CN107449378A - A kind of test of rock surface degree of roughness and computational methods based on 3-D view - Google Patents
A kind of test of rock surface degree of roughness and computational methods based on 3-D view Download PDFInfo
- Publication number
- CN107449378A CN107449378A CN201710602292.XA CN201710602292A CN107449378A CN 107449378 A CN107449378 A CN 107449378A CN 201710602292 A CN201710602292 A CN 201710602292A CN 107449378 A CN107449378 A CN 107449378A
- Authority
- CN
- China
- Prior art keywords
- msub
- mrow
- roughness
- tested
- scope
- 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
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
A kind of rock surface degree of roughness test of the present invention and computational methods, the present invention is on the basis of 3 d image data, evaluate skew dispersion degree of the rock surface irregular geometry for rock surface, rock surface degree of roughness is present and randomness be present in anisotropy and different directions and take into account, the description rock surface degree of roughness of 3-D quantitative, measuring and calculation method are simple and direct, practical.Rock surface degree of roughness testing procedure describes irregular fragment surface roughness test method after impact experiment, and the implementation steps that rock surface degree of roughness calculates describe the method that the three-dimensional data obtained by roughness test calculates roughness of rock surface.Fully there is the problem of randomness and take into account in the present invention, describe rock surface roughening from the angle of 3-D quantitative, survey calculation method is simple and direct, practical, strong applicability by rock surface anisotropic, and on different directions.
Description
Technical field
The invention belongs to Rock Mechanics Test field, is related to roughness of rock surface experiment test technology, particularly one kind
Based on test of the 3-D view to rock surface degree of roughness and computational methods.
Background technology
When by dead load or dynamic loading destruction often along the structural plane of weakness failure by shear occurs for rock, and
Roughness is to influence one of extremely crucial factor of shearing strength, and the roughness on joint surface is to studying ore-rock dilatancy effect
And seepage flow also has and had very important significance, at this stage International Rock mechanics can generally accepted description method be that Barton determines
The typical case of 10 kinds of JRC (rock structural face roughness value, Joint Roughness Coefficient) value from 0-20 of justice is bent
Line, JRC values are widely used in rock mechanics field, and JRC has logarithm pass with the first order derivative root mean square Z that surface profiler measures
System, but the two-dimentional roughness description being only limitted on the line of rock surface joint；What in March, 1993, Xi'an Technology University's journal was delivered
《Shape and a point dimension research are divided in ROCK MASS JOINT face》Fractal Geometry Theory is applied in the description of rough rock degree；The lunar rock of nineteen ninety-five 1
What geotechnological journey journal rock was delivered《The fractal image code at stone joint》The middle theoretical fractal model for establishing joint section cuts open to simulate joint
The roughening in face, using Koch curve simulation random joints variables, the height and length counted by high-order roughening, generate cloth
Bright curve, calculates corresponding fractal dimension D, and above-mentioned fractal dimension research can describe roughness of rock surface from three-dimensional perspective
Feature, but fail quantitative description；Rock surface degree of roughness exists and randomness on anisotropy and different directions be present, and
After rock is damaged there is stereochemical structure characteristic in surface, it is therefore desirable to carry out quantitative description its coarse journey from 3-D solid structure angle
Degree.
The content of the invention
It is an object of the invention to provide it is a kind of based on 3-D view rock surface degree of roughness test and computational methods,
This method is simple and easy to do, reliable results, and it is on the basis of 3 d image data, evaluates rock surface irregular geometry pair
In the skew dispersion degree of rock surface, rock surface degree of roughness is present in anisotropy and different directions and randomness be present
Take into account, the description rock surface degree of roughness of 3-D quantitative, measuring and calculation method is simple and direct, practical.
