CN109520461A - The statistical sample number of array of sizes rock structural plane roughness sample determines method - Google Patents
The statistical sample number of array of sizes rock structural plane roughness sample determines method Download PDFInfo
- Publication number
- CN109520461A CN109520461A CN201811267490.6A CN201811267490A CN109520461A CN 109520461 A CN109520461 A CN 109520461A CN 201811267490 A CN201811267490 A CN 201811267490A CN 109520461 A CN109520461 A CN 109520461A
- Authority
- CN
- China
- Prior art keywords
- group
- coefficient
- sample
- structural plane
- grade
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/30—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring roughness or irregularity of surfaces
Abstract
A kind of statistical sample number of array of sizes rock structural plane roughness sample determines method, minimum samples required for array of sizes rock structural plane roughness are determined than the method for analysis by grade, the dispersion degree that each rock structural plane roughness coefficient in group is expressed with the coefficient of variation, eliminates the influence that roughness value average value difference compares degree of variation；Reflect the difference of dispersion degree between group and group than analyzing by grade.When kth group is similar to k+1 group dispersion degree, the corresponding C.V. of adjacent sample number is almost the same, and grade tends to 1 than coefficient；This invention ensures that the reliability of JRC statistical measurements, avoids influence of the conventional method because of sample number deficiency to measurement result.
Description
Technical field
The invention belongs to field of engineering technology, minimum needed for being related to a kind of determining rock mass discontinuity coefficient of roughness statistical measurement
The quantitative calculation method of sample number, determination array of sizes rock structural plane roughness coefficient especially proposed by the invention are minimum
The method of statistical sample number solves the problems, such as smallest sample number be difficult to determine in collecting sample in the past needed for, it is ensured that rock
The reliability of body structural plane JRC statistical measurements.
Background technique
Structural plane is the important component of rock mass, plays main control action to the engineering characteristic of rock mass.Structural plane
Research is the element task of analysis project rock stability.Structural plane roughness coefficient (JRC) is description rough surface fluctuating shape
The mechanical index that state influences mechanical property of structural plane has important engineering significance to Stability Analysis of Rock Mass.In practical behaviour
During work, structural plane roughness coefficient is often used to directly or indirectly judge each large-engineering such as reservoir slopes, tunnel surrounding
Stability.Structural face shear strength is the key parameter of engineering rock mass stability analysis and consolidation process design.Numerous studies table
Bright, the roughness that structural plane surface undulation is formed has a significant impact to the mechanical property especially shearing strength of structural plane.Ba Dun
(N.R.Barton) by the direct shear test of structural face shear strength studies have shown that the wall rock intensity and surface undulation shape of structural plane
State is to determine the principal element of shearing strength, and propose famous JRC-JCS empirical estimating model.Due to rock mass discontinuity table
Face form has each matter opposite sex, anisotropy, the feature of heterogencity and dimensional effect.At structural plane roughness coefficient (JRC)
When orientation survey, there is also differences for the structural plane configuration of surface of each measuring section, have each matter opposite sex, anisotropy, heterogencity
With the feature of dimensional effect.Therefore, in order to accurately determine rock structural plane roughness coefficient, people are generally surveyed using statistics
The method of amount guarantees the reliability of rock structural plane roughness coefficient measurement result, and some representative researchs are as follows:
Du Shigui (2004) draws the contour curve of the survey section of 12 length 10cm by profilograph, according to fluctuating width
Degree Ry0 calculates each roughness value for surveying section, calculates to obtain its desired value by different roughness values, then by JRC dimensional effect
Fractal model conversion rock structural plane roughness coefficient, has the rock structural plane roughness system of dimensional effect for quantitative statistical analysis
Number JRCn value provides effective means.
Huang Man etc. (2013) passes through the measurement to the rock structural plane roughness coefficient (JRC) that 18 groups of specimen sizes are 10cm
And statistical analysis, having obtained specimen length is probability density function of the 10cm based on normal distribution law.
Yong Rui etc. (2015) thinks to study structural plane roughness from probability statistics angle, and there are sample numbers by artificial
It regulation and quantity the deficiencies of not accounting for dimensional effect less, proposes to carry out large sample statistics according to array of sizes sample, building knot
After structure surface roughness coefficient dimensional effect probability density estimation, structural fece sample representativeness evaluation index is obtained.
