CN112529869B - Valve sleeve throttling square hole detection method - Google Patents
Valve sleeve throttling square hole detection method Download PDFInfo
- Publication number
- CN112529869B CN112529869B CN202011444969.XA CN202011444969A CN112529869B CN 112529869 B CN112529869 B CN 112529869B CN 202011444969 A CN202011444969 A CN 202011444969A CN 112529869 B CN112529869 B CN 112529869B
- Authority
- CN
- China
- Prior art keywords
- square hole
- image
- valve sleeve
- orifice
- throttling
- 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.)
- Active
Links
- 238000001514 detection method Methods 0.000 title abstract description 7
- 238000005259 measurement Methods 0.000 claims abstract description 16
- 238000000034 method Methods 0.000 claims description 27
- 230000035772 mutation Effects 0.000 claims description 2
- 238000011179 visual inspection Methods 0.000 claims 4
- 230000000007 visual effect Effects 0.000 abstract description 7
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0006—Industrial image inspection using a design-rule based approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention relates to a valve pocket throttling square hole detection method, firstly, a three-dimensional measuring head is adopted to calibrate a measurement system, a visual image measuring head is utilized to obtain a square hole image of a valve pocket throttling square hole, through denoising and binarization processing, a throttling square hole boundary point is obtained, a boundary line is fitted, the length and width dimensions of the valve pocket throttling square hole are obtained, then the boundary line is offset, and whether four corners of the throttling square hole meet the requirements of sharp edges is judged; and finally, detecting the size of the relative throttling square hole by rotating the measuring head, and judging whether the throttling square meets the requirement of hole coplanarity. The invention can accurately measure the requirements of the valve sleeve throttling square hole size, sharp edges and coplanarity, and has high measurement speed and high measurement result precision.
Description
Technical Field
The invention relates to the technical field of measurement, in particular to a valve sleeve throttling square hole visual detection method.
Background
The valve core and the valve sleeve matching parts are key parts in a hydraulic servo control product, wherein the throttle square hole of the valve sleeve part not only needs to ensure the axial position size and sharp edge requirement, but also needs to ensure coplanarity requirement, and the position and shape precision of the throttle square hole determines indexes such as hydraulic flow output signals, logic conversion control realization precision and the like. Because the square hole size is smaller, can't pass through contact measurement, current valve pocket throttle square hole detects, adopts omnipotent instrument microscope to measure, needs manual adjustment eyepiece, objective to focus, and measurement of inefficiency, the human factor influence is great. The valve sleeve throttling square hole visual detection method provided by the invention combines three coordinates with visual measurement, can rapidly and accurately measure the requirements of the valve sleeve throttling square hole on the size, sharp edge and coplanarity, and has stable measurement result and is not influenced by human factors.
Disclosure of Invention
The purpose of the invention is that: the valve sleeve throttling square hole detection method can be used for visually and rapidly and accurately measuring the requirements of the valve sleeve throttling square hole on the size, sharp edges and coplanarity, and the measurement result is stable and is not influenced by human factors.
The technical scheme of the invention is as follows:
the method is characterized by comprising the following steps of:
step one: clamping and fixing the valve sleeve, and positioning the valve sleeve throttling square hole center and the plane where the valve sleeve throttling square hole orifice is positioned by utilizing three-dimensional measurement to obtain spatial position data of the valve sleeve throttling square hole center and the plane where the valve sleeve throttling square hole orifice is positioned; changing a measuring needle of the three-coordinate measuring machine into an image measuring head, and acquiring an orifice image of a valve sleeve throttling square hole through the image measuring head;
step two: denoising the orifice image, and then binarizing to obtain a binarized orifice image;
step three, obtaining orifice boundary points of a throttling square hole from a binarized orifice image, and fitting a rectangular boundary line and the length and width of the rectangle through the obtained orifice boundary points;
step four: the four rectangular boundary lines are offset in parallel towards the rectangular center by the same distance to obtain four offset boundary lines, and the offset boundary lines are intersected to obtain four intersection points serving as reference points
Step five, intercepting orifice boundary points in the binarized orifice image through the datum point and the two offset boundary lines passing through the datum point, and judging whether the distance between each intercepted orifice boundary point and the datum point meets a preset value or not.
Further, under the condition that a plurality of valve sleeve throttling square holes are annularly arranged on the valve sleeve, in the first step, after the center of one valve sleeve throttling square hole and the plane where the orifice of the valve sleeve throttling square hole is located are positioned, the image measuring head is rotated, image acquisition is carried out on the orifice of each valve sleeve throttling square hole, images of all orifices are compared, and whether the horizontal position of all valve sleeve throttling square holes meets the process standard is judged.
