CN106872472A - Surface Quality of Concrete method of determination and evaluation - Google Patents
Surface Quality of Concrete method of determination and evaluation Download PDFInfo
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- CN106872472A CN106872472A CN201710036091.8A CN201710036091A CN106872472A CN 106872472 A CN106872472 A CN 106872472A CN 201710036091 A CN201710036091 A CN 201710036091A CN 106872472 A CN106872472 A CN 106872472A
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- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000011156 evaluation Methods 0.000 title claims abstract description 19
- 230000007547 defect Effects 0.000 claims abstract description 46
- 238000001514 detection method Methods 0.000 claims abstract description 34
- 239000000945 filler Substances 0.000 claims abstract description 24
- 238000006243 chemical reaction Methods 0.000 claims abstract description 20
- 238000006467 substitution reaction Methods 0.000 claims abstract description 5
- 239000004568 cement Substances 0.000 claims description 10
- 239000011521 glass Substances 0.000 claims description 10
- 238000007667 floating Methods 0.000 claims description 7
- 238000012856 packing Methods 0.000 claims description 4
- 239000004576 sand Substances 0.000 claims description 3
- 238000007619 statistical method Methods 0.000 claims description 3
- 239000000084 colloidal system Substances 0.000 claims description 2
- 239000002245 particle Substances 0.000 claims description 2
- 238000012545 processing Methods 0.000 abstract description 4
- 238000012360 testing method Methods 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000007689 inspection Methods 0.000 description 3
- 230000015271 coagulation Effects 0.000 description 2
- 238000005345 coagulation Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 239000004035 construction material Substances 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000010422 painting Methods 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
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- Health & Medical Sciences (AREA)
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- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
A kind of Surface Quality of Concrete method of determination and evaluation, comprises the following steps：1) it is S to choose area0Detection sample, shoot obtain surface picture；2) binary conversion treatment is carried out to surface picture；3) surface picture after binary conversion treatment is analyzed, obtains the percentage A shared by defect part pixel；4) the defect area S of detection sample is calculated；5) filler is smeared in detection sample surface, front volume V is smeared according to filler0With volume V after smearing1Change, equivalent substitution detects the defect volume V of sample；6) the defect mean depth H, defect mean depth H=V/S of detection sample are calculated；7) according to defect mean depth H overall merit concrete surface presentation qualities.The present invention carries out quantitative measurment using image binaryzation processing and isometric method of substitution to concrete appearance defect, and human factor can be avoided to influence, and the Evaluation on Appearance Quality science to concrete is objective, and the method is efficiently convenient, can greatly save cost of labor.
Description
Technical field
The present invention relates to the concrete commonly used in architectural engineering, commented in particular to a kind of detection of Surface Quality of Concrete
Valency method.
Background technology
Concrete is the maximum construction material of usage amount, and particularly important effect is played in construction project.With coagulation
The high performance of soil, the presentation quality of concrete is also increasingly taken seriously.Existing GB GB50204-2015《Concrete structure
Engineering construction quality acceptance specification》In the presentation quality of concrete is specified below：The outward appearance of dominant item pouring structure
Structure should not have major defect, to the major defect for having occurred, should propose treatment scheme by unit in charge of construction, and through management
Processed after the accreditation of (construction) unit；To treated position, examination should be reexamined ....The method of inspection：Observation, inspection
Look into treatment scheme ... ".
According to current specifications and code, detection and the evaluation of Surface Quality of Concrete are typically by testing staff's Visual Observations Observations
Concrete aberration, measure Air Bubble Size and penetration of fracture etc. with graduated scale.The method concrete structure general inspection and comment
Fixed aspect serves important function, but the method is based on the testing result of artificial vision, heavy dependence testing staff individual's
Standard and experience, cause evaluation result to lack objectivity, and be difficult to the degradation of accurate quantification constructional appearance quality.In addition,
In view of concrete works has a large capacity and a wide range, wasted time and energy using manual detection method, testing cost is high, while being received in detection process
Environment limitation is big, and the safety requirements to testing staff is very high.
