CN117194862A - Method for realizing JRC estimation based on curve accumulated slope similarity - Google Patents
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Abstract
The invention discloses a method for realizing JRC estimation based on curve accumulated slope similarity. And (3) finding out the structural surface standard contour line most similar to the actual measurement curve by calculating the similarity of the cumulative slopes of the actual measurement curve and the 10 structural surface standard contour lines of Barton, and endowing the actual measurement curve with the JRC value corresponding to the structural surface standard contour line, thereby finally realizing the estimation of the JRC value of the actual measurement curve. The method is simple and has high accuracy.
Description
Technical Field
The invention belongs to the technical field of engineering geological investigation, and particularly relates to a method for realizing JRC estimation based on curve accumulated slope similarity.
Background
Barton and Choubey in 1977 in document 1"BARTONN,CHOUBEYV.The shear strength ofrockjoints in theory and practice[J ]. Rock Mechanics,1977, 10 (1/2): 1-54' provides that the structural surface roughness coefficient JRC is adopted to quantitatively describe the structural surface shape difference of the structural surface roughness fluctuation, 10 structural surface standard contour lines are constructed, and each standard curve corresponds to a corresponding JRC value, as shown in figure 1. Standard profiles corresponding to the standard contour lines of the 10 structural faces have been incorporated into the ISRM specification.
In actual field work, a visual comparison method is generally adopted, that is, by obtaining an actual structural surface morphology chart and a Barton standard profile morphology for comparison, a JRC value of a standard profile most similar to the actual profile according to a visual difference is the JRC value of the actual structural surface. The method is visual and visual, does not need calculation, and is widely used in field determination of the structural surface roughness coefficient. However, the geometric forms of the rock mass structural surfaces are complex and changeable, the lengths of the rock mass structural surfaces are different, and when the rock mass structural surfaces are compared with the standard section by adopting a visual comparison method, the rock mass structural surfaces are similar to a plurality of curves, and the rock mass structural surfaces are possibly dissimilar to all the standard curves. Thus, the JRC assessment score of the method often depends on the experience of the user, is difficult to accurately grasp, has great randomness, and usually causes artificial estimation errors.
To reduce subjectivity and randomness of visual comparison methods, many researchers established JRC and slope root mean square Z 2 The quantitative calculation formula is shown in table 1.
TABLE 1 JRC values and Z 2 Summarizing the calculation formulas among the two
However, the following disadvantages are also present with the above method:
1) The existing quantitative calculation formula of JRC is obtained based on a relation fitting formula between the gradient root mean square of 10 standard curves of Barton and the JRC value, and the fitting formula has only 10 data, so that the limitation of the use of the fitting formula is caused, and the situation that the JRC is smaller than 0 or the JRC value is larger than 20 can occur when the formula is adopted for calculation, as shown in tables 1-3. If the JRC is smaller than 0 and is not in line with the actual situation, if the JRC is larger than 20, the calculated shear strength of certain calculation formulas of the shear strength based on the JRC is higher, so that the engineering safety is not facilitated.
2) The JRC value calculated by any calculation formula for the same curve should have only one JRC value, or the calculation results are not much different. But the slope root mean square Z in the fitting formula of JRC value 2 Closely related to the sampling interval of the section line, if the sampling interval is different, a situation that one curve corresponds to a plurality of JRC values will often occur according to different calculation formulas, as shown in table 4.
According to the study of document 3, it is found that the root mean square Z 2 Closely related to the sampling pitch of the section line, therefore, when the JRC value of the measured curve is calculated using an empirical formula, the section line sampling pitch must be identical to the sampling pitch used when deriving the empirical formula, otherwise the error in calculating JRC may be as high as 100% (see document 4).
In addition, patent CN105678786a, patent CN105716545A, and patent CN105737768A disclose structural plane roughness coefficient evaluation methods based on Jaccard similarity measure, dice similarity measure, and Cosine similarity measure, respectively. The method mainly comprises the following steps: respectively extracting coordinates of 10 standard contour curves of Barton, calculating adjacent relief angles, respectively counting the distribution frequency of the voltage rising angles in each statistical interval, and reconstructing the relief angle feature vector of the standard contour curve; and then calculating the similarity between the fluctuation angle feature vector of the test curve and the fluctuation angle feature vector of each standard curve according to the Jaccard similarity measure, the Dice similarity measure or the sine similarity measure, and selecting the roughness coefficient of the corresponding curve when the similarity is 1 as the JRC value of the test curve.
