CN113375569A - Oil film thickness analysis device and method based on image recognition - Google Patents
Oil film thickness analysis device and method based on image recognition Download PDFInfo
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- CN113375569A CN113375569A CN202110541399.4A CN202110541399A CN113375569A CN 113375569 A CN113375569 A CN 113375569A CN 202110541399 A CN202110541399 A CN 202110541399A CN 113375569 A CN113375569 A CN 113375569A
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- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000004458 analytical method Methods 0.000 title claims abstract description 18
- 239000011521 glass Substances 0.000 claims abstract description 22
- 230000007246 mechanism Effects 0.000 claims abstract description 8
- 238000012545 processing Methods 0.000 claims abstract description 8
- 239000003921 oil Substances 0.000 claims description 60
- 238000012360 testing method Methods 0.000 claims description 20
- 238000007781 pre-processing Methods 0.000 claims description 15
- 238000001914 filtration Methods 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 8
- 239000010687 lubricating oil Substances 0.000 claims description 8
- 229910000831 Steel Inorganic materials 0.000 claims description 7
- 238000003709 image segmentation Methods 0.000 claims description 7
- 239000010959 steel Substances 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 230000001427 coherent effect Effects 0.000 claims description 6
- 238000003708 edge detection Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 239000011248 coating agent Substances 0.000 claims description 3
- 238000000576 coating method Methods 0.000 claims description 3
- 239000003086 colorant Substances 0.000 claims description 3
- 230000001678 irradiating effect Effects 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 9
- 239000010408 film Substances 0.000 description 66
- 238000010586 diagram Methods 0.000 description 8
- 238000005461 lubrication Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000007561 laser diffraction method Methods 0.000 description 1
- 230000001050 lubricating effect Effects 0.000 description 1
- 230000009347 mechanical transmission Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000012788 optical film Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
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- 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
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0616—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material of coating
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- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses an oil film thickness analysis device and method based on image recognition, which comprises a glass disc, wherein an oil film generation mechanism is arranged on the lower surface of the glass disc; the upper surface of the glass disc is provided with a microscope, the end of the microscope eye is provided with a CCD image sensor, and the CCD image sensor is connected with a data processing terminal; the oil film thickness is measured by an image recognition technology, an interference image is received and converted into an electric signal by an image microscope and a CCD image sensor, the electric signal is processed by software compiled by a computer, and finally the actual oil film thickness is obtained by looking up a table, so that the oil film thickness can be accurately measured; the device has solved the lower problem of prior art measurement oil film thickness precision, has the higher characteristics of measurement accuracy.
Description
Technical Field
The invention belongs to the technical field of oil film thickness detection, and particularly relates to an oil film thickness analysis device and method based on image recognition.
Background
In order to improve the lubrication reliability of a mechanical transmission system, the thickness of an oil film between interfaces needs to be measured, and the research on the lubrication performance is very important. Under the elastohydrodynamic lubrication state, the lubricating oil is often in special conditions of high pressure, high temperature, greasy dirt and the like and plays an important role in reducing the abrasion of various parts. Therefore, the thickness of the lubricating oil film reflects the lubricating performance of various parts to a great extent, and accurate measurement of the oil film thickness is necessary to determine whether the parts are in a good running state.
At present, there are various methods for monitoring the thickness of an oil film, such as a resistance method, a discharge voltage method, a capacitance method, an X-ray transmission method, a laser diffraction method, an interference method, and the like. However, these methods have limitations, and for various reasons, a mature method for effectively detecting the dynamic change information of the oil film thickness of the sliding bearing has not been found so far. With the continuous development of computer technology, the image recognition technology provides a new method for realizing the accurate measurement of the oil film thickness, namely, the distribution and the shape of the oil film thickness in a contact area are reflected through the light intensity and the color of an interference image.
