CN106841575A - A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method - Google Patents
A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method Download PDFInfo
- Publication number
- CN106841575A CN106841575A CN201710018314.8A CN201710018314A CN106841575A CN 106841575 A CN106841575 A CN 106841575A CN 201710018314 A CN201710018314 A CN 201710018314A CN 106841575 A CN106841575 A CN 106841575A
- Authority
- CN
- China
- Prior art keywords
- polishing scratch
- mill spot
- edge
- spot image
- positioning method
- 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
- 238000005498 polishing Methods 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000012360 testing method Methods 0.000 title claims abstract description 26
- 238000003708 edge detection Methods 0.000 claims abstract description 14
- 238000012545 processing Methods 0.000 claims abstract description 10
- 238000001514 detection method Methods 0.000 claims abstract description 6
- 238000001914 filtration Methods 0.000 claims description 15
- 229910000831 Steel Inorganic materials 0.000 claims description 9
- 239000010959 steel Substances 0.000 claims description 9
- 238000002474 experimental method Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 8
- 238000010835 comparative analysis Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 5
- 239000003921 oil Substances 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000003556 assay Methods 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004040 coloring Methods 0.000 description 2
- 239000010687 lubricating oil Substances 0.000 description 2
- 238000011158 quantitative evaluation Methods 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- 231100000241 scar Toxicity 0.000 description 2
- 238000010408 sweeping Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000007728 cost analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000004519 grease Substances 0.000 description 1
- 239000000314 lubricant Substances 0.000 description 1
- 230000001050 lubricating effect Effects 0.000 description 1
- 238000005461 lubrication Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000015654 memory Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/28—Oils, i.e. hydrocarbon liquids
- G01N33/2888—Lubricating oil characteristics, e.g. deterioration
Landscapes
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medicinal Chemistry (AREA)
- Oil, Petroleum & Natural Gas (AREA)
- General Chemical & Material Sciences (AREA)
- Food Science & Technology (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Finish Polishing, Edge Sharpening, And Grinding By Specific Grinding Devices (AREA)
Abstract
A kind of four balls friction test mill spot image polishing scratch direction automatic positioning method of the invention, gray processing treatment is carried out to the polishing scratch image for not possessing obvious color for collecting first, increase the processing speed of image, rim detection is carried out by grinding spot figure to gray scale, obtain edge detection graph, again by being circulated rotation to edge detection graph, some groups of level marks values are obtained, polishing scratch deflection has been worth to eventually through the maximum horizontal mark for obtaining.The present invention can accurately determine the deflection of polishing scratch using marginal information, overcome testing crew because lacking experience or being short of the certainty of measurement brought.And multiple comparative analysis need not be carried out, you can obtain accurate polishing scratch deflection.
Description
Technical field
The present invention relates to the expanded application that a kind of four balls frictional testing machine determines oil lubrication performance, and in particular to a kind of
The method that polishing scratch direction is automatically positioned is carried out using marginal information.
Background technology
The good lubricating oil of lubricity can protect machinery, extension working life, be surveyed often through four-ball tribotester
Amount.According to China's oil chemical industry standard (GB-T 12583-1998 and H-T 0762-2005), the anti-wear performance of lubricant
Assay method is：The steel ball of three a diameter of 12.7mm is clamped in an oil box, and is submerged with formation testing, placed in three top dome portions
One steel ball of diameter, after formation testing temperature reaches 75 DEG C ± 2 DEG C, applies 147N or 392N active forces, heads a ball in certain rotating speed
Lower rotation 60min, then takes out three steel balls of bottom, three steel balls of measurement in the case where certainty of measurement is for the microscope of 0.01mm
Wear scar diameter, three steel balls are obtained six groups of measurement data, the anti-friction performance of lubricating oil or lubricating grease by three six times of ball
The arithmetic mean of instantaneous value of the spot diameter that rubs of measurement is evaluated.The determination in polishing scratch direction can be easy to the measurement of wear scar diameter, ajust mill
The shooting angle of spot image, and it is easy to follow-up analyzing and processing such as follow-up polishing scratch intensity, density etc..Based on this, we
Propose a kind of polishing scratch direction automatic positioning method based on marginal information.