The above method also has a series of disadvantages:
1) The similarity calculation of the method needs to count the fluctuation angle distribution interval, constructs a new fluctuation angle characteristic vector, carries out vector operation, and has complex calculation method and calculation process.
2) The structural surface roughness coefficient evaluation method for the similarity measurement of the method not only needs to ensure that the sampling interval of the test curve is the same as the curve interval of the standard curve, but also needs to ensure that the statistical interval of the voltage rising angle is the same, and has more severe requirements on calculation conditions.
3) The accuracy of the evaluation result is low.
Taking the test curve case published in the embodiment of patent CN105737768A as an example, according to the calculation method, the JRC value of the test curve is 2-4, but through visual comparison with 10 standard curves of Barton, the JRC value of the test curve is intuitively judged to belong to 18-20 according to engineering experience.
Taking the test curve case published in the embodiment of patent CN105678786a as an example, according to the calculation method, the JRC value of the test curve is 10-12, but through visual comparison with the 10 standard curves of Barton, the JRC value of the test curve should also belong to 18-20 according to engineering experience.
Taking the test curve case published in the embodiment of patent CN105716545a as an example, according to the calculation method, the JRC value of the test curve is 10-12, but through visual comparison with the 10 standard curves of Barton, the JRC value of the test curve should also belong to 18-20 according to engineering experience.
Further, in order to verify the error of the calculation result based on the similarity of the characteristic vector of the curve relief angle in the above method, further verification is performed by taking the test curve case published in the CN105737768A embodiment as an example, and the verification method is as follows: the coordinates of the test curve in CN105737768A (sampling interval dx=0.5 mm) were extracted, and the root mean square (Z) of the slope was calculated 2 ) The JRC values were calculated according to the methods of table documents 3, 4, and 5, and as shown in table 1, the calculation results showed that the JRC values of the test curves were all greater than 20. The JRC values in CN105678786a and CN105716545A were calculated according to the same method, see tables 2 and 3, and were also greater than 20. According to the 10 standard curves of Barton, the JRC value ranges from 0 to 20, and for the calculated JRC value is greater than 20, the value is 20. It can be seen that the JRC value calculated according to the methods disclosed in the above three patents and the slope root mean square Z are determined empirically 2 There is a large difference in the comparison of the calculated JRC values.
The engineering experience verification and the slope root mean square verification are combined to obtain that: the structural surface roughness coefficient evaluation method based on the curve relief angle feature vector similarity measurement in the three patent publications is inaccurate and has larger error.
Table 1 JRC value calculation of test curves in cn105737768a
Table 2 JRC value calculation of test curves in cn105678786a
Table 3 JRC value calculation of test curves in cn105716545a
TABLE 4 calculation of different JRC values for the same Curve with different sampling intervals
Note that: root mean square (Z) of standard curve 2 ) Data are derived from publicly published document 6: li Rui Shovidone rock joint JRC calculation New formula research based on Barton standard section line fine digital processing [ J ]]Rock mechanics and engineering report, 2018, 37 (S1): 3515-3522, calculation formula from document 3.
Disclosure of Invention
The purpose of the invention is that: a method for implementing JRC estimation based on curve accumulated slope similarity is provided. The method is simple and has high accuracy.
The technical scheme of the invention is as follows: a method for realizing JRC estimation based on curve accumulated slope similarity is characterized in that the accumulated slope similarity of an actual measurement curve and 10 structural surface standard contour lines of Barton is calculated, the structural surface standard contour line which is most similar to the actual measurement curve is found out, the corresponding JRC value is given to the actual measurement curve, and finally the estimation of the JRC value of the actual measurement curve is realized.
In the method for realizing JRC estimation based on curve accumulated slope similarity, the accumulated slope similarity is calculated as follows:
design (x) i ，y i )，(x i+1 ，y i+1 ) For the coordinates of two adjacent points on the standard contour line of the actual measurement curve/structural plane, the absolute value ki of the slope of the two adjacent points and the accumulated slope Sum k The calculation formula is as follows:
based on the above formula, the accumulated slope Sum of the measured curves is calculated at the same sampling interval t And the cumulative slope Sum of the standard contour lines of the structural surfaces s1 ，Sum s2 ,Sum s3 ,…,Sum s10 ；
Calculation of Sum t Respectively with Sum s1 ，Sum s2 ,Sum s3 ,…,Sum s10 The absolute value of the difference value is used for obtaining a similar distance D of the accumulated slope between the actually measured curve and the standard contour line of each structural surface; and the standard contour line of the corresponding structural surface is most similar to the actual measurement curve when the D value is minimum.