In order to achieve the above object, the present invention is realized using following technical scheme：
A kind of rock surface degree of roughness method of testing based on 3-D view, is followed the steps below：
1) rock sample after impact experiment destruction, test specimen volume range 10-1000cm are taken3, surface of test piece is tested
Try the areal extent 2-50cm of scope2, most long air line distance is no more than 7cm between surface of test piece is tested 2 points of scope；
2) being positioned over test specimen can contain in the container of neutral cleaners, and vessel volume scope is 250-500ml, vessel port
Areal extent is 50-80cm2, neutral cleaners are added in container to test specimen top is not crossed, cleaning agent pH range is 7-8.5,
Soak time is not less than 60s, and test specimen is cleaned with Dustproof brush or cotton pad, dry tack free is dried to after taking-up；
3) by test specimen be positioned over can left and right, fore-and-aft direction movement objective table on, surface of test piece is tested extent parallel
Fixed in objective table, and surface of test piece is tested scope and be easy to laser scanner vertical scanning upwards；
4) three-dimensional laser scanner that scanning accuracy reaches 1-10 μm of rank is chosen, scanner is placed in the vertical of objective table
Top, and vertical range is 20-30cm；Objective table point-to-point speed is adjusted, makes objective table with 0.005-0.01m/s speed translation
Until surface is tested scope topography scan and completed, obtain surface and be tested scope three-dimensional stereo model and three dimensional point cloud；
5) three-dimensional stereo model and three dimensional point cloud that surface is tested scope are handled, is converted into different chromatic values
Represent the color mode plane picture of different elevations.
A kind of rock surface degree of roughness computational methods based on 3-D view, are followed the steps below：
1) it is i to define each chromatic value in color mode plane picture, and pixel quantity corresponding to each chromatic value is Ni,
Corresponding elevation is Zi, total pixel quantity is M, statistics color mode plane picture difference chromatic value i pixel quantity NiWith
And the elevation Z of different chromatic valuesi, then total pixel quantity of image
2) pixel ratio for defining each chromatic value is Si：
3) it is V to define surface of test piece profile volume arithmetic mean differencea, surface profile volume root-mean-square deviation be Vp, by above-mentioned number
V is calculated according to below equationa、Vp, Va、VpIt can be used to state rock surface degree of roughness；
Compared with prior art, the beneficial effects of the invention are as follows：
The invention provides a kind of simple and easy to do, reliable results rock surface degree of roughness test based on 3-D view
And computational methods, by describing discrete features of the rock surface irregular geometry for reference plane, evaluation rock surface is not advised
Then solid numerical value, so as to describe the degree of roughness of rock surface；The present invention is fully by rock surface anisotropic, and not Tongfang
The problem of randomness be present upwards to take into account, describe rock surface roughening from the angle of 3-D quantitative, managed relative to a point shape
By more directly perceived, survey calculation method is simple and direct, practical, strong applicability.
Brief description of the drawings
Fig. 1 is the testing procedure figure of the present invention.
Fig. 2 is the calculation procedure figure of the present invention.
Embodiment
The embodiment of the present invention is described further below in conjunction with the accompanying drawings：
As shown in figure 1, a kind of rock surface degree of roughness method of testing based on 3-D view, enters according to following steps
OK：
1) rock sample after impact experiment destruction, test specimen volume range 10-1000cm are taken3, surface of test piece is tested
Try the areal extent 2-50cm of scope2, most long air line distance is no more than 7cm between surface of test piece is tested 2 points of scope.
2) being positioned over test specimen can contain in the container of neutral cleaners, and vessel volume scope is 250-500ml, vessel port
Areal extent is 50-80cm2, neutral cleaners are added in container to test specimen top is not crossed, cleaning agent pH range is 7-8.5,
Soak time is not less than 60s, and test specimen is cleaned with Dustproof brush or cotton pad, dry tack free is dried to air duct after taking-up.
3) by test specimen be positioned over can left and right, fore-and-aft direction movement objective table on, surface of test piece is tested extent parallel
Fixed in objective table, and surface of test piece is tested scope and be easy to laser scanner vertical scanning upwards.
Test specimen propeller is housed on objective table, has propeller left regulation wheel under objective table, objective table or so, fore-and-aft direction can be made
Movement, according to test specimen volume choose can the spring clips of clamping test pieces both sides test specimen is fixed.
4) three-dimensional laser scanner that scanning accuracy reaches 1-10 μm of rank is chosen, scanner is placed in the vertical of objective table
Top, and vertical range is 20-30cm；Objective table point-to-point speed is adjusted, makes objective table with 0.005-0.01m/s speed translation
Until surface is tested scope topography scan and completed, obtain surface and be tested scope three-dimensional stereo model and three dimensional point cloud.
Scanner can be fixed on the tripod of regulating height, and scanner height is highly adjusted by adjusting tripod
Degree.