Disclosure of Invention
The invention aims to solve the technical problem of providing an oil film thickness analysis device and method based on image recognition, which solve the problem of low precision of oil film thickness measurement in the prior art and have the characteristic of high measurement precision.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
an oil film thickness analysis device based on image recognition comprises a glass disc, wherein an oil film generation mechanism is arranged on the lower surface of the glass disc; the upper surface of the glass disc is provided with a microscope, the end of the microscope eye is provided with a CCD image sensor, and the CCD image sensor is connected with the data processing terminal.
Preferably, the oil film generating mechanism comprises a Cr film evaporated on the surface of the glass disc, and SiO is evaporated on the surface of the Cr film2An insulating film; the lower surface of the glass disc is provided with an ultra-fine steel ball which is matched with the coating film to form a lubricating oil film.
Preferably, the method for analyzing the oil film thickness based on image recognition includes the following steps:
s1, irradiating the Cr film on the upper surface of the glass disc with a light beam, and forming two beams of light by refraction and reflection, wherein the reflected light is directly reflected from the upper surface of the Cr film, the refracted light passes through the Cr film and the lubricating oil film to reach the steel ball and is reflected again, and the two beams of reflected light are reflected and interfered to form coherent light;
s2, the coherent light is received by the microscope and the CCD image sensor and converted into an electric signal, and the electric signal is sent to a computer for image preprocessing; carrying out image segmentation after image preprocessing to obtain an interference image, and sending the interference image into an oil film thickness calibration program for processing to obtain the corresponding relation between the position coordinates of pixels in each fringe on the interference image and the oil film thickness and color;
s3, carrying out image recognition on the color test image after image preprocessing to obtain coordinates and color data corresponding to each pixel point of the image;
and S4, converting the relation between the size of the test image and the size of the interference image to realize the unification of the coordinate values, and acquiring the color value and the coordinate value of any point on the test image to obtain the oil film thickness value of the point.
Preferably, in the method for analyzing oil film thickness based on image recognition, the image preprocessing in S2 includes image enhancement, image restoration, and feature extraction, and the specific method includes:
s101, image enhancement: the image is regarded as a two-dimensional signal, signal enhancement based on two-dimensional Fourier transform is carried out on the two-dimensional signal, and then noise in the image is removed by adopting a low-pass filtering method;
s102, image restoration: in the image enhancement process, the image quality is degraded, wiener filtering is carried out on the degraded image, and the original content and quality are restored;
s103, feature detection: and carrying out positioning analysis on the stripes in the image, and extracting pixel positions corresponding to the stripes in the image.
Preferably, in the method for analyzing oil film thickness based on image recognition, the method for segmenting the image in S2 is as follows:
s201, threshold segmentation: dividing the pixel set according to the gray level to enable each region to have consistent attributes;
s202, edge detection: the method comprises the steps of firstly carrying out smooth filtering on a binary image to eliminate noise to obtain a smooth image, then carrying out sharpening filtering on the smooth image to obtain a sharpened image, carrying out edge judgment on the sharpened image to obtain the binary image again, and finally carrying out edge connection on the binary image to obtain a required edge image.
Preferably, in the method for oil film thickness analysis based on image recognition, the oil film thickness calibration procedure in S2 includes the following steps:
s301, calibrating the circle center position of an image by using a rough transformation detection circle for an interference image obtained after image preprocessing and image segmentation, establishing a coordinate system by taking the circle center as a coordinate origin after calibrating the circle center position, and determining the relationship of each pixel and the conversion relationship between the pixel coordinate and an actual space coordinate;
s302, determining the level number of interference fringes where the position coordinates of each pixel point are located, and obtaining a database of corresponding relations among the interference fringe coordinates, corresponding colors and space position heights through table data.
Preferably, in the method for analyzing oil film thickness based on image recognition, the method for image recognition in S3 is as follows:
s401, identifying the pixel position of each point in the test image, and performing relation conversion on the test image and the actual size of the oil film shape;
s402, dividing the test image into grids to obtain RGB color data and coordinate values corresponding to each point on the grids, and comparing the coordinate values with the database in S302 to obtain oil film thickness data of corresponding positions.