In the method for realizing JRC estimation based on curve accumulated slope similarity, the standard contour line of the structural surface adopts PHOTOSHOP and MATLAB to carry out fine digital processing of removing the impurity points and repairing the fracture before carrying out accumulated slope calculation.
In the method for realizing JRC estimation based on curve accumulated slope similarity, the sampling interval is 1mm.
In the method for realizing JRC estimation based on curve accumulated slope similarity, the actually measured curve is obtained by a shape extractor, a profiler or a scanner in a field environment.
Advantageous effects
Compared with the prior art, the method and the device have the advantages that the standard profile which is most similar to the measured profile is found out by calculating the similarity of the accumulated slopes of the measured curve and the 10 standard profiles of Barton, the estimation of the JRC value based on the similarity of the accumulated slopes of the curve is realized, and the influence of subjectivity and sampling interval of the traditional visual comparison method on a formula calculation method is avoided.
The invention adopts the slope root mean square Z 2 Compared with the calculation method of the method, the method has the following advantages:
1) The defect that the calculation result in the JRC calculation formula exceeds the JRC boundary is overcome. The JRC value estimation method based on the cumulative slope similarity provided by the invention has the calculated JRC value of between 0 and 20, and avoids the adoption of the slope root mean square Z 2 The formula computes JRC values beyond 20.
2) The condition that a plurality of JRC value calculation results appear on the same curve due to different sampling intervals is overcome. The invention is known by analysis: although the sampling interval has a larger influence on the JRC calculation result, the gradient root mean square Z is changed no matter how the sampling interval is changed 2 Are positively correlated with JRC values. Based on the method, in order to overcome the influence of the sampling interval on the JRC calculation error, the invention provides a JRC estimation method based on the curve accumulated slope similarity, and the JRC value of the estimated actual measurement curve can be obtained only by ensuring that the sampling interval of the actual measurement curve is consistent with the sampling interval of the standard curve.
In addition, compared with a calculation method based on the similarity of the relief angle feature vector, the method has the following advantages:
1) The mathematical method for calculating the similarity is adopted, and the calculation process is simple. The calculation method of the invention is to extract the coordinates of 10 standard contour curves of Barton respectively, calculate the cumulative slope of the curve, select the JRC value of the standard curve with the smallest cumulative slope difference value as the JRC value of the test curve by calculating the absolute value of the difference value between the cumulative slope of the test curve and the slope of the standard curve. According to the calculation method, the fluctuation angle distribution interval does not need to be counted, a new fluctuation angle characteristic vector does not need to be constructed, vector operation is not needed, after coordinates are obtained, corresponding results can be obtained through calculation only by means of EXCEL, and the whole calculation method and the calculation process are simple.
2) The requirement on the calculation condition is simple. The invention can obtain the corresponding estimation result only by ensuring that the sampling interval of the test curve is the same as the sampling interval of the standard curve.
3) The accuracy of the evaluation result is high. Taking the test curve case published by the CN105737768A embodiment as an example, the calculation is performed according to the method of the present invention: at a sampling interval of 0.5mm, the cumulative slope of the test curve was 63.816; at a sampling interval of 1mm, the cumulative slope of the test curve was 29.539. The JRC values of the test curve at both the 0.5mm sampling interval and the 1mm sampling interval are 18-20 as calculated by the cumulative slope with the standard curve. The specific calculation results are shown in tables 5 and 6.
TABLE 5 JRC values (sampling spacing 0.5 mm) for the test curves in patent CN105737768A were calculated by the method of the invention
TABLE 6 JRC values (sampling spacing 1 mm) for the test curves in patent CN105737768A were calculated by the method of the invention
Through comparison, the calculation result based on the cumulative slope similarity provided by the invention is more accurate than the calculation result based on the fluctuation angle feature vector similarity provided by the patent CN 105737768A.
In conclusion, the method realizes JRC value estimation based on the similarity of the curve cumulative slope, avoids randomness and subjectivity of JRC value determination caused by comparing with a standard section by adopting naked eye observation, and has simple calculation method and process and higher accuracy.
Drawings
FIG. 1 is a Barton10 structural plane standard curve and corresponding JRC values;
FIG. 2 is a cross section of a standard Barton curve obtained after refinement;
FIG. 3 is a schematic view of the in situ shear failure plane of mudstone, where (a) is τ 1-2 A picture of the shear failure surface of the test block, (b) is tau 1-3 Cutting the broken surface photo by the test block;
FIG. 4 is a graph of the profile of the extracted fracture surface, where (a) is τ 1-2 A profile curve on the fracture surface (b) is τ 1-3 Breaking the profile curve on the surface;
fig. 5 is a test curve fitted at dx=1 mm sampling intervals.