Du Shigui etc. (2016) passes through the structural plane roughness coefficient ordered series of numbers to same rock mass discontinuity surface different directions
Statistical analysis, quantitative determination finishes the degree of structure surface roughness index anisotropy.
Ma Chengrong etc. (2017) is in order to overcome existing structure surface roughness coefficient parting evaluation method to be unable to accurate description knot
The deficiency of structure surface roughness, by calculating fractal dimension D and obtaining to 24 parallel contour curves of slate structural plane surface rendering
The corresponding roughness value characteristic value of 24 contour curves, the roughness value for finally counting structural plane along test direction are average
Value, the as roughness value of structural plane.
In the studies above, structural plane roughness statistical sample number is not examined by artificially providing or empirically value
Consider the requirement of array of sizes sample statistical sample number, test result accuracy is difficult to be guaranteed.From the point of view of probability statistics,
Statistical sample quantity is bigger, and representativeness is better, but therewith bring be measurement and calculation amount increase to take a substantial amount of time and
Energy；Statistical sample quantity is fewer, representative poorer, so that measurement result and this statistical result of bulk sample have large error.Cause
This, the side that there is an urgent need to propose to determine rock structural plane roughness coefficient minimum statistics sample number under the conditions of a kind of array of sizes
Method.
Summary of the invention
In order to solve in current structural plane roughness coefficient statistical measurement sample size by artificially providing or empirically value
And the problem of sample number needed for not being able to satisfy array of sizes structural plane.The present invention provides a kind of array of sizes rock mass discontinuities
The statistical sample number of roughness sample determines method, determines array of sizes rock structural plane roughness than the method for analysis by grade
Required minimum samples.Technical solution of the present invention ensure that the reliability of JRC statistical measurements, avoid tradition side
Influence of the method because of sample number deficiency to measurement result.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of statistical sample number of array of sizes rock structural plane roughness sample determines method, comprising the following steps:
(1) engineering rock structural face analyzed required for selecting extracts n with profilograph on rock mass discontinuity surface
Specimen length is the contour curve of l, and wherein the value of n is sufficiently big, and Zhao Jing etc. (2016) is to Rock And Soil rational sample number
Discussion in, by probability statistical analysis, show that value is with regard to sufficiently large when sample size reaches 120；
(2) structural plane roughness coefficient and record corresponding to the n contour curve that specimen length is l are calculated；
(3) n sample is grouped, first group is s sample, and second group is s+c, third group be s+2c it is a,,
Wherein s is any sample quantities, and c is every group of increased any sample quantities, amounts to m group, and m is natural number, calculates simultaneously list note
The average value mu and standard deviation sigma of rock structural plane roughness coefficient corresponding to recording every group；
(4) with acquired in (3) data calculate each group coefficient of variation C.V.kAnd it records, C.V.k=σ/μ, k=1,2,3, m,
Wherein k is the group of each group coefficient of variation；
(5) pass through C.V.k/C.V.k+1Grade is obtained than coefficient, k=1,2,3, m-1, be sequentially recorded result and obtain a grade ratio
Sequence；
(6) scatter plot is drawn with the data obtained in (5), ratio is 1 when former and later two values are identical, former and later two numerical value
When gap is larger, ratio is further away from 1.Scatter plot is observed, all the points after some point are all fallen in the section ± γ %, are said
It is smallest sample number needed for l cm that the representative sample size of this bright point, which is the specimen length,；
(7) above-mentioned (1)~(6) step is repeated, average value mu, standard deviation sigma, the coefficient of variation are calculated and carries out grade than analysis, really
Minimum samples needed for other fixed specimen lengths.
The coefficient of variation is generally used to eliminate the shadow that unit compares two or more data variance degree with average difference
It rings.When comparing two groups of data discrete degree sizes, if the measurement scale of two groups of data differs too big or data dimension
Difference should eliminate the influence of measurement scale and dimension at this time, and the coefficient of variation can accomplish this point, it is initial data standard
The ratio of difference and raw value.In the present invention, since the average value of each group structural plane roughness coefficient is not fully identical, because
This, the dispersion degree of each rock structural plane roughness coefficient in group is expressed with the coefficient of variation, and it is average to eliminate roughness value
The influence that value difference compares degree of variation.