The invention has the beneficial effects that:
the method measures the oil film thickness by using an image recognition technology, receives and converts an interference image into an electric signal through an image microscope and a CCD image sensor, processes the electric signal through software compiled by a computer, finally obtains the actual oil film thickness through table lookup, and can realize the accurate measurement of the oil film thickness; compared with the prior art, the method has the characteristic of high measurement precision, and can realize effective detection on the dynamic change information of the oil film thickness of the sliding bearing.
Drawings
FIG. 1 is a schematic diagram of the system connection of the present invention;
FIG. 2 is a schematic diagram of an image processing flow according to the present invention;
FIG. 3 is a schematic diagram of an edge detection step according to the present invention;
FIG. 4 is a schematic diagram of interference image boundary extraction in the present invention;
FIG. 5 is a schematic diagram of a gridding of a test image in accordance with the present invention;
FIG. 6 is a logic diagram of a procedure for oil film thickness calibration in accordance with the present invention;
FIG. 7 is a diagram illustrating the effect of software execution according to an embodiment of the present invention;
FIG. 8 is a diagram B illustrating the effect of software execution according to an embodiment of the present invention;
FIG. 9 is a software interface in an embodiment of the invention;
in the figure: the device comprises a glass disc 1, an oil film generating mechanism 2, a microscope 3 and a super-fine steel ball 4.
Detailed Description
Example 1:
an oil film thickness analysis device based on image recognition comprises a glass disc, wherein an oil film generation mechanism is arranged on the lower surface of the glass disc; the upper surface of the glass disc is provided with a microscope, the end of the microscope eye is provided with a CCD image sensor, and the CCD image sensor is connected with the data processing terminal.
Preferably, the oil film generating mechanism comprises a Cr film evaporated on the surface of the glass disc, and SiO is evaporated on the surface of the Cr film2An insulating film; the lower surface of the glass disc is provided with an ultra-fine steel ball which is matched with the coating film to form a lubricating oil film.
Example 2:
preferably, the method for analyzing the oil film thickness based on image recognition includes the following steps:
s1, irradiating the Cr film on the upper surface of the glass disc with a light beam, and forming two beams of light by refraction and reflection, wherein the reflected light is directly reflected from the upper surface of the Cr film, the refracted light passes through the Cr film and the lubricating oil film to reach the steel ball and is reflected again, and the two beams of reflected light are reflected and interfered to form coherent light;
s2, the coherent light is received by the microscope and the CCD image sensor and converted into an electric signal, and the electric signal is sent to a computer for image preprocessing; carrying out image segmentation after image preprocessing to obtain an interference image, and sending the interference image into an oil film thickness calibration program for processing to obtain the corresponding relation between the position coordinates of pixels in each fringe on the interference image and the oil film thickness and color;
s3, carrying out image recognition on the color test image after image preprocessing to obtain coordinates and color data corresponding to each pixel point of the image;
and S4, converting the relation between the size of the test image and the size of the interference image to realize the unification of the coordinate values, and acquiring the color value and the coordinate value of any point on the test image to obtain the oil film thickness value of the point.
Preferably, in the method for analyzing oil film thickness based on image recognition, the image preprocessing in S2 includes image enhancement, image restoration, and feature extraction, and the specific method includes:
s101, image enhancement: the image is regarded as a two-dimensional signal, signal enhancement based on two-dimensional Fourier transform is carried out on the two-dimensional signal, and then noise in the image is removed by adopting a low-pass filtering method;
s102, image restoration: in the image enhancement process, the image quality is degraded, wiener filtering is carried out on the degraded image, and the original content and quality are restored;
s103, feature detection: and carrying out positioning analysis on the stripes in the image, and extracting pixel positions corresponding to the stripes in the image.
Preferably, in the method for analyzing oil film thickness based on image recognition, the method for segmenting the image in S2 is as follows:
s201, threshold segmentation: dividing the pixel set according to the gray level to enable each region to have consistent attributes;
s202, edge detection: the method comprises the steps of firstly carrying out smooth filtering on a binary image to eliminate noise to obtain a smooth image, then carrying out sharpening filtering on the smooth image to obtain a sharpened image, carrying out edge judgment on the sharpened image to obtain the binary image again, and finally carrying out edge connection on the binary image to obtain a required edge image.