5) three-dimensional stereo model and three dimensional point cloud that surface is tested scope are handled, is converted into different chromatic values
Represent the color mode plane picture of different elevations.
As shown in Fig. 2 a kind of rock surface degree of roughness method of testing based on 3-D view, enters according to following steps
OK：
1) it is i to define each chromatic value in color mode plane picture, and pixel quantity corresponding to each chromatic value is Ni,
Corresponding elevation is Zi, total pixel quantity is M, statistics color mode plane picture difference chromatic value i pixel quantity NiWith
And the elevation Z of different chromatic valuesi, then total pixel quantity of imageDifferent elevation ZiCorresponding different pixels points
Measure NiAnd total pixel quantity M is shown in Table 1：
Table 1
| Elevation Zi | Pixel quantity Ni |
| Z1 | N1 |
| Z2 | N2 |
| Z3 | N3 |
| …… | …… |
| Zn | Nn |
| It is total | M |
2) pixel ratio for defining each chromatic value is Si：
Then pixel ratio corresponding to different elevations is shown in Table 2：
Table 2
| Elevation Zi | Pixel ratio Si |
| Z1 | S1 |
| Z2 | S2 |
| Z3 | S3 |
| Z4 | S4 |
| Z5 | S5 |
| …… | …… |
| Zn | Sn |
| It is total | 1 |
3) it is V to define surface of test piece profile volume arithmetic mean differencea, surface profile volume root-mean-square deviation be Vp, by above-mentioned number
V is calculated according to below equationa、Vp：
In formula, Va、VpIt can be used to state rock surface degree of roughness.
Embodiment 1：
Choose amphibolite rock sample after dynamic impulsion depression bar is tested, test specimen volume 400cm3, surface is tested scope
Area is 10.5cm2；Most long air line distance is 4cm between surface of test piece is tested 2 points of scope；
Test specimen is positioned in beaker, beaker volume is 500ml, and beaker aperture area is 80cm2, add in beaker neutral
For cleaning agent to test specimen top is not crossed, cleaning agent pH value is 7.5, after soaking 60s, test specimen is cleaned with cotton pad, air duct is used after taking-up
It is dried to dry tack free；
Test specimen is positioned over objective table, clamping test specimen both sides using the American spring clip of F types is fixed, and is tested surface
Scope is easy to laser scanner vertical scanning upwards and parallel to objective table；
3D three-dimensional laser scanners (HL-3DM) are chosen, scanner is fixed on the tripod of regulating height, are adjusted
Tripod highly makes scanner perpendicular to objective table and vertical range be 20cm；Adjust objective table point-to-point speed, make objective table with
For 0.01m/s speed translation until surface is tested scope topography scan and completed, acquisition surface is tested scope 3 D stereo mould
Type and three dimensional point cloud；
The three-dimensional stereo model and three dimensional point cloud of scope are tested using Geomagic software processings surface, by its turn
Change the color mode plane picture that different chromatic values represent different elevations into；
ImageMagick software processings are used to the above-mentioned image of institute, according to software computational accuracy, elevation is taken by 10 μm of spans
Value, exports different chromatic value pixel quantities, counts its different chromatic value i pixel quantity Ni, different chromatic values elevation Zi
And total pixel quantity M is shown in Table 3：
Table 3
| Elevation Zi | Pixel quantity Ni |
| 345μm | 314 |
| 335μm | 463 |
| 325μm | 326 |
| 315μm | 289 |
| 305μm | 312 |
| 295μm | 431 |
| 285μm | 806 |
| 275μm | 1657 |
| 265μm | 2675 |
| 255μm | 3497 |
| 245μm | 3568 |
| …… | …… |
| 5μm | 2864 |
| It is total | 147971 |
Calculate pixel ratio S corresponding to different chromatic valuesiIt is shown in Table 4：
Table 4
Bring upper step data into formula
Calculation testing piece surface is tested the surface profile volume root-mean-square deviation V of scopep=70.192 μm, the surface of test piece quilt
The roughness value of test scope is 70.192 μm.