In order to solve the above problems, those skilled in the art theoretically and in putting into practice are studying and how effectively to comment always
Sentence the presentation quality of concrete, but not yet obtain satisfied evaluation method up to now.
The content of the invention
Present invention aim to overcome the defect existing for above-mentioned prior art, there is provided a kind of efficient, objective, operation
Easy Surface Quality of Concrete method of determination and evaluation.
To achieve the above object, the Surface Quality of Concrete method of determination and evaluation designed by the present invention, comprises the following steps：
1) it is S that one piece of area is chosen on concrete surface to be evaluated0Detection sample, under gentle natural light environment,
Shoot the surface picture for obtaining detection sample；
2) binary conversion treatment is carried out to gained surface picture using binary conversion treatment software, wherein defect part pixel
Gray value is set to 0 or 255；
3) statistical analysis is carried out to the surface picture after binary conversion treatment, it is total that acquisition defect part pixel accounts for surface picture
The percentage A of pixel；
4) the defect area S of detection sample, defect area S and detection sample area S are calculated0Between meet following mathematics
Relation：S=S0×A；
5) filler is smeared in detection sample surface, and its is floating, front volume V is then smeared according to filler0With painting
Smear rear volume V1Change, equivalent substitution detects the defect volume V, defect volume V=V of sample0- V1；
6) the defect mean depth H of detection sample is calculated, defect mean depth H=V/S, the wherein unit of V are cm3, S
Unit be cm2, the unit of H is cm；
7) according to gained defect area S and defect mean depth H overall merit concrete surface presentation qualities.
Further, in order that detecting rejected region and flattened region significant difference in sample, it is to avoid image procossing occurs
Error, the step 1) in, nature light direction and detection sample surface are selected during shooting in 30~60 ° of angle, preferably
Angle is 35~45 °.
Further, the important step that suitable gray threshold is image binaryzation is chosen, too high gray threshold can make
Some true edges are lost, and too low gray threshold can produce some meaningless false edges again, influence the segmentation of image accurate
Degree, therefore, the step 2) in the gray threshold of binary conversion treatment be adjusted according to the brightness of surface picture, or according to multiple
The result of manual value is selected, and preferred binary conversion treatment gray threshold is 60~80.
Further, the step 2) in, binary conversion treatment software uses Matlab softwares or Photoshop softwares.
Further, its packing ratio is tightr with uniform fine sand for level, and compactibility is small, and the effect of smaller external force is piled up to it
State influence is little, can be filled into the defect of concrete surface naturally, it is adaptable to which surface is in the concrete of horizontality
Component, the compressibility of glass cement is also smaller, with certain viscosity, it is adaptable to which surface is in the concrete structure of vertical state
Part, therefore, the step 5) in, filler matches somebody with somebody uniform fine sand or glass cement using level.
Further, in order to ensure that filler being capable of filling defect position, the step 5 naturally) in, using soft use
Power mode is floating by filler, it is floating during to keep filling agent particle or colloid be in natural packing state.
Further, because the volume before and after filler filling is difficult direct measurement, and its quality can be by simple weighing
Obtain, therefore, by step 5) in filler filling before and after Volume Changes be converted into its mass change, the step 5) in, fill out
Fill agent and smear front volume V0=m0/ ρ, volume V after filler smearing1=m1/ρ；Wherein：m0Quality before being smeared for filler, m1For
Quality, m after filler smearing0And m1Unit be g；ρ is filler bulk density, and the unit of ρ is g/cm3；V0And V1Unit
It is cm3。
The principle of image binaryzation processing is：The gray value of the pixel on image is set to 0 or 255, also
It is that whole image is showed into obvious black and white effect, its method is one threshold value T of the overall situation of setting, with T by the data of image
It is divided into two parts：Pixel group more than T and the pixel group less than T.Will be greater than the pixel group of T pixel value be set as white (or
Person's black), the pixel value of the pixel group less than T is set as black (or white).At the binaryzation of image of the present invention
Reason, the depth disparity of rejected region and other positions is exactly converted to the difference of gray scale by light and shadow imaging, then using threshold
Value selecting technology splits the image, and the ratio shared by different gray-scale pixels can be calculated by gray-scale statistical.