The content of the invention
It is an object of the invention to provide a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method, certainly
Due to the perceptual error of testing crew in existing assay method, the defect such as caused certainty of measurement is inaccurate.
To reach above-mentioned purpose, the present invention is adopted the following technical scheme that and is achieved：
A kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that the present invention is provided, including following step
Suddenly：
Step S1, after four ball friction tests terminate, the mill spot image F on three used bottom steel balls of collection experiment；
Step S2, the colored mill spot image F that will be collected carries out gray processing treatment, obtains gray scale mill spot figure f；
Step S3, grinding spot figure f to gray scale by edge detection operator carries out rim detection, for extracting the mill in mill spot figure
Trace, obtains mill spot edge figure E；
Step S4, above-mentioned resulting mill spot edge figure E is rotated with the anglec of rotation of α=0 for the first time, is revolved
The rotated edge map E of α is turnedα；
Step S5, calculates the rotated edge map E of above-mentioned gainedαMiddle xth row is from (x, 1) to the length of the continuous boundary of (x, y)
Degree, obtains row edge figure d longα；
Step S6, to the edge graph d long of above-mentioned gainedαProgressive scan filtering process is from left to right carried out, is retained in often going
The continuous long edge more than certain value T, obtains going filtering figure hα；
Step S7, calculates rotated edge map EαLevel marks Sα；
Step S8, works as α<At 180 °, then step S4 to step S7 need to be performed with iterative method circulation；
Step S9, when α >=180 °, then according to level marks SαIt is determined that mill spot image direction horizontal angle θ.
Preferably, in step S1, the pixel size of the mill spot image F is M × N, any pixel of the mill spot image F
The coordinate of point is (x, y), then x and y represent the row and column of the pixel respectively, and x and y are integer.
Preferably, in step S2, the gray value of pixel (x, y) is f (x, y) in gray scale mill spot image f, then f (x,
Y) shown in calculating formula such as formula (1)：
F (x, y)=0.3R (x, y)+0.59G (x, y)+0.11B (x, y) (1)
Wherein, R (x, y), G (x, y) and B (x, y) represent the red color component value of pixel (x, y) in mill spot image F, green respectively
Colouring component value and blue color component value.
Preferably, in step S3, described edge detection operator is Sobel, Canny or Prewit edge detection operator,
Wherein, the mill spot edge figure E is binary map, wherein, E (x, y)=1 represents marginal point, and E (x, y)=0 represents non-edge point.
Preferably, in step S4, described rotated edge map EαIt is binary map, its size is MαAnd Nα, wherein, Eα(x,y)
=1 represents marginal point, Eα(x, y)=0 represents non-edge point.
Preferably, in step S5, row edge calculating formula (2) long is such as formula：
Wherein, dα(x, y) represents that the continuous boundary of row edge image vegetarian refreshments (x, y) long is long, that is, represent pixel in xth row
There is (d on the left of (x, y)α(x, y) -1) individual 1.
Preferably, in step S6, the calculating formula (3) of the row filtering process is such as formula：
Wherein, hα(x, y) is the pixel value of row filtering image vegetarian refreshments (x, y), and T is definite value, and value is 10~100.
Preferably, in step S7, the calculating formula (4) of the level marks is such as formula：
Wherein, the level marks SαIt is maximum to be worth, and the polishing scratch of mill spot figure F is located at horizontal direction；The level marks SαValue
It is minimum, the polishing scratch of mill spot figure F is located at vertical direction.
Preferably, in step S8, the iterative method refers to add fixed rotary step β as new rotation using anglec of rotation α
Gyration is circulated rotation, i.e. α=alpha+beta, wherein, the value of β is smaller, and precision is higher, and C is obtained afterwardsβThe mill spot gray scale of group
The rotation array of figure and level marks S corresponding with its arrayαValue.
Preferably, in step S9, according to above-mentioned gained CβThe level marks S of groupα, meetWhen, then α=θ.