Further, the same distance is 0.05mm or less. For example 0.03mm.
Further, in the denoising processing in the second step, a method of subtracting the polished image from the non-polished image at the same position is adopted to remove the non-random noise in the image, so that the image with the non-random noise removed is obtained;
and denoising the image with the non-random noise removed by adopting a Gaussian denoising method, and removing the random noise in the image, thereby obtaining the square hole image with the random noise removed.
Further, selecting a threshold according to the gray level histogram of the aperture image, and performing binarization processing on the square aperture image according to the selected threshold;
in the third step, four boundary lines are fitted through orifice boundary points of the throttling square holes corresponding to the orifice sides, and the average distance of a pair of boundary lines of the relative positions is obtained.
In the fifth step, it is determined whether the distance between each of the obtained orifice boundary points and the reference point is equal to or greater than 0.05mm.
If the distances are all larger than or equal to 0.05, the requirements of R0.05max are met, otherwise, the requirements of R0.05max are not met.
When the rotation influences the measuring head, the measuring head can be rotated by 90 degrees or 180 degrees each time, the sizes of the opposite throttling square holes are detected by the same method, the average distances from the boundary points on the opposite square holes to the valve sleeve reference surface are calculated respectively, if the average distance difference is smaller than or equal to 0.005, the requirement of coplanarity of 0.005 is met, otherwise, the requirement is not met.
The invention has the advantages that: the method provided by the invention combines three coordinates with vision measurement, can rapidly and accurately measure the requirements of the valve sleeve throttling square hole size, sharp edges and coplanarity, and has stable measurement results and no influence of human factors.
Drawings
FIG. 1 is a schematic diagram of the measurement of the sharp edge R0.05max of a throttling square hole according to the invention;
FIG. 2 is a representation of a throttled square bore of the present invention;
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
In the example of the present invention, the measurement accuracy of the three coordinates was (1.69+L/280 μm), and the resolution of the visual measurement was 2.5. Mu.m.
A valve sleeve throttling square hole visual detection method comprises the following steps:
step one: calibrating a measuring system by adopting a three-coordinate measuring head, and acquiring a square hole image of a valve sleeve throttling square hole by utilizing a visual image measuring head;
step two: denoising the obtained square hole image to obtain a denoised square hole image, wherein the denoising method comprises the following sub-steps of:
step 2.1: removing non-random noise in the image by adopting a method of subtracting the square hole image polished at the same position from the image not polished to obtain an image from which the non-random noise is removed;
step 2.2: and denoising the image with the non-random noise removed by adopting a Gaussian denoising method, and removing the random noise in the image, thereby obtaining the square hole image with the random noise removed.
Step three: performing binarization processing on the square hole image, obtaining a throttling square hole boundary point and fitting the boundary line, and solving the length and width dimensions of the valve sleeve throttling square hole, wherein the method comprises the following substeps:
step 3.1: selecting a proper threshold according to the gray level histogram of the square hole image, performing binarization processing on the square hole image, and extracting the square hole boundary aiming at the binarized image identification gray level mutation point;
step 3.2: fitting two long boundary lines of the square hole, obtaining the average distance from each long boundary point to the corresponding long boundary line to be the dimension in the length direction of the square hole, fitting two wide boundary lines of the square hole, and obtaining the average distance from each wide boundary point to the corresponding wide boundary line to be the dimension in the width direction of the square hole.
Step four: and (3) offsetting the boundary line, and judging whether four corners of the throttling square hole meet R0.05max or not, wherein the concrete method is as follows:
and respectively offsetting four boundary lines of the square hole to the center of the square hole by 0.05 to obtain 4 intersecting points, respectively solving the distances from the boundary points within the range of 90 degrees of four corners to the nearest intersecting point, and if the distances are equal to or greater than 0.05, meeting the requirement of R0.05max, otherwise, not meeting the requirement of R0.05max.
Step five: the measuring head is rotated, the relative throttle square hole size is detected, and whether the coplanarity of the throttle square holes meets the requirement of 0.005 is judged, wherein the specific method is as follows:
and rotating the measuring head by 180 degrees, detecting the sizes of the opposite throttling square holes by the same method, respectively calculating the average distances from the boundary points on the opposite square holes to the valve sleeve reference surface, and if the average distance difference is less than or equal to 0.005, meeting the requirement of 0.005 on coplanarity, otherwise, not meeting the requirement.