The invention has the advantages that：
1st, the present invention is quantified using image binaryzation processing and isometric method of substitution to concrete appearance defect
Measurement, and evaluation index of the average defect depth H as concrete appearance defect is proposed, the influence of human factor can be avoided, it is right
The presentation quality of concrete carries out quantitative and science objective appraisal, and the method is efficiently convenient, in can greatling save engineering
Cost of labor.
2nd, the present invention on the basis of concrete surface crack, bubble, voids and pits, hole etc. is considered comprehensively to concrete
Presentation quality carry out overall merit, it is to avoid the one-sidedness evaluated Surface Quality of Concrete in the prior art, and the present invention
Binaryzation gray threshold can be set automatically, eliminate and need to delineate flattened region in conventional images treatment technology, deduct
Human factor influences larger processing procedure, also greatly simplify process step.
3rd, IMAQ of the present invention is carried out under being 30~60 ° in natural light direction and the angle of detection sample surface, makes to lack
Fall into and flattened region significant difference, it is to avoid the error that image procossing occurs.
Brief description of the drawings
Fig. 1 is the surface picture that concrete surface of the present invention detects sample；
Fig. 2 is the surface picture of the concrete surface detection sample after binary conversion treatment of the present invention.
Specific embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.
Fig. 1 is the surface picture that concrete surface of the present invention detects sample, and the acquisition of the photo is first in coagulation to be evaluated
Area S is chosen on native surface0The detection sample of=50cm × 50cm, is in then 30 ° in natural light direction and detection sample surface
Angle under shoot gained.
As seen from Figure 1, the surface of detection sample have many surface cracks not of uniform size, bubble, voids and pits and
Hole, defect is more.
In order to quantify, objectively describing the degree of above-mentioned detection sample surface defect, first, using binary conversion treatment software
Photoshop carries out binary conversion treatment to the surface picture of gained detection sample, wherein, binary conversion treatment gray threshold is 60,
The gray value of defect part pixel is set to 0, obtains the detection sample of the concrete surface after binary conversion treatment as shown in Figure 2
Surface picture；Secondly, statistical analysis is carried out to the surface picture after binary conversion treatment, defect part pixel can be obtained and account for surface
The percentage A=17.8% of the total pixel of photo, according to formula S=S0× A calculates the area S=445cm of defect part2；Then,
Weigh quality m0The glass cement of=100g is smeared detection sample surface, and is smeared glass cement using soft force method
It is flat, it is floating during to keep glass cement be in natural packing state, smearing weighs the quality m of remaining glass cement after terminating1=42g,
Wherein glass cement bulk density ρ=1.9g/cm3, according to Formula V0=m0/ ρ and Formula V1=m1Before/ρ calculates glass cement smearing respectively
Volume V0=52.6cm3, glass cement smear after volume V1=22.1cm3, the Volume Changes be detection sample defect body
Product, according to Formula V=V0- V1Calculate the defect volume V=30.5cm of detection sample3；Finally, detection sample is calculated according to formula H=V/S
This defect mean depth H=0.069cm, defect mean depth H can be used to evaluate concrete surface open defect situation.
Table 1 is the grade scale of concrete surface ocular estimate, and wherein the grade scale is with reference to CJJ99-2003《City bridge
Beam maintenance technology specification》Formulated.
Table 1
Table 1 understands that the Surface Quality of Concrete for being detected has larger defect, and defect rank is IV grade.
Claims (9)
1. Surface Quality of Concrete method of determination and evaluation, it is characterised in that：The method is comprised the following steps：
1) it is S that one piece of area is chosen on concrete surface to be evaluated0Detection sample, under gentle natural light environment, shooting is obtained
The surface picture of sample must be detected；
2) binary conversion treatment, the wherein gray scale of defect part pixel are carried out to gained surface picture using binary conversion treatment software
Value is set to 0 or 255；
3) statistical analysis is carried out to the surface picture after binary conversion treatment, defect part pixel is obtained and is accounted for the total pixel of surface picture
The percentage A of point；
4) the defect area S of detection sample, defect area S and detection sample area S are calculated0Between meet following mathematical relationship：
S=S0×A；
5) filler is smeared in detection sample surface, and its is floating, front volume V is then smeared according to filler0With body after smearing
Product V1Change, equivalent substitution detects the defect volume V, defect volume V=V of sample0- V1；
6) the defect mean depth H of detection sample is calculated, defect mean depth H=V/S, the wherein unit of V are cm3, the list of S
Position is cm2, the unit of H is cm；
7) according to gained defect mean depth H overall merit concrete surface presentation qualities.
2. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 1) in,
Nature light direction is selected during shooting with the angle that detection sample surface is in 30~60 °.
3. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 1) in,
Nature light direction is selected during shooting with the angle that detection sample surface is in 35~45 °.
4. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 2) in,
The gray threshold of binary conversion treatment is adjusted according to the brightness of surface picture, or is selected according to the result of multiple manual value
Select.
5. Surface Quality of Concrete method of determination and evaluation according to claim 4, it is characterised in that：The step 2) in,
The gray threshold of binary conversion treatment is 60~80.
6. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 2) in,
Binary conversion treatment software uses Matlab softwares or Photoshop softwares.
7. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 5) in,
Filler matches somebody with somebody uniform fine sand or glass cement using level.
8. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 5) in,
It is using soft force method that filler is floating, it is floating during to keep filling agent particle or colloid be in natural packing state.
9. Surface Quality of Concrete method of determination and evaluation according to claim 1, it is characterised in that：The step 5) in,
Filler smears front volume V0=m0/ ρ, volume V after filler smearing1=m1/ρ；Wherein：m0Quality before being smeared for filler, m1
Quality, m after being smeared for filler0And m1Unit be g；ρ is filler bulk density, and the unit of ρ is g/cm3；V0And V1List
Position is cm3。
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107621436A (en) * | 2017-10-11 | 2018-01-23 | 云南省交通规划设计研究院 | A kind of cement concrete pore property analysis system and its method of testing |
| CN108896558A (en) * | 2018-06-27 | 2018-11-27 | 石家庄铁道大学 | Railway self-compacting concrete surface quality detection method and terminal device |
| CN108896746A (en) * | 2018-07-06 | 2018-11-27 | 中南大学 | Non-fragment orbit self-compacting concrete filling layer defects quantitative testing device and method |
| CN109490252A (en) * | 2018-11-15 | 2019-03-19 | 北京海瑞克科技发展有限公司 | A kind of interior formwork analysis method and device |
| CN110146511A (en) * | 2019-05-16 | 2019-08-20 | 中铁十二局集团建筑安装工程有限公司 | A kind of clear-water concrete bubble detecting method |
| CN110349123A (en) * | 2019-06-11 | 2019-10-18 | 东南大学 | A kind of quantitative evaluation method of apparent mass of clear concrete |
| CN110827264A (en) * | 2019-11-06 | 2020-02-21 | 四川济通工程试验检测有限公司 | Evaluation system for apparent defects of concrete member |
| CN111024503A (en) * | 2019-12-30 | 2020-04-17 | 中建七局第四建筑有限公司 | Annular test device for measuring internal tensile stress and crack development of soil body in real time |
| CN111060521A (en) * | 2019-12-31 | 2020-04-24 | 中国水利水电第十四工程局有限公司 | Method for detecting quantity and area of bubbles on surface of precast concrete T beam |
| CN113052804A (en) * | 2021-03-12 | 2021-06-29 | 中建西部建设贵州有限公司 | Concrete member appearance quality quantitative evaluation processing method and device |
| CN114187303A (en) * | 2021-11-23 | 2022-03-15 | 北京羽医甘蓝信息技术有限公司 | Oral cavity image processing method, device, electronic equipment and computer storage medium |
| CN114511619A (en) * | 2022-04-01 | 2022-05-17 | 石家庄市长安育才建材有限公司 | Concrete appearance evaluation method and device and computer readable storage medium |
| US20220381687A1 (en) * | 2019-12-19 | 2022-12-01 | Teknologian Tutkimuskeskus Vtt Oy | Method and apparatus for determining the quality of fresh concrete or the like |