Detailed Description
The invention is further illustrated by the following figures and examples, which are not intended to be limiting.
Example 1. A method for implementing JRC estimation based on curve accumulated slope similarity, comprising the steps of:
step one: the standard section line of Barton was taken. Barton and Choubey 1997 published "The Shear Strength of Rock Joints in Theory and Practice" in the J.rock Mechanics "from which corresponding PDF versions could be downloaded. From this article, an original standard section line image (as shown in fig. 1) can be obtained.
Step two: standard section line fine digital processing. Reference 4 discloses a technique of performing fine digital processing such as removing points and repairing breaks on10 standard section lines by using photo and MATLAB graphic processing professional software to obtain 10 Barton standard section lines (see fig. 2). Coordinates of each curve were extracted in MATLAB at sampling intervals of dx=1 mm for analytical calculation.
Step three: and acquiring actual curve outline and coordinate data of the structural surface. In the field, the outline and coordinate data of the structural surface can be obtained by adopting a shape taking device, a profiler, a scanner or the like.
Step four: respectively calculating and actually measuring the curves under the same sampling intervalAbsolute values of slopes of the line and 10 standard profile curves and cumulative slope Sum k . Suppose (x) i ，y i )，(x i+1 ，y i+1 ) Is the coordinates of two adjacent points on the curve, wherein the slope (ki) and the accumulated slope (Sum) of the two adjacent points k ) The calculation formula is as follows:
step five: at the same sampling interval, the cumulative slope (Sum t ) And cumulative slope Sum of 10 marked sections s Wherein the cumulative slopes of the 10 marked sections are Sum respectively s1 ，Sum s2 ,Sum s3 ,…,Sum s10 。
Step six: the absolute value (|DeltaSum) of the difference between the cumulative slope of the test curve and the cumulative slope of the 10 marked section curves is calculated separately j I), i.e., the distance (D) between the cumulative slopes of the curves, the smaller the absolute value of the difference, the more similar the cumulative slope of the measured curve to the standard profile, indirectly the closer the roughness. The JRC value of the standard profile with the smallest absolute value can be selected as the JRC value of the measured curve.
D＝|ΔSum ki |＝|Sum kt -Sum ksi |
Example 2. Taking Barton standard section line data as an example, the cumulative slope similarity of each curve and other 9 curves is calculated respectively, the sampling interval is dx=1 mm, and the calculation result is shown in table 7.
Table 7 Barton standard section line data cumulative slope similarity distance calculation results table (dx=1 mm)
| D | JRC 0-2 | JRC 2-4 | JRC 4-6 | JRC6-8 | JRC 8-10 | JRC 10-12 | JRC 12-14 | JRC 14-16 | JRC 16-118 | JRC 18-20 |
| JRC 0-2 | 0 | 3.064482 | 4.719356 | 6.993312 | 9.720316 | 10.77992 | 11.77149 | 16.72658 | 17.48315 | 21.98502 |
| JRC 2-4 | 3.064482 | 0 | 1.654873 | 3.92883 | 6.655834 | 7.715435 | 8.707003 | 13.66209 | 14.41866 | 18.92054 |
| JRC 4-6 | 4.719356 | 1.654873 | 0 | 2.273956 | 5.000961 | 6.060561 | 7.05213 | 12.00722 | 12.76379 | 17.26566 |
| JRC6-8 | 6.993312 | 3.92883 | 2.273956 | 0 | 2.727004 | 3.786605 | 4.778173 | 9.733263 | 10.48983 | 14.99171 |
| JRC 8-10 | 9.720316 | 6.655834 | 5.000961 | 2.727004 | 0 | 1.059601 | 2.051169 | 7.006259 | 7.762829 | 12.2647 |
| JRC 10-12 | 10.77992 | 7.715435 | 6.060561 | 3.786605 | 1.059601 | 0 | 0.991568 | 5.946658 | 6.703228 | 11.2051 |
| JRC 12-14 | 11.77149 | 8.707003 | 7.05213 | 4.778173 | 2.051169 | 0.991568 | 0 | 4.95509 | 5.71166 | 10.21353 |
| JRC 14-16 | 16.72658 | 13.66209 | 12.00722 | 9.733263 | 7.006259 | 5.946658 | 4.95509 | 0 | 0.75657 | 5.258444 |
| JRC 16-118 | 17.48315 | 14.41866 | 12.76379 | 10.48983 | 7.762829 | 6.703228 | 5.71166 | 0.75657 | 0 | 4.501873 |
| JRC 18-20 | 21.98502 | 18.92054 | 17.26566 | 14.99171 | 12.2647 | 11.2051 | 10.21353 | 5.258444 | 4.501873 | 0 |
As can be seen from table 7, the similarity distance between each curve and each curve is 0, and as the JRC value increases or decreases, the similarity distance increases, which indicates that the similarity is worse, so that the accuracy and the accuracy of the method for estimating the roughness coefficient (JRC) of the structural surface based on the cumulative slope similarity are verified. The difference between the cumulative slope of each curve and the two curves adjacent to each other is the smallest, which indicates that the similarity between the two curves adjacent to each other is the best, and the estimation of the structural surface roughness coefficient JRC value can be realized based on the similarity of the cumulative slopes.