Reflect the difference of dispersion degree between group and group than analyzing by grade.When kth group is similar to k+1 group dispersion degree
When, the corresponding C.V. of adjacent sample number is almost the same, and grade tends to 1 than coefficient.In engineering, allowable error be generally γ=±
2%.Therefore, after sample size reaches a certain level, front and back data ratio is strictly controlled at ± 2%, i.e., from certain point
When origination class is all fallen between 0.98~1.02 than coefficient, the requirement that sample size is enough and satisfaction is to computational accuracy can be considered.
Compared with the existing methods, beneficial effect is mainly manifested in the present invention: on the one hand solving sample size by artificial
Regulation or the empirically deficiency of value, on the other hand can effectively avoid due to sample number is excessive waste of resource or because of hits not
Foot leads to the influence of statistical result bigger error.The invention proposes a kind of determining array of sizes rock structural plane roughness coefficients
The method of minimum statistics sample number has biggish implementary value and economic benefit.
Detailed description of the invention
Fig. 1 is that the grade that specimen length is 10cm compares analysis chart.
Fig. 2 is that the grade that specimen length is 20cm compares analysis chart.
Fig. 3 is that the grade that specimen length is 30cm compares analysis chart.
Fig. 4 is that the grade that specimen length is 20cm compares analysis chart.
Fig. 5 is that the grade that specimen length is 50cm compares analysis chart.
Fig. 6 is that the grade that specimen length is 60cm compares analysis chart.
Fig. 7 is that the grade that specimen length is 70cm compares analysis chart.
Fig. 8 is that the grade that specimen length is 80cm compares analysis chart.
Fig. 9 is that the grade that specimen length is 90cm compares analysis chart.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing.
Referring to Fig.1~Fig. 9, a kind of statistical sample number of array of sizes rock structural plane roughness sample determine method, institute
State method the following steps are included:
(1) engineering rock structural face analyzed required for selecting extracts n with profilograph on rock mass discontinuity surface
Specimen length is the contour curve of l, and wherein the value of n is sufficiently big, and Zhao Jing etc. (2016) is to Rock And Soil rational sample number
Discussion in, by probability statistical analysis, show that value is with regard to sufficiently large when sample size reaches 120；
(2) structural plane roughness coefficient and record corresponding to the n contour curve that specimen length is l are calculated；
(3) n sample is grouped, first group is s sample, and second group is s+c, third group be s+2c it is a,,
Wherein s is any sample quantities, and c is every group of increased any sample quantities, amounts to m group, and m is natural number, calculates simultaneously list note
The average value mu and standard deviation sigma of rock structural plane roughness coefficient corresponding to recording every group；
(4) with acquired in (3) data calculate each group coefficient of variation C.V.kAnd it records, wherein C.V.k=σ/μ, k=1,2,
3, m, wherein k is the group of each group coefficient of variation；
(5) pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3, m-1, be sequentially recorded result and obtain a grade ratio
Sequence；
(6) scatter plot is drawn with the data obtained in (5), ratio is 1 when former and later two values are identical, former and later two numerical value
When gap is larger, ratio is further away from 1.Scatter plot is observed, all the points after some point are all fallen in the section ± γ %, are said
It is smallest sample number needed for l cm that the representative sample size of this bright point, which is the specimen length,
(7) above-mentioned (1)~(6) step is repeated, average value mu, standard deviation sigma, the coefficient of variation are calculated and carries out grade than analysis, really
Minimum samples needed for other fixed sampling lengths.
Example: the experimental data of the present embodiment is derived from the typical slate in Changshan city, Zhejiang Province green stone town locality stone pit
Structural plane.
It is respectively 10cm, 20cm, 30cm, 40cm, 50cm, 60cm, 70cm, 80cm, 90cm that sample length, which is given below,
The determination process of smallest sample number.
