944, it can be as aliquot part.Its coordinate position is Y-axis 0.28m to 0.78m in the section X-axis 0.28m to 0.78m
In section.
| Number | Similarity | Number | Similarity | Number | Similarity | Number | Similarity | Number | Similarity |
| 1 | 0.7771 | 21 | 0.7765 | 41 | 0.8143 | 61 | 0.8045 | 81 | 0.9029 |
| 2 | 0.6767 | 22 | 0.8068 | 42 | 0.7877 | 62 | 0.9275 | 82 | 0.9531 |
| 3 | 0.6545 | 23 | 0.7284 | 43 | 0.8737 | 63 | 0.9777 | 83 | 0.9739 |
| 4 | 0.7401 | 24 | 0.9372 | 44 | 0.9441 | 64 | 0.9564 | 84 | 0.9739 |
| 5 | 0.6660 | 25 | 0.8680 | 45 | 0.9403 | 65 | 0.9398 | 85 | 0.9634 |
| 6 | 0.8704 | 26 | 0.9607 | 46 | 0.9468 | 66 | 0.9540 | 86 | 0.9116 |
| 7 | 0.8832 | 27 | 0.9319 | 47 | 0.8758 | 67 | 0.9442 | 87 | 0.9497 |
| 8 | 0.9298 | 28 | 0.9529 | 48 | 0.9050 | 68 | 0.8840 | 88 | 0.9298 |
| 9 | 0.9576 | 29 | 0.9722 | 49 | 0.9543 | 69 | 0.8934 | 89 | 0.8675 |
| 10 | 0.9721 | 30 | 0.9637 | 50 | 0.9568 | 70 | 0.8911 | 90 | 0.8343 |
| 11 | 0.8140 | 31 | 0.7766 | 51 | 0.8023 | 71 | 0.8897 | 91 | 0.9507 |
| 12 | 0.6582 | 32 | 0.7349 | 52 | 0.8700 | 72 | 0.8595 | 92 | 0.9586 |
| 13 | 0.5820 | 33 | 0.8846 | 53 | 0.9288 | 73 | 0.9571 | 93 | 0.9779 |
| 14 | 0.6764 | 34 | 0.9475 | 54 | 0.9509 | 74 | 0.9829 | 94 | 0.9507 |
| 15 | 0.8431 | 35 | 0.9452 | 55 | 0.9443 | 75 | 0.9892 | 95 | 0.8993 |
| 16 | 0.9055 | 36 | 0.9331 | 56 | 0.9944 | 76 | 0.9695 | 96 | 0.9162 |
| 17 | 0.9073 | 37 | 0.9390 | 57 | 0.9217 | 77 | 0.9580 | 97 | 0.9086 |
| 18 | 0.9330 | 38 | 0.9506 | 58 | 0.9658 | 78 | 0.9490 | 98 | 0.8396 |
| 19 | 0.9375 | 39 | 0.9784 | 59 | 0.9417 | 79 | 0.9166 | 99 | 0.8019 |
| 20 | 0.9799 | 40 | 0.9650 | 60 | 0.9338 | 80 | 0.8233 | 100 | 0.5750 |
Table 5
Core of the invention is the structural plane roughness statistical number according to different location, different directions on large scale sample
According to using assembly average as standard, the assembly average by structural plane all directions JRC is similar to measured value feature vector
Degree, which is analyzed, determines aliquot part.If the method for change measurement JRC is belonged to using similar similarity measure analysis method
In the range of the claims in the present invention and its equivalent technologies, then the present invention is also intended to encompass including these changes and deformation.
Claims (1)
1. a kind of three-dimensional structure face aliquot part choosing method based on Dice similarity measure, it is characterised in that: the selection
Method the following steps are included:
(1) large-scale structure interview sample is scanned using three-dimensional laser scanner, obtains structural plane three-dimensional point cloud number of coordinates
According to；
(2) according to the experimental design size of structural fece sample, interception is in difference within the scope of the three-dimensional coordinate of large-scale structure face
The structural plane coordinate data of position；
(3) horizontal centre for finding out intercepted test structural plane, using the normal by the horizontal centre as rotation axis, with setting
Angle direction angle is interval, makees the vertical plane of the horizontal plane of structural plane, the intersection of the plane and structural plane three-dimensional contoured surface
For the topography line of structural plane different directions, profile line length is equal to the lab design size of structural fece sample；
(4) according to the surface coordinate information of structural plane contour line, all interceptions are calculated using Barton straight flange method simplicity formula
The roughness value JRC of structural fece sample different directions；
(5) statistical analysis of JRC is carried out by different measurement directions, is determined most respectively to statistical result according to the JRC of all samples
Greatly, minimum value, and solve assembly average；
(6) feature vector of structural plane roughness anisotropy assembly average is calculated；
(7) the JRC value according to each test structural plane all directions actual measurement calculates the statistics actual measurement of structural plane roughness anisotropy
As a result feature vector；
(8) according to Dice similarity measure, the similitude of the feature vector of each test structural plane and assembly average is compared, by phase
Like the highest sample of degree as the aliquot part under the size condition.
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| CN109470181A (en) * | 2018-11-07 | 2019-03-15 | 绍兴文理学院 | Method is determined based on the structural plane two dimension roughness value of progressive sampling |
| CN109509184A (en) * | 2018-11-07 | 2019-03-22 | 绍兴文理学院 | Method is determined based on the structural plane three-dimensional roughness coefficient of all standing sampling |
| CN109470168A (en) * | 2018-11-07 | 2019-03-15 | 绍兴文理学院 | The progressive sampling method of structural plane two-dimensional silhouette curve |
| CN109493424A (en) * | 2018-11-07 | 2019-03-19 | 绍兴文理学院 | The all standing sampling method of structural plane 3 d surface topography |
| CN114370844B (en) * | 2021-12-20 | 2024-03-22 | 包头钢铁（集团）有限责任公司 | Statistical method for uniformity of characteristic values of surface of plate |
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