Embodiment 2：
Choose amphibolite rock sample after dynamic impulsion depression bar is tested, test specimen volume 500cm3, surface is tested scope
Area is 13cm2；Most long air line distance is 4.5cm between surface of test piece is tested 2 points of scope；
Test specimen is positioned in beaker, beaker volume is 500ml, and beaker aperture area is 80cm2, add in beaker neutral
For cleaning agent to test specimen top is not crossed, cleaning agent pH value is 8, after soaking 65s, test specimen is cleaned with cotton pad, dried after taking-up with air duct
To dry tack free；
Test specimen is positioned over objective table, clamping test specimen both sides using the American spring clip of F types is fixed, and is tested surface
Scope is easy to laser scanner vertical scanning upwards and parallel to objective table；
3D three-dimensional laser scanners (HL-3DM) are chosen, scanner is fixed on the tripod of regulating height, are adjusted
Tripod highly makes scanner perpendicular to objective table and vertical range be 20cm；Adjust objective table point-to-point speed, make objective table with
For 0.01m/s speed translation until surface is tested scope topography scan and completed, acquisition surface is tested scope 3 D stereo mould
Type and three dimensional point cloud；
The three-dimensional stereo model and three dimensional point cloud of scope are tested using Geomagic software processings surface, by its turn
Change the color mode plane picture that different chromatic values represent different elevations into；
ImageMagick software processings are used to the above-mentioned image of institute, according to software computational accuracy, elevation is taken by 10 μm of spans
Value, exports different chromatic value pixel quantities, counts its different chromatic value i pixel quantity Ni, different chromatic values elevation Zi
And total pixel quantity M is shown in Table 5：
Table 5
Calculate pixel ratio S corresponding to different chromatic valuesiIt is shown in Table 6：
Table 6
| Elevation Zi | Pixel ratio Si |
| 340μm | 0.001306 |
| 330μm | 0.000843 |
| 320μm | 0.001907 |
| 310μm | 0.010763 |
| 300μm | 0.007042 |
| 290μm | 0.001909 |
| 280μm | 0.000886 |
| 270μm | 0.000819 |
| 260μm | 0.000356 |
| 250μm | 0.000341 |
| …… | …… |
| 10μm | 0.000961 |
| It is total | 1 |
Bring upper step data into formula
Calculation testing piece surface is tested the surface profile volume root-mean-square deviation V of scopep=68.21 μm, the surface of test piece quilt
The roughness value of test scope is 68.21 μm.
Embodiment 3：
Choose amphibolite rock sample after dynamic impulsion depression bar is tested, test specimen volume 600cm3, surface is tested scope
Area is 16cm2；Most long air line distance is 6cm between surface of test piece is tested 2 points of scope；
Test specimen is positioned in beaker, beaker volume is 500ml, and beaker aperture area is 80cm2, add in beaker neutral
For cleaning agent to test specimen top is not crossed, cleaning agent pH value is 7.5, after soaking 65s, test specimen is cleaned with cotton pad, air duct is used after taking-up
It is dried to dry tack free；
Test specimen is positioned over objective table, clamping test specimen both sides using the American spring clip of F types is fixed, and is tested surface
Scope is easy to laser scanner vertical scanning upwards and parallel to objective table；
3D three-dimensional laser scanners (HL-3DM) are chosen, scanner is fixed on the tripod of regulating height, are adjusted
Tripod highly makes scanner perpendicular to objective table and vertical range be 20cm；Adjust objective table point-to-point speed, make objective table with
For 0.01m/s speed translation until surface is tested scope topography scan and completed, acquisition surface is tested scope 3 D stereo mould
Type and three dimensional point cloud；
The three-dimensional stereo model and three dimensional point cloud of scope are tested using Geomagic software processings surface, by its turn
Change the color mode plane picture that different chromatic values represent different elevations into；
ImageMagick software processings are used to the above-mentioned image of institute, according to software computational accuracy, elevation is taken by 10 μm of spans
Value, exports different chromatic value pixel quantities, counts its different chromatic value i pixel quantity Ni, different chromatic values elevation Zi
And total pixel quantity M is shown in Table 7：
Table 7
| Elevation Zi | Pixel quantity Ni |
| 560μm | 304 |
| 550μm | 900 |
| 540μm | 1346 |
| 530μm | 2164 |
| 520μm | 1333 |
| 510μm | 987 |
| 500μm | 614 |
| 490μm | 1645 |
| 480μm | 2648 |
| 470μm | 4687 |
| 460μm | 5597 |
| …… | …… |
| 10μm | 132 |
| It is total | 74684 |
Calculate pixel ratio S corresponding to different chromatic valuesiIt is shown in Table 8：
Table 8
Bring upper step data into formula
Calculation testing piece surface is tested the surface profile volume root-mean-square deviation V of scopep=99.87 μm, the surface of test piece quilt
The roughness value of test scope is 99.87 μm.