1, engineering rock structural face is selected, extracts n=120 specimen length with profilograph on rock mass discontinuity surface
For the contour curve of l=10cm；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 1；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 2；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 1.Scatter plot is observed, after the 12nd group
All the points are all fallen in the section γ=± 2%, and the 12nd group of corresponding sample number is 65, illustrate sampling length for l=10cm most
Small sample quantity is 65.
Table 1 is the coefficient of variation tables of data of specimen length 10cm, and table 2 is the grade of specimen length 10cm than coefficient data table.
Table 1
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 0.91 | 12 | 1.00 |
| 2 | 1.22 | 13 | 1.00 |
| 3 | 0.93 | 14 | 0.98 |
| 4 | 1.06 | 15 | 0.99 |
| 5 | 0.98 | 16 | 0.99 |
| 6 | 0.95 | 17 | 1.00 |
| 7 | 0.94 | 18 | 1.01 |
| 8 | 1.03 | 19 | 1.01 |
| 9 | 1.01 | 20 | 1.01 |
| 10 | 1.01 | 21 | 0.99 |
| 11 | 1.03 | 22 | 1.00 |
Table 2
1, the profile that n=120 sampling length is l=20cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 3；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 4；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 2.Scatter plot is observed, after the 13rd group
All the points are all fallen in the section γ=± 2%, and the 13rd group of corresponding sample number is 70, illustrate sampling length for l=20cm most
Small sample quantity is 70.
Table 3 is the coefficient of variation tables of data of specimen length 20cm, and table 4 is the grade of specimen length 20cm than coefficient data table.
| Sample number | The coefficient of variation | Sample number | The coefficient of variation |
| 10 | 0.37 | 70 | 0.28 |
| 15 | 0.32 | 75 | 0.29 |
| 20 | 0.31 | 80 | 0.29 |
| 25 | 0.30 | 85 | 0.29 |
| 30 | 0.29 | 90 | 0.29 |
| 35 | 0.30 | 95 | 0.28 |
| 40 | 0.30 | 100 | 0.28 |
| 45 | 0.29 | 105 | 0.28 |
| 50 | 0.29 | 110 | 0.28 |
| 55 | 0.29 | 115 | 0.28 |
| 60 | 0.29 | 120 | 0.28 |
| 65 | 0.29 |
Table 3
Table 4
1, the profile that n=120 sampling length is l=30cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 5；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 6；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 3.Scatter plot is observed, after the 2nd group
All the points are all fallen in the section γ=± 2%, and the 2nd group of corresponding sample number is 15, illustrate that sampling length is the minimum of l=30cm
Sample size is 15.
Table 5 is the coefficient of variation tables of data of specimen length 30cm, and table 6 is the grade of specimen length 30cm than coefficient data table.
Table 5
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 1.07 | 12 | 1.00 |
| 2 | 1.01 | 13 | 1.00 |
| 3 | 1.00 | 14 | 1.00 |
| 4 | 1.02 | 15 | 1.00 |
| 5 | 1.01 | 16 | 1.01 |
| 6 | 1.01 | 17 | 0.99 |
| 7 | 1.01 | 18 | 1.00 |
| 8 | 0.99 | 19 | 1.01 |
| 9 | 1.01 | 20 | 1.00 |
| 10 | 1.00 | 21 | 1.00 |
| 11 | 0.99 | 22 | 1.01 |
Table 6
1, the profile that n=120 sampling length is l=40cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 7；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 8；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 4.Scatter plot is observed, after the 1st group
All the points are all fallen in the section γ=± 2%, and the 1st group of corresponding sample number is 10, illustrate that sampling length is the minimum of l=40cm
Sample size is 10.
Table 7 is the coefficient of variation tables of data of specimen length 40cm, and table 8 is the grade of specimen length 40cm than coefficient data table.