Compared with prior art, the beneficial effects of the invention are as follows：
A kind of four balls friction test mill spot image polishing scratch direction automatic positioning method of the invention, first to collecting not
The polishing scratch image for possessing obvious color carries out gray processing treatment, increases the processing speed of image, is entered by grinding spot figure to gray scale
Row rim detection, obtains edge detection graph, then by being circulated rotation to edge detection graph, has obtained some groups of level marks
Value, polishing scratch deflection is worth to eventually through the maximum horizontal mark for obtaining.The present invention can accurately really using marginal information
Determine the direction of polishing scratch, overcome testing crew because lacking experience or being short of the certainty of measurement brought.And need not carry out repeatedly to score
Analysis, you can obtain accurate polishing scratch deflection.
Brief description of the drawings
Fig. 1 is polishing scratch deflection θ schematic diagrames；
Fig. 2 is mill spot image F schematic diagrames；
Fig. 3 is gray scale mill spot figure f schematic diagrames；
Fig. 4 is mill spot edge figure E schematic diagrames；
Fig. 5 is rotated edge map EαSchematic diagram.
Specific embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail.
The present invention characterizes polishing scratch direction with the horizontal angle of polishing scratch, and polishing scratch horizontal angle is defined as polishing scratch and horizontal line is intersecting
Afterwards, left horizontal rays and the upper left corner folded by upper polishing scratch ray, Fig. 1 polishing scratch horizontal angles θ.
The present invention proposes a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method, including following step
Suddenly：
Step S1：The mill spot image of experiment steel ball is gathered by Scanning Electron microscope.Specifically：In four ball friction tests
After end, three used bottom steel balls taking-ups will be tested respectively and will be placed in surface sweeping Electronic Speculum, and adjust the light of surface sweeping Electronic Speculum
According to the parameter such as multiplication factor, clearly to collect mill spot image, the mill spot image F for being gathered is represented, such as Fig. 2 institutes
Show.Meanwhile, the pixel size of the mill spot image F for obtaining is M × N, and the size for for example grinding spot image is 768 × 1024, i.e. M
=768, N=1024.Meanwhile, utilize (x, y) to represent the coordinate of any pixel point of mill spot image F, then x and y represent this respectively
The row and column of pixel, and x and y are integer；
Step S2：The colored mill spot image that will be collected carries out gray processing treatment.The mill spot image collected in step S1
Without significant colouring information, therefore gray processing treatment first preferably is carried out to mill spot image, can so greatly speed up processing speed.
Specifically, mill spot image F is converted into gray level image, obtains gray scale mill spot figure f as shown in Figure 3, then in gray scale mill spot image f
The gray value of pixel (x, y) is f (x, y), then shown in the calculating formula of f (x, y) such as formula (1)：
F (x, y)=0.3R (x, y)+0.59G (x, y)+0.11B (x, y) (1)
Wherein, f (x, y) represents the gray value of pixel (x, y) in gray scale mill spot figure f；R (x, y), G (x, y) and B (x, y) point
Red color component value, green component values and the blue color component value of pixel (x, y) in spot image F Biao Shi not ground；
Step S3：Rim detection.Rim detection is carried out by edge detection operator to gray scale mill spot image f to can be used to extract
Polishing scratch in mill spot figure, described edge detection operator can be Sobel, Canny or Prewit edge detection operator, be ground
Spot edge figure E, as shown in Figure 4.The present embodiment takes traditional Sobel edge detection operators.The mill spot edge figure E that obtains is
Binary map, wherein, E (x, y)=1 represents marginal point, and E (x, y)=0 represents non-edge point.
Step S4：Rotation mill spot edge figure.By above-mentioned resulting mill spot edge figure E for the first time with the anglec of rotation of α=0
(not performing rotation for the first time) is rotated, and obtains the rotated edge map E that have rotated α as shown in Figure 5α.The rotation of gained
Edge graph EαSize be MαAnd Nα.Likewise, described rotated edge map EαIt is also binary map, wherein, Eα(x, y)=1 represents
Marginal point, Eα(x, y)=0 represents non-edge point.
Step S5：Calculate row edge long.Rotated edge map E is evaluated by the way that row edge is longαMiddle xth row from (x, 1) to (x,
The length of continuous boundary y), obtains row edge figure d longα, wherein, row edge calculating formula 2 long) such as formula：
Wherein, dα(x, y) represents that the continuous boundary of row edge image vegetarian refreshments (x, y) long is long, that is, represent pixel in xth row
There is (d on the left of (x, y)α(x, y) -1) individual 1.