Embodiment 4：
Choose amphibolite rock sample after dynamic impulsion depression bar is tested, test specimen volume 250cm3, surface is tested scope
Area is 10cm2；Most long air line distance is 3.5cm between surface of test piece is tested 2 points of scope；
Test specimen is positioned in beaker, beaker volume is 500ml, and beaker aperture area is 80cm2, add in beaker neutral
For cleaning agent to test specimen top is not crossed, cleaning agent pH value is 8, after soaking 75s, test specimen is cleaned with cotton pad, dried after taking-up with air duct
To dry tack free；
Test specimen is positioned over objective table, clamping test specimen both sides using the American spring clip of F types is fixed, and is tested surface
Scope is easy to laser scanner vertical scanning upwards and parallel to objective table；
3D three-dimensional laser scanners (HL-3DM) are chosen, scanner is fixed on the tripod of regulating height, are adjusted
Tripod highly makes scanner perpendicular to objective table and vertical range be 20cm；Adjust objective table point-to-point speed, make objective table with
For 0.01m/s speed translation until surface is tested scope topography scan and completed, acquisition surface is tested scope 3 D stereo mould
Type and three dimensional point cloud；
The three-dimensional stereo model and three dimensional point cloud of scope are tested using Geomagic software processings surface, by its turn
Change the color mode plane picture that different chromatic values represent different elevations into；
ImageMagick software processings are used to the above-mentioned image of institute, according to software computational accuracy, elevation is taken by 10 μm of spans
Value, exports different chromatic value pixel quantities, counts its different chromatic value i pixel quantity Ni, different chromatic values elevation Zi
And total pixel quantity M is shown in Table 9：
Table 9
Calculate pixel ratio S corresponding to different chromatic valuesiIt is shown in Table 10 as follows：
Table 10
| Elevation Zi | Pixel ratio Si |
| 260μm | 0.000933 |
| 250μm | 0.010916 |
| 240μm | 0.020682 |
| 230μm | 0.042421 |
| 220μm | 0.02967 |
| 210μm | 0.030603 |
| 200μm | 0.019096 |
| 190μm | 0.050165 |
| 180μm | 0.082913 |
| 170μm | 0.072184 |
| …… | …… |
| 10μm | 0.000404 |
| It is total | 1 |
Bring upper step data into formula
Calculation testing piece surface is tested the surface profile volume root-mean-square deviation V of scopep=32.68 μm, the surface of test piece quilt
The roughness value of test scope is 32.68 μm.
Claims (2)
1. a kind of rock surface degree of roughness method of testing based on 3-D view, it is characterised in that follow the steps below：
1) rock sample after impact experiment destruction, test specimen volume range 1-1000cm are taken3, surface of test piece is tested scope
Areal extent 2-50cm2, most long air line distance is no more than 7cm between surface of test piece is tested 2 points of scope；
2) being positioned over test specimen can contain in the container of neutral cleaners, and vessel volume scope is 250-500ml, container opening area
Scope is 50-80cm2, neutral cleaners are added in container to test specimen top is not crossed, cleaning agent pH range be 7-8.5, is soaked
Time is not less than 60s, and test specimen is cleaned with Dustproof brush or cotton pad, dry tack free is dried to after taking-up；
3) by test specimen be positioned over can left and right, fore-and-aft direction movement objective table on, surface of test piece is tested extent parallel in load
Thing platform is fixed, and surface of test piece is tested scope and be easy to laser scanner vertical scanning upwards；
4) choose scanning accuracy and reach the three-dimensional laser scanner of 1-10 μm of rank, by scanner be placed in objective table it is vertical on
Side, and vertical range is 20-30cm；Objective table point-to-point speed is adjusted, makes objective table straight with 0.005-0.01m/s speed translation
Scope topography scan is tested to surface to complete, and is obtained surface and is tested scope three-dimensional stereo model and three dimensional point cloud；
5) three-dimensional stereo model and three dimensional point cloud that surface is tested scope are handled, different chromatic values is converted into and represents
The color mode plane picture of different elevations.