| Sample number | The coefficient of variation | Sample number | The coefficient of variation |
| 10 | 0.31 | 70 | 0.30 |
| 15 | 0.31 | 75 | 0.30 |
| 20 | 0.31 | 80 | 0.30 |
| 25 | 0.31 | 85 | 0.30 |
| 30 | 0.30 | 90 | 0.30 |
| 35 | 0.30 | 95 | 0.30 |
| 40 | 0.30 | 100 | 0.30 |
| 45 | 0.30 | 105 | 0.30 |
| 50 | 0.30 | 110 | 0.30 |
| 55 | 0.30 | 115 | 0.30 |
| 60 | 0.30 | 120 | 0.30 |
| 65 | 0.30 |
Table 7
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 1.00 | 12 | 1.00 |
| 2 | 1.02 | 13 | 1.00 |
| 3 | 0.99 | 14 | 1.00 |
| 4 | 1.02 | 15 | 1.00 |
| 5 | 1.00 | 16 | 1.00 |
| 6 | 1.01 | 17 | 1.00 |
| 7 | 0.99 | 18 | 1.00 |
| 8 | 1.00 | 19 | 1.00 |
| 9 | 1.01 | 20 | 1.00 |
| 10 | 1.00 | 21 | 1.00 |
| 11 | 1.00 | 22 | 1.00 |
Table 8
1, the profile that n=120 sampling length is l=50cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 9；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 10；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 5.Scatter plot is observed, after the 1st group
All the points are all fallen in the section γ=± 2%, and the 1st group of corresponding sample number is 10, illustrate that sampling length is the minimum of l=50cm
Sample size is 10.
Table 9 is the coefficient of variation tables of data of specimen length 50cm, and table 10 is the grade of specimen length 50cm than coefficient data table.
Table 9
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 1.00 | 12 | 1.00 |
| 2 | 1.01 | 13 | 1.00 |
| 3 | 1.00 | 14 | 1.00 |
| 4 | 1.02 | 15 | 1.01 |
| 5 | 0.99 | 16 | 1.00 |
| 6 | 1.00 | 17 | 1.00 |
| 7 | 1.00 | 18 | 1.00 |
| 8 | 1.00 | 19 | 1.00 |
| 9 | 1.00 | 20 | 1.00 |
| 10 | 1.00 | 21 | 1.00 |
| 11 | 1.00 | 22 | 1.00 |
Table 10
1, the profile that n=120 sampling length is l=60cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 11；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 12；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 6.Scatter plot is observed, after the 1st group
All the points are all fallen in the section γ=± 2%, and the 1st group of corresponding sample number is 10, illustrate that sampling length is the minimum of l=60cm
Sample size is 10.
Table 11 is the coefficient of variation tables of data of specimen length 60cm, and table 12 is that the grade of specimen length 60cm compares coefficient data
Table.
| Sample number | The coefficient of variation | Sample number | The coefficient of variation |
| 10 | 0.26 | 70 | 0.26 |
| 15 | 0.27 | 75 | 0.26 |
| 20 | 0.26 | 80 | 0.26 |
| 25 | 0.26 | 85 | 0.26 |
| 30 | 0.26 | 90 | 0.26 |
| 35 | 0.26 | 95 | 0.26 |
| 40 | 0.26 | 100 | 0.26 |
| 45 | 0.26 | 105 | 0.26 |
| 50 | 0.26 | 110 | 0.26 |
| 55 | 0.26 | 115 | 0.26 |
| 60 | 0.26 | 120 | 0.26 |
| 65 | 0.26 |
Table 11
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 0.98 | 12 | 1.00 |
| 2 | 1.01 | 13 | 1.00 |
| 3 | 1.00 | 14 | 1.00 |
| 4 | 1.01 | 15 | 1.00 |
| 5 | 1.01 | 16 | 1.00 |
| 6 | 1.01 | 17 | 1.01 |
| 7 | 0.99 | 18 | 1.00 |
| 8 | 1.00 | 19 | 1.00 |
| 9 | 1.00 | 20 | 1.00 |
| 10 | 1.00 | 21 | 1.00 |
| 11 | 1.00 | 22 | 1.00 |
Table 12
1, the profile that n=120 sampling length is l=70cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 13；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 14；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 7.Scatter plot is observed, after the 4th group
All the points are all fallen in the section γ=± 2%, and the 4th group of corresponding sample number is 25, illustrate that sampling length is the minimum of l=70cm
Sample size is 25.