Step S6：The row filtering process of row edge figure long.To edge graph d longαFrom left to right carry out at progressive scan filtering
Reason, retains the continuous long edge more than certain value T in often going, and obtains going filtering figure hα.Because polishing scratch has significant direction one
Cause property, when polishing scratch is horizontally oriented, polishing scratch edge is also at level, when entering every trade filtering, will be retained；When polishing scratch is in
During vertical direction, when entering every trade filtering, nearly all it is deleted.
The calculating formula (3) of row filtering process is such as formula：
Wherein, hα(x, y) is the pixel value of row filtering image vegetarian refreshments (x, y), and T is definite value, and general value is 10~100.
Step S7：Calculate rotated edge map EαLevel marks.Use SαRepresent EαLevel marks, level marks SαValue table
Degree of the polishing scratch positioned at horizontal direction, level marks S are leviedαValue is bigger, polishing scratch closer to horizontal direction, i.e.,：When mill spot figure F's
When polishing scratch is located at horizontal direction, level marks SαValue is maximum；When the polishing scratch for grinding spot figure F is located at vertical direction, level marks SαValue
It is minimum.The calculating formula (4) of level marks is such as formula：
Step S8：Calculate new anglec of rotation α.
Work as α<At 180 °, then step S4 to step S7 need to be performed with iterative method circulation, i.e. the iterative method refers to rotate
Angle [alpha] adds fixed rotary step β and is circulated rotation as the new anglec of rotation, i.e. α=alpha+beta, wherein, the value of β is got over
Small, precision is higher；
When α >=180 °, then step S9 is transferred to.
Step S9：Polishing scratch direction determines.
When the polishing scratch direction for grinding spot image is rotated to horizontal direction, the level marks S for obtainingαValue is maximum, is based on
The level marks array for obtaining can determine that the direction of polishing scratch.Specifically：
According to step-length β rotation mill spot gray-scale maps, will obtainThe rotation array of the mill spot gray-scale map of group,
And level marks S corresponding with its arrayα, wherein, CβTo grind the rotation array of spot gray-scale map.
In CβThe level marks S of groupαIn, work as satisfactionWhen, then α=θ, θ is polishing scratch direction horizontal angle, is mill
Trace and horizontal angle, for characterizing polishing scratch direction.
According to above technical scheme, in terms of run time and cost analysis two, contrast the present invention program and
The advantage and disadvantage of traditional manual measurement method.
1 run time.By taking the image of the present embodiment as an example, simulation process platform of the invention is：At Intel I3 M350
Reason device, the computer of 2GB internal memories is emulated under MATLAB platforms, and the time used by algorithm is 42 seconds, and hardware realizes this calculation
After method, Riming time of algorithm can also greatly reduce.
2 precision analysis.It is to rely primarily on human eye to judge to carry out qualitative estimation that conventional method determines one, does not have quantitative evaluation
Value, can produce ambiguous；This method has quantitative evaluation criteria, therefore the polishing scratch directional precision for judging is higher than tradition side
Method.
Claims (10)
1. a kind of four balls friction test grinds spot image polishing scratch direction automatic positioning method, it is characterised in that comprise the following steps：
Step S1, after four ball friction tests terminate, the mill spot image F on three used bottom steel balls of collection experiment；
Step S2, the colored mill spot image F that will be collected carries out gray processing treatment, obtains gray scale mill spot figure f；
Step S3, grinding spot figure f to gray scale by edge detection operator carries out rim detection, for extracting the polishing scratch in mill spot figure,
Obtain mill spot edge figure E；
Step S4, above-mentioned resulting mill spot edge figure E is rotated with the anglec of rotation of α=0 for the first time, be have rotated
The rotated edge map E of αα；
Step S5, calculates the rotated edge map E of above-mentioned gainedαMiddle xth row to the length of the continuous boundary of (x, y), is obtained from (x, 1)
To row edge figure d longα；
Step S6, to the edge graph d long of above-mentioned gainedαProgressive scan filtering process is from left to right carried out, retains continuously long in often going
More than the edge of certain value T, obtain going filtering figure hα；
Step S7, calculates rotated edge map EαLevel marks Sα；
Step S8, works as α<At 180 °, then step S4 to step S7 need to be performed with iterative method circulation；
Step S9, when α >=180 °, then according to level marks SαIt is determined that mill spot image direction horizontal angle θ.
2. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S1, the pixel size of the mill spot image F is M × N, and the coordinate of any pixel point of the mill spot image F is
(x, y), then x and y represent the row and column of the pixel respectively, and x and y are integer.
3. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S2, the gray value of pixel (x, y) is f (x, y) in the gray scale mill spot image f, then the calculating formula of f (x, y)
As shown in formula (1)：
F (x, y)=0.3R (x, y)+0.59G (x, y)+0.11B (x, y) (1)
Wherein, R (x, y), G (x, y) and B (x, y) represent the red color component value of pixel (x, y) in mill spot image F, green point respectively
Value and blue color component value.
4. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S3, described edge detection operator is Sobel, Canny or Prewit edge detection operator, wherein, the mill
Spot edge figure E is binary map, wherein, E (x, y)=1 represents marginal point, and E (x, y)=0 represents non-edge point.
5. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S4, described rotated edge map EαIt is binary map, its size is MαAnd Nα, wherein, Eα(x, y)=1 represents side
Edge point, Eα(x, y)=0 represents non-edge point.
6. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S5, row edge calculating formula (2) long is such as formula：
Wherein, dα(x, y) represents that the continuous boundary of row edge image vegetarian refreshments (x, y) long is long, that is, represent pixel (x, y) in xth row
Left side have (dα(x, y) -1) individual 1.
7. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S6, the calculating formula (3) of the row filtering process is such as formula：
Wherein, hα(x, y) is the pixel value of row filtering image vegetarian refreshments (x, y), and T is definite value, and value is 10~100.
8. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S7, the calculating formula (4) of the level marks is such as formula：
Wherein, the level marks SαIt is maximum to be worth, and the polishing scratch of mill spot figure F is located at horizontal direction；The level marks SαIt is worth for most
Small, the polishing scratch of mill spot figure F is located at vertical direction.
9. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 1 is above-mentioned, its feature
It is：In step S8, the iterative method refers to add fixed rotary step β using anglec of rotation α to be carried out as the new anglec of rotation
Circulation rotating, i.e. α=alpha+beta, wherein, the value of β is smaller, and precision is higher, and C is obtained afterwardsβThe rotation number of the mill spot gray-scale map of group
Group and level marks S corresponding with its arrayαValue.
10. according to a kind of four balls friction test mill spot image polishing scratch direction automatic positioning method that claim 8 is above-mentioned, its feature
It is：In step S9, according to above-mentioned gained CβThe level marks S of groupα, meetWhen, then α=θ.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710018314.8A CN106841575B (en) | 2017-01-11 | 2017-01-11 | A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710018314.8A CN106841575B (en) | 2017-01-11 | 2017-01-11 | A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106841575A true CN106841575A (en) | 2017-06-13 |
| CN106841575B CN106841575B (en) | 2019-02-05 |
Family
ID=59118174
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710018314.8A Expired - Fee Related CN106841575B (en) | 2017-01-11 | 2017-01-11 | A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106841575B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107403445A (en) * | 2017-07-20 | 2017-11-28 | 长安大学 | A kind of pattern comparative analysis method for lubricant wear resistence |
| CN110568164A (en) * | 2019-07-24 | 2019-12-13 | 国电科学技术研究院有限公司 | Method for judging service performance of steam turbine oil from friction performance perspective |
| WO2021169996A1 (en) * | 2020-02-26 | 2021-09-02 | 长安大学 | Grinding mark angle automatic detection method based on grinding mark gray level similarity |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080132149A1 (en) * | 2006-12-05 | 2008-06-05 | Feng Chia University | Grinding method and system with non-contact real-time detection of workpiece thickness |
| CN102289821A (en) * | 2011-08-25 | 2011-12-21 | 西北工业大学 | Image detection method for side-slipping motion of vehicle |
