CN107843215B - Based on the roughness value fractal evaluation model building method under optional sampling spacing condition - Google Patents
Based on the roughness value fractal evaluation model building method under optional sampling spacing condition Download PDFInfo
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- CN107843215B CN107843215B CN201710823597.3A CN201710823597A CN107843215B CN 107843215 B CN107843215 B CN 107843215B CN 201710823597 A CN201710823597 A CN 201710823597A CN 107843215 B CN107843215 B CN 107843215B
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- 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
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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Abstract
A kind of roughness value fractal evaluation model building method under the spacing condition based on optional sampling, include the following steps: the high pixel picture for 1) choosing the m standard contour line of Barton, the data information of m canonical profile line in picture is extracted, the profile of m canonical profile line is obtained and carries out post-processing；2) program is write in matlab according to yardstick method, structural plane contour line information obtained in (1) is imported, different sampling interval r is set, obtained corresponding N (r) value of m canonical profile line, calculate fractal dimension D；3) dispersion degree of fractal dimension D value under 91 sampling interval sections is analyzed；4) changing rule for exploring fractal dimension D value under different sampling interval intervals, obtains optional sampling spacing r, constructs the function model of optional sampling spacing flowering structure surface roughness coefficient.The present invention can more precisely estimate structural plane roughness coefficient JRC according to optional sampling spacing.
Description
Technical field
The present invention relates to the model structures that a kind of consideration sampling interval influences the evaluation of structural plane roughness coefficient fractal dimension
Construction method, suitable for estimating the occasion of structural plane roughness coefficient according to sampling interval and fractal dimension D value.
Background technique
Rock mass discontinuity controls the mechanical properties such as the deformation and failure of rock mass, and the mechanical property of rock mass discontinuity and its
Surface topography is closely related.Characteristic parameter of the JRC as description scheme face surface topography, the extensive concern by scholars.It closes
In rock structural plane roughness coefficient JRC evaluation method mainly include the following types: empirical estimation method, statistical parameter method, straight flange
Method and fractal dimension method etc..A kind of quantitative method of the fractal dimension method as evaluation rock mass discontinuity surface roughness, by
The extensive concern of scholar is arrived.
About fractal dimension D calculation method there are many kinds of, as yardstick method, package topology, variogram method, spectroscopic methodology, from
Affine fractal method, h-L method etc., wherein in calculation method about two-dimensional fractal dimension D, the most commonly used method first is that yardstick
Method.Lee etc. calculates fractal dimension D using five 2,4,6,8,10mm sampling intervals, Bae analyze sampling interval be 1,2,4,
8, acquired fractal dimension D value when 16,32,64mm, and Zhu Yuxue, Li Yanrong etc. do not provide specific sampling in the literature
Spacing.The fractal dimension D being calculated under more sampling interval is analyzed in the above research, but is not provided between suitable sampling
Away from section.
Week, wound soldier was using different yardstick r measurement joint hatchings, available when proposing that critical yardstick takes 1~3mm
" appropriate fractal dimension ".Kulatilake etc. proposes the new general of a suitably sized range based on the method for linear scale
It reads, Jang etc. applies this method, obtains preferable effect.Not yet network analysis sampling interval in the above analysis and research
Influence to fractal dimension, this be also different researchers calculated result is different or even the reason for it that conflicts mutually.