Preferably, in the method for oil film thickness analysis based on image recognition, the oil film thickness calibration procedure in S2 includes the following steps:
s301, calibrating the circle center position of an image by using a rough transformation detection circle for an interference image obtained after image preprocessing and image segmentation, establishing a coordinate system by taking the circle center as a coordinate origin after calibrating the circle center position, and determining the relationship of each pixel and the conversion relationship between the pixel coordinate and an actual space coordinate;
s302, determining the level number of interference fringes where the position coordinates of each pixel point are located, and obtaining a database of corresponding relations among the interference fringe coordinates, corresponding colors and space position heights through table data.
Further, the tabular data are as follows in table 1; taking the data obtained from the D.Zhu study as an example, if the 8 th level of a plurality of interference fringes is red light, the corresponding film thickness is 2.287 microns.
Actual Film Thickness＝Optical Film Thickness/Refractive Index
TABLE 1
Preferably, in the method for analyzing oil film thickness based on image recognition, the method for image recognition in S3 is as follows:
s401, identifying the pixel position of each point in the test image, and performing relation conversion on the test image and the actual size of the oil film shape;
s402, dividing the test image into grids to obtain RGB color data and coordinate values corresponding to each point on the grids, and comparing the coordinate values with the database in S302 to obtain oil film thickness data of corresponding positions.
Through tests, the measurement accuracy of the relative light intensity method can reach the resolution of 0.167nm in the vertical direction and the resolution of 0.33 mu m in the horizontal direction.
The above-described embodiments are merely preferred embodiments of the present invention, and should not be construed as limiting the present invention, and features in the embodiments and examples in the present application may be arbitrarily combined with each other without conflict. The protection scope of the present invention is defined by the claims, and includes equivalents of technical features of the claims. I.e., equivalent alterations and modifications within the scope hereof, are also intended to be within the scope of the invention.
Claims (7)
1. The utility model provides an oil film thickness analytical equipment based on image recognition which characterized in that: comprises a glass disc (1), wherein an oil film generating mechanism (2) is arranged on the lower surface of the glass disc (1); the upper surface of the glass plate (1) is provided with a microscope (3), the eyepiece end of the microscope (3) is provided with a CCD image sensor, and the CCD image sensor is connected with a data processing terminal.
2. The oil film thickness analysis device based on image recognition as claimed in claim 1, wherein: the oil film generating mechanism (2) comprises a Cr film evaporated on the surface of the glass disc (1), and SiO is evaporated on the surface of the Cr film2An insulating film; the lower surface of the glass disc (1) is provided with an ultra-precision steel ball (4) which is matched with the coating film to form a lubricating oil film.
3. The method for oil film thickness analysis based on image recognition is characterized by comprising the following steps: the method comprises the following steps:
s1, irradiating the Cr film on the upper surface of the glass disc (1) with a light beam, forming two beams of light by refraction and reflection, wherein the reflected light is directly reflected from the upper surface of the Cr film, the refracted light passes through the Cr film and a lubricating oil film to reach the steel ball and is reflected again, and the two beams of reflected light are reflected and interfered to form coherent light;
s2, the coherent light is received by the microscope (3) and the CCD image sensor and converted into an electric signal, and the electric signal is sent to a computer for image preprocessing; carrying out image segmentation after image preprocessing to obtain an interference image, and sending the interference image into an oil film thickness calibration program for processing to obtain the corresponding relation between the position coordinates of pixels in each fringe on the interference image and the oil film thickness and color;
s3, carrying out image recognition on the color test image after image preprocessing to obtain coordinates and color data corresponding to each pixel point of the image;
and S4, converting the relation between the size of the test image and the size of the interference image to realize the unification of the coordinate values, and acquiring the color value and the coordinate value of any point on the test image to obtain the oil film thickness value of the point.