Table 13 is the coefficient of variation tables of data of specimen length 70cm, and table 14 is that the grade of specimen length 70cm compares coefficient data
Table.
| Sample number | The coefficient of variation | Sample number | The coefficient of variation |
| 10 | 0.22 | 70 | 0.20 |
| 15 | 0.21 | 75 | 0.20 |
| 20 | 0.21 | 80 | 0.20 |
| 25 | 0.20 | 85 | 0.20 |
| 30 | 0.20 | 90 | 0.20 |
| 35 | 0.20 | 95 | 0.20 |
| 40 | 0.20 | 100 | 0.20 |
| 45 | 0.20 | 105 | 0.20 |
| 50 | 0.20 | 110 | 0.20 |
| 55 | 0.20 | 115 | 0.20 |
| 60 | 0.20 | 120 | 0.20 |
| 65 | 0.20 |
Table 13
Table 14
1, the profile that n=120 sampling length is l=80cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and 5 samples of every increase are considered as one later
Group amounts to m=23 group, calculates the average value mu and standard of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Poor σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in Table 15；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 16；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 8.Scatter plot is observed, after the 3rd group
All the points are all fallen in the section γ=± 2%, and the 3rd group of corresponding sample number is 20, illustrate that sampling length is the minimum of l=80cm
Sample size is 20.
Table 15 is the coefficient of variation tables of data of specimen length 80cm, and table 16 is that the grade of specimen length 80cm compares coefficient data
Table.
Table 15
| Group | Grade compares coefficient | Group | Grade compares coefficient |
| 1 | 1.00 | 12 | 1.00 |
| 2 | 1.03 | 13 | 1.00 |
| 3 | 1.01 | 14 | 1.00 |
| 4 | 0.99 | 15 | 1.00 |
| 5 | 1.01 | 16 | 1.00 |
| 6 | 1.00 | 17 | 1.00 |
| 7 | 1.01 | 18 | 1.00 |
| 8 | 1.00 | 19 | 1.00 |
| 9 | 1.00 | 20 | 1.00 |
| 10 | 1.00 | 21 | 1.00 |
| 11 | 1.00 | 22 | 1.00 |
Table 16
1, the profile that n=120 sampling length is l=90cm is extracted with profilograph on same rock mass discontinuity surface
Curve；
2, structural plane roughness coefficient and record corresponding to each survey section are calculated separately；
3, n=120 sample is grouped, first group is s=10 sample, and every c=5 sample of increase is considered as later
One group, amount to m=23 group, calculates the average value mu and mark of simultaneously rock structural plane roughness coefficient corresponding to every group of list records
Quasi- difference σ；
4, with the coefficient of variation and the record for calculating resulting standard deviation sigma in step 3 divided by average value mu and acquiring each group
C.V.k, k=1,2,3 ..., 23, as shown in table 17；
5, pass through C.V.k/C.V.k+1, obtain grade than coefficient, k=1,2,3 ..., 22, be sequentially recorded result and obtain a grade ratio
Sequence, as shown in table 18；
6, scatter plot drafting is carried out with the data obtained in step 5, as shown in Figure 9.Scatter plot is observed, after the 21st group
All the points are all fallen in the section γ=± 2%, and the 21st group of corresponding sample number is 110, illustrate sampling length for l=90cm most
Small sample quantity is 110.
Table 17 is the coefficient of variation tables of data of specimen length 90cm, and table 18 is that the grade of specimen length 90cm compares coefficient data
Table.
| Sample number | The coefficient of variation | Sample number | The coefficient of variation |
| 10 | 0.08 | 70 | 0.05 |
| 15 | 0.06 | 75 | 0.05 |
| 20 | 0.07 | 80 | 0.05 |
| 25 | 0.06 | 85 | 0.05 |
| 30 | 0.05 | 90 | 0.05 |
| 35 | 0.06 | 95 | 0.05 |
| 40 | 0.06 | 100 | 0.05 |
| 45 | 0.06 | 105 | 0.05 |
| 50 | 0.05 | 110 | 0.05 |
| 55 | 0.06 | 115 | 0.05 |
| 60 | 0.05 | 120 | 0.05 |
| 65 | 0.05 |
Table 17
Table 18.