Summary of the invention
In order to overcome existing structural plane roughness coefficient fractal dimension evaluation method that can not comprehensively consider sampling interval pair
Its deficiency influenced, the present invention provide the structural plane roughness coefficient fractal evaluation mould under a kind of spacing condition based on optional sampling
The construction method of type can more precisely estimate structural plane roughness coefficient JRC according to optional sampling spacing.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of roughness value fractal evaluation model building method under the spacing condition based on optional sampling, the method packet
Include following steps:
1) the high pixel picture for choosing the m standard contour line of Barton, is mentioned using " image " function of matlab software
The data information of m canonical profile line in picture is taken, the profile of m canonical profile line is obtained and carries out post-processing, is saved as
Jpg format；
2) program is write in matlab according to yardstick method, structural plane contour line information obtained in (1) is imported
In matlab software, different sampling interval r is set, obtains corresponding N (r) value of m canonical profile line, C is undetermined constant, is pressed
Corresponding fractal dimension D is calculated according to following formula；
LogN (r)=- Dlogr+C (1)
3) according to formula CV=σ/μ, wherein σ is standard deviation, and μ is average value, and CV is the coefficient of variation, to sampling interval
When section is R=a~bmm, the dispersion degree of 0.1mm≤a≤9.1mm, 1.0mm≤b≤10.0mm, fractal dimension D value are carried out
Analysis, obtain: 1. the coefficient of variation of fractal dimension D value gradually increases with the increase of sampling interval section and hatching roughness
Greatly；2. as sampling interval section R=0.1mm-1.2mm, the coefficient of variation CV of profile line fractal dimension D value is respectively less than 0.05,
Dispersion degree is lower.
4) it explores under different sampling interval intervals, the changing rule of fractal dimension D value obtains optional sampling spacing r, in turn
The function model of optional sampling spacing flowering structure surface roughness coefficient can be constructed:
JRC=1126.95D-1127.50 (2)
Beneficial effects of the present invention are mainly manifested in: (1) it can be considered that sampling interval is to structural plane fractal dimension evaluation side
The influence of method, so that calculated roughness value characteristic value JRC is more representative.(2) it can relatively accurately count
It calculates under optional sampling spacing, the corresponding JRC value of standard contour line line, and new JRC formula has preferable applicability.
Detailed description of the invention
Fig. 1 is the schematic diagram of Barton10 standard contour line.
Fig. 2 is the coefficient of variation CV changing rule of Article 7 hatching.
Fig. 3 is under different sampling intervals, and the fractal dimension D value of hatching compares.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Referring to Fig.1~Fig. 3, the structural plane roughness coefficient fractal evaluation model under a kind of spacing condition based on optional sampling
According to method, comprising the following steps:
1) the high pixel picture for choosing the m standard contour line of Barton, is mentioned using " image " function of matlab software
The data information of m canonical profile line in picture is taken, the profile of m canonical profile line is obtained and carries out post-processing, is saved as
Jpg format；
2) program is write in matlab according to yardstick method, structural plane contour line information obtained in (1) is imported
In matlab software, different sampling interval r is set, obtains corresponding N (r) value of m canonical profile line, C is undetermined constant, is pressed
Corresponding fractal dimension D is calculated according to following formula；
LogN (r)=- Dlogr+C (1)
3) according to formula CV=σ/μ, wherein σ is standard deviation, and μ is average value, and CV is the coefficient of variation, to sampling interval
When section is R=a~bmm, the dispersion degree of 0.1mm≤a≤9.1mm, 1.0mm≤b≤10.0mm, fractal dimension D value are carried out
Analysis.Obtain: 1. the coefficient of variation of fractal dimension D value gradually increases with the increase of sampling interval section and hatching roughness
Greatly；2. as sampling interval section R=0.1mm-1.2mm, the coefficient of variation CV of profile line fractal dimension D value is respectively less than 0.05,
Dispersion degree is lower.
4) it explores under different sampling interval intervals, the changing rule of fractal dimension D value obtains optional sampling spacing r, in turn
Construct the function model of optional sampling spacing flowering structure surface roughness coefficient:
JRC=1126.95D-1127.50 (2).