Claims (5)
1. The method for visually detecting the valve sleeve throttling square hole utilizes a three-coordinate measuring machine and an image measuring head and is characterized by comprising the following steps:
step one: clamping and fixing the valve sleeve, and positioning the valve sleeve throttling square hole center and the plane where the valve sleeve throttling square hole orifice is positioned by utilizing three-dimensional measurement to obtain spatial position data of the valve sleeve throttling square hole center and the plane where the valve sleeve throttling square hole orifice is positioned; changing a measuring needle of the three-coordinate measuring machine into an image measuring head, and acquiring an orifice image of a valve sleeve throttling square hole through the image measuring head;
step two: the aperture image is firstly subjected to denoising treatment and then binarization treatment, so that a binarized aperture image is obtained, wherein the method comprises the following substeps:
step 2.1, removing non-random noise in the image by adopting a method of subtracting the square hole image polished at the same position from the image which is not polished, and obtaining the image from which the non-random noise is removed;
step 2.2: denoising the image with the non-random noise removed by adopting a Gaussian denoising method, and removing the random noise in the image, so as to obtain a square hole image with the random noise removed;
step three, obtaining orifice boundary points of a throttling square orifice from a binarized orifice image, fitting a rectangular boundary line and the dimension in the length direction and the dimension in the width direction of the square orifice through the obtained orifice boundary points of the square orifice, and the method comprises the following substeps:
step 3.1: selecting a proper threshold according to the gray level histogram of the square hole image, performing binarization processing on the square hole image, and extracting the square hole boundary aiming at the binarized image identification gray level mutation point;
step 3.2: fitting two long boundary lines of the square hole, obtaining the average distance from each long boundary point to the corresponding long boundary line to be the dimension in the length direction of the square hole orifice, fitting two wide boundary lines of the square hole, and obtaining the average distance from each wide boundary point to the corresponding wide boundary line to be the dimension in the width direction of the square hole orifice;
step four: the four rectangular boundary lines are offset in parallel to the rectangular center by the same distance to obtain four offset boundary lines, and the offset boundary lines are intersected to obtain four intersection points serving as reference points;
step five, intercepting orifice boundary points in the binarized orifice image through the datum point and the two offset boundary lines passing through the datum point, and judging whether the distance between each intercepted orifice boundary point and the datum point meets a preset value or not;
and step six, rotating the image measuring head in the step one, acquiring an orifice image of the valve sleeve throttling square hole every time by 90 degrees or 180 degrees, repeating the step two and the step three to detect the size of the opposite throttling square hole, respectively calculating the average distance from the boundary point on the opposite square holes to the valve sleeve reference surface, and if the average distance difference is smaller than or equal to 0.005, meeting the requirement of coplanarity of 0.005, otherwise, not meeting the requirement.
2. The visual inspection method for the valve sleeve throttling square hole according to claim 1, wherein the method comprises the following steps of: and (3) under the condition that a plurality of valve sleeve throttling square holes are annularly arranged on the valve sleeve, in the first step, after the center of one valve sleeve throttling square hole and the plane where the orifice of the valve sleeve throttling square hole is positioned are positioned, the image measuring head is rotated, the image acquisition is carried out on the orifice of each valve sleeve throttling square hole, all orifice images are compared, and whether the horizontal position of all valve sleeve throttling square holes meets the process standard is judged.
3. The visual inspection method for the valve sleeve throttling square hole according to claim 1, wherein the method comprises the following steps of: the same distance is 0.05mm or less.
4. The visual inspection method for the valve sleeve throttling square hole according to claim 1, wherein the method comprises the following steps of: and fifthly, judging whether the distance between each intercepted orifice boundary point and the datum point is greater than or equal to 0.05mm.