2. a kind of rock surface degree of roughness computational methods based on 3-D view, it is characterised in that follow the steps below：
1) it is i to define each chromatic value in color mode plane picture, and pixel quantity corresponding to each chromatic value is Ni, it is corresponding
Elevation be Zi, total pixel quantity is M, statistics color mode plane picture difference chromatic value i pixel quantity NiAnd not
With the elevation Z of chromatic valuei, then total pixel quantity of image
2) pixel ratio for defining each chromatic value is Si：
<mrow>
<msub>
<mi>S</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>N</mi>
<mi>i</mi>
</msub>
<mi>M</mi>
</mfrac>
<mo>;</mo>
</mrow>
3) it is V to define surface of test piece profile volume arithmetic mean differencea, surface profile volume root-mean-square deviation be Vp, above-mentioned data are transported
V is calculated with below equationa、Vp, Va、VpIt can be used to state rock surface degree of roughness；
<mrow>
<msub>
<mi>V</mi>
<mi>a</mi>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>Z</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<msub>
<mi>S</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>V</mi>
<mi>p</mi>
</msub>
<mo>=</mo>
<msqrt>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>Z</mi>
<mi>i</mi>
</msub>
<mo>|</mo>
<msub>
<mi>S</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
1
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710602292.XA CN107449378B (en) | 2017-07-21 | 2017-07-21 | A kind of test of rock surface degree of roughness and calculation method based on 3-D image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710602292.XA CN107449378B (en) | 2017-07-21 | 2017-07-21 | A kind of test of rock surface degree of roughness and calculation method based on 3-D image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107449378A true CN107449378A (en) | 2017-12-08 |
| CN107449378B CN107449378B (en) | 2019-08-20 |
Family
ID=60487297
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710602292.XA Active CN107449378B (en) | 2017-07-21 | 2017-07-21 | A kind of test of rock surface degree of roughness and calculation method based on 3-D image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107449378B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108073774A (en) * | 2017-12-29 | 2018-05-25 | 辽宁科技大学 | A kind of reliable method for verifying quick-fried heap LUMPINESS DISTRIBUTION |
| CN108304629A (en) * | 2018-01-19 | 2018-07-20 | 石家庄铁道大学 | A kind of engineering structure surface of base roughness confining method |
| CN108895992A (en) * | 2018-09-03 | 2018-11-27 | 大连理工大学 | A kind of laser scanning device and application method for distress in concrete fracture surface roughness |
| CN108896004A (en) * | 2018-08-01 | 2018-11-27 | 刘敬寿 | A kind of fracture surface roughness anisotropy characterizing method |
| CN109612412A (en) * | 2018-11-28 | 2019-04-12 | 同济大学 | A kind of precast concrete faying face roughness calculation method and evaluation system |
| CN109859301A (en) * | 2019-03-04 | 2019-06-07 | 浙江大学 | A kind of rock structural face roughness value fining characterizing method |
| CN110057325A (en) * | 2019-04-26 | 2019-07-26 | 湖南大学 | A kind of Surface Roughness Detecting Method and calculating equipment based on imaging simulation |
| CN111750808A (en) * | 2020-06-28 | 2020-10-09 | 电子科技大学 | Surface roughness obtaining method based on laser radar scanner |
| CN112050756A (en) * | 2020-09-04 | 2020-12-08 | 南通大学 | Rock ore slice and resin target surface flatness recognition processing method |
| CN114544487A (en) * | 2022-01-11 | 2022-05-27 | 西安理工大学 | Method for testing bonding performance of asphalt and aggregate interface transition region in core wall dam |
| CN115290010A (en) * | 2022-04-13 | 2022-11-04 | 同济大学 | Concrete joint surface roughness detection method and equipment |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100442071B1 (en) * | 1999-10-26 | 2004-07-30 | 가부시키가이샤 히타치세이사쿠쇼 | Nondestructive inspection method and an apparatus thereof |
| CN1737494A (en) * | 2004-08-19 | 2006-02-22 | 财团法人工业技术研究院 | Surface profile analytical method for object needing measure |