The present embodiment chooses ten standard contour lines of Barton as research object, and specific embodiment is as follows:
1) the high pixel photo for choosing ten (taking m=10) nominal contour curve of Barton respectively, utilizes matlab
" image " function of software extracts the data information of ten canonical profile lines in picture, obtains the profile of ten canonical profile lines
And post-processing is carried out, jpg format is saved as, as shown in Figure 1；
2) program is write in matlab according to yardstick method, structural plane contour line information obtained in (1) is imported
In matlab software, setting sampling interval section be respectively 0.1mm-1.0mm, 0.2mm-1.1mm ..., 9.1mm-10mm, obtain
To corresponding N (r) value of ten canonical profile lines, corresponding fractal dimension D value is calculated according to following formula；
LogN (r)=- Dlogr+C (1)
3) 91 are sampled according to formula CV=σ/μ (wherein, σ is standard deviation, and μ is average value, and CV is the coefficient of variation)
Under Space Interval, the dispersion degree of fractal dimension D value is analyzed, as shown in Figure 2.It obtains: the 1. variation lines of fractal dimension D value
Number is gradually increased with the increase of sampling interval section and hatching roughness；2. in 0.1mm-1.2mm sampling interval section
Interior, the coefficient of variation CV of profile line fractal dimension D value is respectively less than 0.05, and dispersion degree is lower.
4) setting sampling interval is respectively r1=0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0,1.1,
1.2mm；r2=0.2,0.4,0.6,0.8,1.0,1.2mm；r3=0.3,0.6,0.9,1.2mm；r4=0.6,1.2mm are calculated
To corresponding fractal dimension D, comparing result is shown in Fig. 3, to obtain optional sampling spacing r=0.3,0.6,0.9,1.2mm；
And then construct under optional sampling spacing condition, the model of roughness value JRC and fractal dimension is as follows:
JRC=1126.95D-1127.50 R=0.998 (2)
Wherein, R is fitting parameter.
Claims (1)
1. the roughness value fractal evaluation model building method under a kind of spacing condition based on optional sampling, it is characterised in that:
Described method includes following steps:
1) the high pixel picture for choosing the m standard contour line of Barton extracts figure using " image " function of matlab software
The data information of m canonical profile line in piece obtains the profile of m canonical profile line and carries out post-processing, saves as jpg lattice
Formula；
2) program is write in matlab according to yardstick method, structural plane contour line information obtained in step 1) is imported into matlab
In software, different sampling interval r is set, obtains corresponding N (r) value of m canonical profile line, C is undetermined constant, according to as follows
Formula calculates corresponding fractal dimension D；
LogN (r)=- Dlogr+C (1)
3) according to formula CV=σ/μ, wherein σ is standard deviation, and μ is average value, and CV is the coefficient of variation, to sampling interval section
When for R=a~bmm, the dispersion degree of 0.1mm≤a≤9.1mm, 1.0mm≤b≤10.0mm, fractal dimension D value are analyzed,
Obtain: 1. the coefficient of variation of fractal dimension D value is gradually increased with the increase of sampling interval section and hatching roughness；②
As sampling interval section R=0.1mm-1.2mm, the coefficient of variation CV of profile line fractal dimension D value is respectively less than 0.05, discrete journey
It spends lower；
4) it explores under different sampling interval intervals, the changing rule of fractal dimension D value, obtains optional sampling spacing r, and then construct
The function model of optional sampling spacing flowering structure surface roughness coefficient:
JRC=1126.95D-1127.50 (2).
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| CN109460603B (en) * | 2018-11-07 | 2023-05-16 | 绍兴文理学院 | JRC parameter formula correction method based on self-adaptive correction function |
| CN115930847B (en) * | 2022-09-30 | 2023-09-22 | 中国科学院武汉岩土力学研究所 | Quantitative determination method for roughness evaluation index of three-dimensional structural surface |
| CN116008139B (en) * | 2023-03-27 | 2023-06-23 | 华中科技大学 | Evaluation method and evaluation system for fractal dimension of particles in dispersion system |
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| US5612700A (en) * | 1995-05-17 | 1997-03-18 | Fastman, Inc. | System for extracting targets from radar signatures |
| CN1645049A (en) * | 2004-12-15 | 2005-07-27 | 金华职业技术学院 | Method for determining dimensional size effects of toughness coefficients of typical stone structural surface |
| CN103644866A (en) * | 2013-12-10 | 2014-03-19 | 中国地质大学（武汉） | Rock mass structure surface roughness evaluation method overcoming size effect |
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