5. The visual inspection method for the valve sleeve throttling square hole according to claim 1, wherein the method comprises the following steps of: the same distance is 0.03mm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011444969.XA CN112529869B (en) | 2020-12-11 | 2020-12-11 | Valve sleeve throttling square hole detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011444969.XA CN112529869B (en) | 2020-12-11 | 2020-12-11 | Valve sleeve throttling square hole detection method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112529869A CN112529869A (en) | 2021-03-19 |
| CN112529869B true CN112529869B (en) | 2023-07-21 |
Family
ID=75000281
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011444969.XA Active CN112529869B (en) | 2020-12-11 | 2020-12-11 | Valve sleeve throttling square hole detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112529869B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114739314B (en) * | 2022-03-01 | 2023-01-17 | 上海交通大学 | Method and device for precisely measuring profile of square hole of valve sleeve shell of electro-hydraulic servo valve |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203964822U (en) * | 2014-07-15 | 2014-11-26 | 安徽江淮汽车股份有限公司 | A kind of apart from cubing |
| WO2015115669A1 (en) * | 2014-01-28 | 2015-08-06 | Ricoh Company, Limited | Calibration method and measurement tool |
| WO2015154487A1 (en) * | 2014-04-09 | 2015-10-15 | 华南理工大学 | Grouped holes verticality detection system and method based on visual measurement |
| EP3339943A1 (en) * | 2016-12-21 | 2018-06-27 | Fielmann Ventures GmbH | Method and system for obtaining optometric parameters for fitting eyeglasses |
| CN109238084A (en) * | 2018-08-28 | 2019-01-18 | 合肥工业大学 | A kind of Autonomous Seam Locating Method of miniature circular hole measurement |
| CN110567339A (en) * | 2019-10-16 | 2019-12-13 | 洛阳Lyc轴承有限公司 | Method for detecting position degree of circumferential hole on end face of super-huge type bearing |
| CN112001917A (en) * | 2020-09-04 | 2020-11-27 | 南京大学金陵学院 | Machine vision-based geometric tolerance detection method for circular perforated part |
-
2020
- 2020-12-11 CN CN202011444969.XA patent/CN112529869B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015115669A1 (en) * | 2014-01-28 | 2015-08-06 | Ricoh Company, Limited | Calibration method and measurement tool |
| WO2015154487A1 (en) * | 2014-04-09 | 2015-10-15 | 华南理工大学 | Grouped holes verticality detection system and method based on visual measurement |
| CN203964822U (en) * | 2014-07-15 | 2014-11-26 | 安徽江淮汽车股份有限公司 | A kind of apart from cubing |
| EP3339943A1 (en) * | 2016-12-21 | 2018-06-27 | Fielmann Ventures GmbH | Method and system for obtaining optometric parameters for fitting eyeglasses |
| CN109238084A (en) * | 2018-08-28 | 2019-01-18 | 合肥工业大学 | A kind of Autonomous Seam Locating Method of miniature circular hole measurement |
| CN110567339A (en) * | 2019-10-16 | 2019-12-13 | 洛阳Lyc轴承有限公司 | Method for detecting position degree of circumferential hole on end face of super-huge type bearing |
| CN112001917A (en) * | 2020-09-04 | 2020-11-27 | 南京大学金陵学院 | Machine vision-based geometric tolerance detection method for circular perforated part |
Non-Patent Citations (2)
| Title |
|---|
| 一种面向对缝测量的双线结构光光条中心提取方法;丁祖娇;《航空制造技术》;全文 * |
| 某车门储物盒模具设计;王正社;《模具工业》;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112529869A (en) | 2021-03-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107341802B (en) | Corner sub-pixel positioning method based on curvature and gray scale compounding | |
| CN109003258B (en) | High-precision sub-pixel circular part measuring method | |
| CN105334219B (en) | A kind of bottle mouth defect detection method of residual analysis dynamic threshold segmentation | |
| CN109060836B (en) | Machine vision-based high-pressure oil pipe joint external thread detection method | |
| CN102799867B (en) | Meter pointer angle identification method based on image processing | |
| CN103345755B (en) | A kind of Chessboard angular point sub-pixel extraction based on Harris operator | |
| CN100547351C (en) | A kind of machine vision localization method | |
| CN102496161B (en) | Method for extracting contour of image of printed circuit board (PCB) | |
| CN111080582B (en) | Method for detecting defects of inner and outer surfaces of workpiece | |
| CN103292701A (en) | Machine-vision-based online dimensional measurement method of precise instrument | |
| AU2016385541A1 (en) | Object surface deformation feature extraction method based on line scanning three-dimensional point Cloud | |
| CN107564006B (en) | Circular target detection method utilizing Hough transformation | |
| CN106643549A (en) | Machine vision-based tile size detection method | |
| Zhou et al. | Chisel edge wear measurement of high-speed steel twist drills based on machine vision | |
| CN110211178B (en) | Pointer instrument identification method using projection calculation | |
| CN111047588A (en) | Imaging measurement method for size of shaft type small part | |
| CN108447070A (en) | A kind of industrial part defect detection algorithm based on pixel vectors invariant relation feature | |
| CN113237889A (en) | Multi-scale ceramic detection method and system | |
| CN104715491A (en) | Subpixel edge detection method based on one-dimensional gray moment | |
| CN112529869B (en) | Valve sleeve throttling square hole detection method | |
| CN111027530A (en) | Preprocessing method based on tire embossed character recognition | |
| CN103258218B (en) | Masking-out detects skeleton generating method, device, defect inspection method and device | |
| CN113222955A (en) | Gear size parameter automatic measurement method based on machine vision | |
| CN104574417A (en) | Image edge grey level fluctuation measurement and adaptive detection method | |
| CN113393447B (en) | Needle tip true position detection method and system based on deep learning |
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 |