| CN103810706A (en) * | 2014-01-27 | 2014-05-21 | 鲁东大学 | Inverted stereo correction method of remote sensing image based on surface roughness participated shadow model |
| CN104778755A (en) * | 2015-03-27 | 2015-07-15 | 浙江理工大学 | Region-division-based three-dimensional reconstruction method for texture image |
| CN105302961A (en) * | 2015-10-29 | 2016-02-03 | 江苏阳明船舶装备制造技术有限公司 | Three-dimensional photography technology based folded pipe field measurement method |
| CN105488836A (en) * | 2015-11-16 | 2016-04-13 | 武汉海达数云技术有限公司 | Circular colored tape point cloud rendering method based on elevation distribution characteristics |
| CN105841641A (en) * | 2016-06-07 | 2016-08-10 | 东莞市三瑞自动化科技有限公司 | Laser triangulation method-based three-dimensional measuring instrument and flatness detection method |
| CN106227923A (en) * | 2016-07-14 | 2016-12-14 | 中国地质大学（武汉） | A kind of rock mass discontinuity three-dimensional roughness evaluation methodology |
| CN106482674A (en) * | 2016-11-14 | 2017-03-08 | 绍兴文理学院 | The approximate expression method of the structural plane roughness dimensional effect based on middle intelligence number function |
| CN106846498A (en) * | 2017-02-08 | 2017-06-13 | 武汉海达数云技术有限公司 | Laser point cloud rendering intent and device |
-
2017
- 2017-07-21 CN CN201710602292.XA patent/CN107449378B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100442071B1 (en) * | 1999-10-26 | 2004-07-30 | 가부시키가이샤 히타치세이사쿠쇼 | Nondestructive inspection method and an apparatus thereof |
| CN1737494A (en) * | 2004-08-19 | 2006-02-22 | 财团法人工业技术研究院 | Surface profile analytical method for object needing measure |
| CN103810706A (en) * | 2014-01-27 | 2014-05-21 | 鲁东大学 | Inverted stereo correction method of remote sensing image based on surface roughness participated shadow model |
| CN104778755A (en) * | 2015-03-27 | 2015-07-15 | 浙江理工大学 | Region-division-based three-dimensional reconstruction method for texture image |
| CN105302961A (en) * | 2015-10-29 | 2016-02-03 | 江苏阳明船舶装备制造技术有限公司 | Three-dimensional photography technology based folded pipe field measurement method |
| CN105488836A (en) * | 2015-11-16 | 2016-04-13 | 武汉海达数云技术有限公司 | Circular colored tape point cloud rendering method based on elevation distribution characteristics |
| CN105841641A (en) * | 2016-06-07 | 2016-08-10 | 东莞市三瑞自动化科技有限公司 | Laser triangulation method-based three-dimensional measuring instrument and flatness detection method |
| CN106227923A (en) * | 2016-07-14 | 2016-12-14 | 中国地质大学（武汉） | A kind of rock mass discontinuity three-dimensional roughness evaluation methodology |
| CN106482674A (en) * | 2016-11-14 | 2017-03-08 | 绍兴文理学院 | The approximate expression method of the structural plane roughness dimensional effect based on middle intelligence number function |
| CN106846498A (en) * | 2017-02-08 | 2017-06-13 | 武汉海达数云技术有限公司 | Laser point cloud rendering intent and device |
Non-Patent Citations (1)
| Title |
|---|
| 李伯奎等: ""三维粗糙度参数算术平均偏差与均方根偏差的规律研究"", 《工具技术》 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108073774A (en) * | 2017-12-29 | 2018-05-25 | 辽宁科技大学 | A kind of reliable method for verifying quick-fried heap LUMPINESS DISTRIBUTION |
| CN108073774B (en) * | 2017-12-29 | 2021-05-14 | 辽宁科技大学 | Reliable method for verifying explosive pile block size distribution |
| CN108304629A (en) * | 2018-01-19 | 2018-07-20 | 石家庄铁道大学 | A kind of engineering structure surface of base roughness confining method |
| CN108896004A (en) * | 2018-08-01 | 2018-11-27 | 刘敬寿 | A kind of fracture surface roughness anisotropy characterizing method |
| CN108896004B (en) * | 2018-08-01 | 2020-03-20 | 中国石油大学(华东) | Crack surface roughness anisotropy characterization method |
| CN108895992A (en) * | 2018-09-03 | 2018-11-27 | 大连理工大学 | A kind of laser scanning device and application method for distress in concrete fracture surface roughness |
| CN109612412B (en) * | 2018-11-28 | 2021-02-02 | 同济大学 | Method for calculating roughness of joint surface of precast concrete member and evaluation system |
| CN109612412A (en) * | 2018-11-28 | 2019-04-12 | 同济大学 | A kind of precast concrete faying face roughness calculation method and evaluation system |
| CN109859301A (en) * | 2019-03-04 | 2019-06-07 | 浙江大学 | A kind of rock structural face roughness value fining characterizing method |