Claims (1)
1. a kind of statistical sample number of array of sizes rock structural plane roughness sample determines method, which is characterized in that the side
Method the following steps are included:
(1) engineering rock structural face analyzed required for selecting extracts n sample with profilograph on rock mass discontinuity surface
Length is the contour curve of l；
(2) structural plane roughness coefficient and record corresponding to the n contour curve that specimen length is l are calculated；
(3) n sample is grouped, first group is s sample, and second group is s+c, third group be s+2c it is a,, wherein
S is any sample quantities, and c is every group of increased any sample quantities, amounts to m group, and m is natural number, calculates and list records are every
The average value mu and standard deviation sigma of the corresponding rock structural plane roughness coefficient of group；
(4) with acquired in (3) data calculate each group coefficient of variation C.V.kAnd it records, C.V.k=σ/μ, k=1,2,3, m, wherein k
For the group of each group coefficient of variation；
(5) pass through C.V.k/C.V.k+1Grade is obtained than coefficient, k=1,2,3, m-1, be sequentially recorded result and obtain grade and compare sequence；
(6) scatter plot is drawn with the data obtained in (5), ratio is 1 when former and later two values are identical, the gap of former and later two numerical value
When larger, ratio is further away from 1；Scatter plot is observed, all the points after some point are all fallen in the section ± γ %, illustrate this
Sample size representated by a point is that the specimen length is smallest sample number needed for l cm；
(7) above-mentioned (1)~(6) step is repeated, average value mu, standard deviation sigma, the coefficient of variation are calculated and carries out grade than analysis, determines it
Minimum samples needed for his specimen length.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811267490.6A CN109520461B (en) | 2018-10-29 | 2018-10-29 | Method for determining statistical sample number of series-size rock structural surface roughness samples |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811267490.6A CN109520461B (en) | 2018-10-29 | 2018-10-29 | Method for determining statistical sample number of series-size rock structural surface roughness samples |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109520461A true CN109520461A (en) | 2019-03-26 |
| CN109520461B CN109520461B (en) | 2020-10-27 |
Family
ID=65772947
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811267490.6A Active CN109520461B (en) | 2018-10-29 | 2018-10-29 | Method for determining statistical sample number of series-size rock structural surface roughness samples |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109520461B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110516281A (en) * | 2019-07-03 | 2019-11-29 | 绍兴文理学院 | A kind of evaluation method of quantification characterization rock mass discontinuity anisotropic dimensions effect |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558094A (en) * | 2013-09-23 | 2014-02-05 | 绍兴文理学院 | Method for representatively sampling subsize rock model structural surface sample sampled based on layering probability |
| CN105243394A (en) * | 2015-11-03 | 2016-01-13 | 中国矿业大学 | Evaluation method for performance influence degree of classification models by class imbalance |
| CN106529156A (en) * | 2016-10-28 | 2017-03-22 | 西南交通大学 | Method for determining rock soil parameter standard value |
| WO2017051996A1 (en) * | 2015-09-24 | 2017-03-30 | 에스케이텔레콤 주식회사 | Non-invasive type fetal chromosomal aneuploidy determination method |
| CN107273609A (en) * | 2017-06-14 | 2017-10-20 | 电子科技大学 | One kind is based on Kriging model gear drive reliability estimation methods |
| CN107656902A (en) * | 2017-09-13 | 2018-02-02 | 绍兴文理学院 | Structural plane roughness coefficient statistical method under different sampling intervals |
| CN108647455A (en) * | 2018-05-16 | 2018-10-12 | 中国建筑科学研究院有限公司 | Concrete member bearing capacity variation coefficient analysis method based on statistical experimental data |
-
2018
- 2018-10-29 CN CN201811267490.6A patent/CN109520461B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558094A (en) * | 2013-09-23 | 2014-02-05 | 绍兴文理学院 | Method for representatively sampling subsize rock model structural surface sample sampled based on layering probability |
| WO2017051996A1 (en) * | 2015-09-24 | 2017-03-30 | 에스케이텔레콤 주식회사 | Non-invasive type fetal chromosomal aneuploidy determination method |
| CN105243394A (en) * | 2015-11-03 | 2016-01-13 | 中国矿业大学 | Evaluation method for performance influence degree of classification models by class imbalance |