4. The method for oil film thickness analysis based on image recognition as claimed in claim 3, wherein: the image preprocessing in S2 includes image enhancement, image restoration, and feature extraction, and the specific method is as follows:
s101, image enhancement: the image is regarded as a two-dimensional signal, signal enhancement based on two-dimensional Fourier transform is carried out on the two-dimensional signal, and then noise in the image is removed by adopting a low-pass filtering method;
s102, image restoration: in the image enhancement process, the image quality is degraded, wiener filtering is carried out on the degraded image, and the original content and quality are restored;
s103, feature detection: and carrying out positioning analysis on the stripes in the image, and extracting pixel positions corresponding to the stripes in the image.
5. The method for oil film thickness analysis based on image recognition as claimed in claim 3, wherein: the method for image segmentation in S2 is as follows:
s201, threshold segmentation: dividing the pixel set according to the gray level to enable each region to have consistent attributes;
s202, edge detection: the method comprises the steps of firstly carrying out smooth filtering on a binary image to eliminate noise to obtain a smooth image, then carrying out sharpening filtering on the smooth image to obtain a sharpened image, carrying out edge judgment on the sharpened image to obtain the binary image again, and finally carrying out edge connection on the binary image to obtain a required edge image.
6. The method for oil film thickness analysis based on image recognition as claimed in claim 3, wherein: the oil film thickness calibration program in S2 includes the following steps:
s301, calibrating the circle center position of an image by using a rough transformation detection circle for an interference image obtained after image preprocessing and image segmentation, establishing a coordinate system by taking the circle center as a coordinate origin after calibrating the circle center position, and determining the relationship of each pixel and the conversion relationship between the pixel coordinate and an actual space coordinate;
s302, determining the level number of interference fringes where the position coordinates of each pixel point are located, and obtaining a database of corresponding relations among the interference fringe coordinates, corresponding colors and space position heights through table data.
7. The method for oil film thickness analysis based on image recognition as claimed in claim 3, wherein: the method of image recognition in S3 is as follows:
s401, identifying the pixel position of each point in the test image, and performing relation conversion on the test image and the actual size of the oil film shape;
and S402, dividing the test image into grids to obtain RGB color data and coordinate values corresponding to each point on the grids, and comparing the coordinate values with the database of S302 to obtain oil film thickness data of corresponding positions.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116557384A (en) * | 2023-07-07 | 2023-08-08 | 江苏洲帆机电设备有限公司 | Automatic pressure compensation method for hydraulic control system |
| CN117843187A (en) * | 2024-01-26 | 2024-04-09 | 中国电建集团北京勘测设计研究院有限公司 | Full-automatic mechanical repair wastewater treatment device and method for hydraulic and hydroelectric engineering |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104154870A (en) * | 2014-08-28 | 2014-11-19 | 青岛理工大学 | Method for measuring thickness of lubricating oil film by two-color light interference |
| JP2017207316A (en) * | 2016-05-17 | 2017-11-24 | 株式会社ジェイテクト | Oil film thickness measuring device and measuring method |
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- 2021-05-18 CN CN202110541399.4A patent/CN113375569A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104154870A (en) * | 2014-08-28 | 2014-11-19 | 青岛理工大学 | Method for measuring thickness of lubricating oil film by two-color light interference |
| JP2017207316A (en) * | 2016-05-17 | 2017-11-24 | 株式会社ジェイテクト | Oil film thickness measuring device and measuring method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116557384A (en) * | 2023-07-07 | 2023-08-08 | 江苏洲帆机电设备有限公司 | Automatic pressure compensation method for hydraulic control system |
| CN116557384B (en) * | 2023-07-07 | 2023-09-29 | 江苏洲帆机电设备有限公司 | Automatic pressure compensation method for hydraulic control system |
| CN117843187A (en) * | 2024-01-26 | 2024-04-09 | 中国电建集团北京勘测设计研究院有限公司 | Full-automatic mechanical repair wastewater treatment device and method for hydraulic and hydroelectric engineering |
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