| CN110057325A (en) * | 2019-04-26 | 2019-07-26 | 湖南大学 | A kind of Surface Roughness Detecting Method and calculating equipment based on imaging simulation |
| CN111750808A (en) * | 2020-06-28 | 2020-10-09 | 电子科技大学 | Surface roughness obtaining method based on laser radar scanner |
| CN111750808B (en) * | 2020-06-28 | 2021-09-14 | 电子科技大学 | Surface roughness obtaining method based on laser radar scanner |
| CN112050756A (en) * | 2020-09-04 | 2020-12-08 | 南通大学 | Rock ore slice and resin target surface flatness recognition processing method |
| CN112050756B (en) * | 2020-09-04 | 2022-05-06 | 南通大学 | Rock ore slice and resin target surface flatness recognition processing method |
| CN114544487A (en) * | 2022-01-11 | 2022-05-27 | 西安理工大学 | Method for testing bonding performance of asphalt and aggregate interface transition region in core wall dam |
| CN114544487B (en) * | 2022-01-11 | 2023-10-27 | 西安理工大学 | Method for testing adhesion performance of asphalt and aggregate interface transition area in core wall dam |
| CN115290010A (en) * | 2022-04-13 | 2022-11-04 | 同济大学 | Concrete joint surface roughness detection method and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107449378B (en) | 2019-08-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107449378A (en) | A kind of test of rock surface degree of roughness and computational methods based on 3-D view | |
| CN106529038B (en) | A method of it is bolted from micro--grand yardstick model identification in conjunction with the tangential damping characteristic in portion | |
| CN105571511B (en) | A kind of ship plank formed precision online test method | |
| CN110702536B (en) | Rock mass structural plane shear failure surface morphology evolution law research method and system | |
| CN107656902B (en) | Structural surface roughness coefficient statistical method under different sampling intervals | |
| CN106482674B (en) | The approximate expression method of structural plane roughness dimensional effect based on middle intelligence number function | |
| CN107423462A (en) | Workpiece considers the Prediction method for fatigue life and system of three-dimensional rough surface morphology | |
| Xavier et al. | Novel experimental approach for longitudinal-radial stiffness characterisation of clear wood by a single test | |
| CN105139441A (en) | Fractal dimension obtaining method of coating surface morphology | |
| CN113466066A (en) | DIC technology-based method for measuring fatigue deformation and crack width of concrete material | |
| CN104296680A (en) | Particle-reinforced titanium-based composite material grinding surface quality evaluation method | |
| CN107036561B (en) | The anisotropic approximate expression method of structural plane roughness based on middle intelligence number function | |
| EP2090886A3 (en) | Method for optimising the voltage distribution in acoustic thermography applications | |
| WO2019136870A1 (en) | Calculation method employing parallel light to evaluate degree of fluctuation in structural surface of rock mass | |
| CN108595794A (en) | A kind of pipeline structure oscillating load analysis method | |
| CN109615594B (en) | Laser point cloud cavity repairing and coloring method | |
| CN107966245A (en) | A kind of crankshaft dynamic balance computational methods | |
| CN109115127B (en) | Sub-pixel peak point extraction algorithm based on Bezier curve | |
| Kornev et al. | Quasi-brittle fracture diagram of structured bodies in the presence of edge cracks | |
| CN105912741A (en) | Method for evaluating fatigue limit and device for evaluating fatigue limit | |
| CN109632487A (en) | A kind of qualitative test method of interior rock internal strain field under load effect | |
| CN105571752B (en) | Ultrasonic wave stress method for quantitative measuring in a kind of experiment by photoelastic method | |
| CN110728027A (en) | Method for evaluating anisotropy rate of roughness coefficient of rock mass structural plane | |
| Liu et al. | Sub-pixel center extraction method for line structured light stripe | |
| CN104616271B (en) | A kind of displacement field adaptive smooth method related suitable for digital picture |
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 |