Example 3. A method for realizing JRC estimation based on curve accumulated slope similarity. Taking a set of mudstone on-site shear tests of a certain hydropower station of tansania as an example, photographs of shear failure surfaces are shown in (a) and (b) in fig. 3, and a surface profiler is used to obtain a 10cm structural surface section along the shear direction, as shown in (a) and (b) in fig. 4.
By means of tau 1-2 Profile curve (test 1) and τ on the fracture surface 1-3 The profile curve on the fracture surface (test 2) is extracted in matlab software at a sampling interval of dx=1 mm to its coordinates, and the fracture surface curve is re-fitted at a sampling interval of 1mm as shown in fig. 5.
Calculating the cumulative slope of the test1 curve as Sum according to the extracted curve coordinates t1 = 9.927526; test2 curve cumulative slope Sum t2 = 16.28571. the cumulative slope similarity distance calculation for the test1 curve, the test2 curve, and the Barton standard section line curve are shown in tables 8 and 9, respectively.
As can be seen from table 8, the test1 curve has the smallest cumulative slope similar to the 4 th Barton standard section line curve, indicating that its JRC value is closest to the JRC value of the 4 th Barton standard section, so jrc=6 to 8 for the test1 curve.
As can be seen from table 9, the test2 curve has the smallest cumulative slope similar to the 7 th Barton standard section line curve, indicating that its JRC value is closest to the JRC value of the 7 th Barton standard section, so jrc=12 to 14 for the test2 curve.
Table 8 table 1 similarity distance calculation table of curve Test1 to standard curve
Table 9 table 2 similarity distance calculation table of curve Test2 to standard curve
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (5)
1. A method for realizing JRC estimation based on curve accumulated slope similarity is characterized in that the accumulated slope similarity of an actual measurement curve and 10 structural surface standard contour lines of Barton is calculated, the structural surface standard contour line which is most similar to the actual measurement curve is found out, the corresponding JRC value is given to the actual measurement curve, and finally the estimation of the JRC value of the actual measurement curve is realized.
2. The method for implementing JRC estimation based on curve cumulative slope similarity according to claim 1, wherein the calculation process of the cumulative slope similarity is as follows:
design (x) i ，y i )，(x i+1 ，y i+1 ) Is two adjacent points on the standard contour line of the actual measurement curve/structural planeCoordinates, the absolute value ki of the slope of the adjacent two points and the cumulative slope Sum k The calculation formula is as follows:
based on the above formula, the accumulated slope Sum of the measured curves is calculated at the same sampling interval t And the cumulative slope Sum of the standard contour lines of the structural surfaces s1 ，Sum s2 ,Sum s3 ,…,Sum s10 ；
Calculation of Sum t Respectively with Sum s1 ，Sum s2 ,Sum s3 ,…,Sum s10 The absolute value of the difference value is used for obtaining a similar distance D of the accumulated slope between the actually measured curve and the standard contour line of each structural surface; and the standard contour line of the corresponding structural surface is most similar to the actual measurement curve when the D value is minimum.
3. The method for realizing JRC estimation based on curve cumulative slope similarity according to claim 1, wherein the standard contour line of the structural plane is subjected to fine digital processing of removing the impurity points and repairing the fracture by using PHOTOSHOP and MATLAB before the cumulative slope calculation is performed.
4. The method for achieving JRC estimation based on curve cumulative slope similarity according to claim 2, wherein the sampling interval is 1mm.
5. The method for implementing JRC estimation based on curve cumulative slope similarity according to claim 1, wherein the measured curve is obtained using a shape finder, a profiler or a scanner in a field environment.
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