| CN106529156A (en) * | 2016-10-28 | 2017-03-22 | 西南交通大学 | Method for determining rock soil parameter standard value |
| CN107273609A (en) * | 2017-06-14 | 2017-10-20 | 电子科技大学 | One kind is based on Kriging model gear drive reliability estimation methods |
| CN107656902A (en) * | 2017-09-13 | 2018-02-02 | 绍兴文理学院 | Structural plane roughness coefficient statistical method under different sampling intervals |
| CN108647455A (en) * | 2018-05-16 | 2018-10-12 | 中国建筑科学研究院有限公司 | Concrete member bearing capacity variation coefficient analysis method based on statistical experimental data |
Non-Patent Citations (3)
| Title |
|---|
| CAI-CHU XIA: "New Peak Shear Strength Criterion of Rock Joints Based on Quantified Surface Description", 《ROCK MECHANICS AND ROCK ENGINEERING》 * |
| 李善皋: "可靠度理论用于路基边坡稳定性的分析", 《路基工程》 * |
| 潘雪航: "基于模糊评价和灰色预测对国家脆弱性的定量分析", 《皖西学院学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110516281A (en) * | 2019-07-03 | 2019-11-29 | 绍兴文理学院 | A kind of evaluation method of quantification characterization rock mass discontinuity anisotropic dimensions effect |
| CN110516281B (en) * | 2019-07-03 | 2023-10-24 | 绍兴文理学院 | Evaluation method for quantitatively representing anisotropic size effect of rock mass structural plane |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109520461B (en) | 2020-10-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104834806B (en) | Structural plane roughness coefficient dimensional effect sample representation evaluation method | |
| CN105221133B (en) | A kind of method and apparatus that content of organic carbon of hydrocarbon source rock is determined based on well logging multi-parameter | |
| Silva et al. | Nonstationarities in the occurrence rates of flood events in Portuguese watersheds | |
| CN103592690B (en) | Method based on electric imaging logging porosity spectrum information automatic Reservoir Recognition crack | |
| CN108489402A (en) | The quick fine obtaining value method of open mine side slope ROCK MASS JOINT scale based on 3 D laser scanning | |
| CN108733961B (en) | Slope slip stability discrimination method considering unsaturated zone effect | |
| CN104833333B (en) | Structural plane roughness coefficient dimensional effect sample characterization unit determines method | |
| CN110210776A (en) | A kind of constructing tunnel dynamic risk appraisal procedure based on monitoring measurement | |
| CN108561126B (en) | Simple method for determining organic porosity of shale gas reservoir | |
| CN106951595A (en) | A kind of accurate obtaining value method of engineering rock structural face shear strength | |
| CN104535420B (en) | The method of railway bed soil deformation state load threshold value under measure static load | |
| CN107288016A (en) | A kind of bituminous paving milling quality evaluating method based on three-dimensional laser detection technique | |
| CN108445188A (en) | The following slope stability expression of harshness coefficient size effect of rock structural face based on middle intelligence interval function | |
| CN106482674A (en) | The approximate expression method of the structural plane roughness dimensional effect based on middle intelligence number function | |
| CN105257284B (en) | A kind of logged well using element capture spectra determines the method and device of tufaceous content | |
| CN109543236A (en) | Method is determined based on the rock structural plane roughness statistical sample number of variation lines several levels score analysis | |
| CN107036561A (en) | The anisotropic approximate expression method of structural plane roughness based on middle intelligence number function | |
| CN104881564B (en) | The construction method of structural plane roughness coefficient dimensional effect probability density estimation | |
| CN109520461A (en) | The statistical sample number of array of sizes rock structural plane roughness sample determines method | |
| CN115131486A (en) | Engineering exploration data acquisition system and method | |
| CN110968840A (en) | Method for judging grade of tunnel surrounding rock based on magnetotelluric sounding resistivity | |
| CN102982244A (en) | Fuzzy comprehensive evaluation method of geological strength index | |
| CN106443782A (en) | Fault and fracture development density and uniformity and combined style evaluation method | |
| CN111779477B (en) | Fractal theory-based dynamic evaluation method for complexity of hydraulic fracture | |
| CN115618457A (en) | Bedding rock slope three-dimensional geological model building and stability evaluation method |
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 |