| CN115808425A (en) * | 2023-01-30 | 2023-03-17 | 安徽新建控股集团有限公司 | Defect identification and countermeasures in the process of springback detection of concrete members |
| CN115830029A (en) * | 2023-02-21 | 2023-03-21 | 山东水利建设集团有限公司 | Spring soil detection method based on computer vision |
| CN116993740A (en) * | 2023-09-28 | 2023-11-03 | 山东万世机械科技有限公司 | Concrete structure surface defect detection method based on image data |
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| CN107621436A (en) * | 2017-10-11 | 2018-01-23 | 云南省交通规划设计研究院 | A kind of cement concrete pore property analysis system and its method of testing |
| CN108896558A (en) * | 2018-06-27 | 2018-11-27 | 石家庄铁道大学 | Railway self-compacting concrete surface quality detection method and terminal device |
| CN108896746A (en) * | 2018-07-06 | 2018-11-27 | 中南大学 | Non-fragment orbit self-compacting concrete filling layer defects quantitative testing device and method |
| CN109490252A (en) * | 2018-11-15 | 2019-03-19 | 北京海瑞克科技发展有限公司 | A kind of interior formwork analysis method and device |
| CN109490252B (en) * | 2018-11-15 | 2021-04-27 | 北京海瑞克科技发展有限公司 | Concrete surface bubble analysis method and device |
| CN110146511A (en) * | 2019-05-16 | 2019-08-20 | 中铁十二局集团建筑安装工程有限公司 | A kind of clear-water concrete bubble detecting method |
| CN110349123A (en) * | 2019-06-11 | 2019-10-18 | 东南大学 | A kind of quantitative evaluation method of apparent mass of clear concrete |
| CN110827264A (en) * | 2019-11-06 | 2020-02-21 | 四川济通工程试验检测有限公司 | Evaluation system for apparent defects of concrete member |
| US20220381687A1 (en) * | 2019-12-19 | 2022-12-01 | Teknologian Tutkimuskeskus Vtt Oy | Method and apparatus for determining the quality of fresh concrete or the like |
| CN111024503A (en) * | 2019-12-30 | 2020-04-17 | 中建七局第四建筑有限公司 | Annular test device for measuring internal tensile stress and crack development of soil body in real time |
| CN111060521A (en) * | 2019-12-31 | 2020-04-24 | 中国水利水电第十四工程局有限公司 | Method for detecting quantity and area of bubbles on surface of precast concrete T beam |
| CN111060521B (en) * | 2019-12-31 | 2024-01-02 | 中国水利水电第十四工程局有限公司 | Method for detecting quantity and area of air bubbles on surface of precast concrete T beam |
| CN113052804A (en) * | 2021-03-12 | 2021-06-29 | 中建西部建设贵州有限公司 | Concrete member appearance quality quantitative evaluation processing method and device |
| CN114187303A (en) * | 2021-11-23 | 2022-03-15 | 北京羽医甘蓝信息技术有限公司 | Oral cavity image processing method, device, electronic equipment and computer storage medium |
| CN114187303B (en) * | 2021-11-23 | 2025-03-07 | 北京羽医甘蓝信息技术有限公司 | Oral image processing method, device, electronic equipment and computer storage medium |
| CN114511619A (en) * | 2022-04-01 | 2022-05-17 | 石家庄市长安育才建材有限公司 | Concrete appearance evaluation method and device and computer readable storage medium |
| CN115808425A (en) * | 2023-01-30 | 2023-03-17 | 安徽新建控股集团有限公司 | Defect identification and countermeasures in the process of springback detection of concrete members |
| CN115830029A (en) * | 2023-02-21 | 2023-03-21 | 山东水利建设集团有限公司 | Spring soil detection method based on computer vision |
| CN115830029B (en) * | 2023-02-21 | 2023-04-28 | 山东水利建设集团有限公司 | A spring soil detection method based on computer vision |
| CN116993740A (en) * | 2023-09-28 | 2023-11-03 | 山东万世机械科技有限公司 | Concrete structure surface defect detection method based on image data |
| CN116993740B (en) * | 2023-09-28 | 2023-12-19 | 山东万世机械科技有限公司 | Concrete structure surface defect detection method based on image data |
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