| CN102538692A (en) * | 2012-01-17 | 2012-07-04 | 济南试金集团有限公司 | Four-ball wear scar testing device |
-
2017
- 2017-01-11 CN CN201710018314.8A patent/CN106841575B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080132149A1 (en) * | 2006-12-05 | 2008-06-05 | Feng Chia University | Grinding method and system with non-contact real-time detection of workpiece thickness |
| CN102289821A (en) * | 2011-08-25 | 2011-12-21 | 西北工业大学 | Image detection method for side-slipping motion of vehicle |
| CN102538692A (en) * | 2012-01-17 | 2012-07-04 | 济南试金集团有限公司 | Four-ball wear scar testing device |
Non-Patent Citations (3)
| Title |
|---|
| 孙卫强 等: "基于图像处理的磨痕快速测量方法研究", 《武汉理工大学学报 信息与管理工程版》 * |
| 肖梅 等: "一种新的边缘检测算法研究", 《郑州大学学报(工学版)》 * |
| 肖梅 等: "基于磨痕检测的润滑油抗磨性能测定方法", 《交通运输工程学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107403445A (en) * | 2017-07-20 | 2017-11-28 | 长安大学 | A kind of pattern comparative analysis method for lubricant wear resistence |
| CN110568164A (en) * | 2019-07-24 | 2019-12-13 | 国电科学技术研究院有限公司 | Method for judging service performance of steam turbine oil from friction performance perspective |
| WO2021169996A1 (en) * | 2020-02-26 | 2021-09-02 | 长安大学 | Grinding mark angle automatic detection method based on grinding mark gray level similarity |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106841575B (en) | 2019-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104458755B (en) | Multi-type material surface defect detection method based on machine vision | |
| CN102636490B (en) | Method for detecting surface defects of dustproof cover of bearing based on machine vision | |
| CN102607977B (en) | Abrasion in-situ measuring device based on digital image processing and method | |
| CN104730091B (en) | The extraction of gas turbine blades defect and analysis method based on region segmentation detection | |
| CN106770296A (en) | A kind of four ball friction tests mill spot image polishing scratch deflection automatic measuring method | |
| CN107239742B (en) | Method for calculating scale value of instrument pointer | |
| CN106841575B (en) | A kind of four ball friction tests mill spot image polishing scratch direction automatic positioning method | |
| CN102136061A (en) | Method for automatically detecting, classifying and identifying defects of rectangular quartz wafer | |
| CN111583114A (en) | Automatic measuring device and measuring method for pipeline threads | |
| CN204405501U (en) | A kind of detecting and analysing system of cement-based material pore structure | |
| CN104778684A (en) | Method and system thereof for automatically measuring, representing and classifying heterogeneous defects on surface of steel | |
| CN103712565B (en) | A kind of wear scar diameter measuring method based on steel ball polishing scratch gradient | |
| US20220245789A1 (en) | Dual-neighborhood wear angle automatic detection method | |
| DE102019121446A1 (en) | Quantitative characterization method for the area and content of different types of inclusions in steel | |
| CN103761729B (en) | Steel ball grinding crack detection method based on neighborhood gray level similarity | |
| WO2021169996A1 (en) | Grinding mark angle automatic detection method based on grinding mark gray level similarity | |
| CN102914479A (en) | Automatic Brinell hardness testing method | |
| CN104748684B (en) | Visual detection method and device for crankshaft shoulder back chipping | |
| CN106546185A (en) | A kind of profile quality determining method based on Machine Vision Detection | |
| CN103063674A (en) | Detection method for copper grade of copper block, and detection system thereof | |
| CN104655642A (en) | Automatic measurement, characterization and classification method for steel cracking defects and system of method | |
| CN107358604B (en) | Four-ball friction test speckle image anomaly detection method | |
| CN103472070B (en) | Method for determining detergency and dispersibility of engine oil | |
| CN105547200A (en) | Method for measurement of finished surface roughness of C/SiC composite materials on the basis of image grey information | |
| CN108846839A (en) | A kind of saggar crack detecting method based on fan-shaped neighborhood difference histogram |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190205 Termination date: 20200111 |