CN110617776A - Non-contact micron-sized vision measuring device and working method thereof - Google Patents
Non-contact micron-sized vision measuring device and working method thereof Download PDFInfo
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- 238000004364 calculation method Methods 0.000 claims description 3
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- 238000005259 measurement Methods 0.000 abstract description 25
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- 238000003754 machining Methods 0.000 description 4
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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
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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
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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Abstract
A non-contact micron-sized vision measuring device and a working method thereof belong to the application field of vision measurement and mainly solve the problem that the elastic resilience of a processing surface in the processing process of a measurement sample is high, and because the cost of the traditional micron-sized measurement mode is high, the non-contact vision measuring device is designed, and an industrial eyepiece, a display device and an industrial camera are arranged by utilizing a base, so that the experiment cost is reduced; in the actual processing process, the temperature around the processed workpiece is higher, the installation requirement on the sensor is higher, the measurement precision of the sensor can be influenced, the device can realize remote measurement, the universality of the measuring device is greatly improved, and the measurement precision is ensured.
Description
Technical Field
The invention relates to a device for measuring elastic resilience of a workpiece in a machining process, which mainly solves the problem of measurement precision in high-temperature and high-speed states; the device is suitable for various materials, is not limited by the geometric shape of a sample, is convenient to integrate with various testing devices, improves the micron-scale measuring efficiency, and belongs to the technical field of measuring devices.
Background
The current micron-scale measuring device mainly utilizes a non-contact sensor (capacitor and laser) to detect a workpiece, and the device has high installation requirement and high cost. For micron-sized rebound measurement in the machining process, the influence on the detection result is huge under a high-temperature state, the measurement precision cannot meet the requirement, and the service life of the sensor is influenced. How to keep the detection precision and improve the economy and universality of the detection device is the target to be achieved by the invention.
Chinese patent document (application No. 201310491644.0) discloses a laser prestress forming clamp with loading and springback measurement, and the core of a measuring device of the laser prestress forming clamp is a dial indicator, so that the laser prestress forming clamp is poor in real-time performance, few in application scenes and low in measurement precision. The Chinese patent document (application number 200810106376.5) is a multi-parameter adjustable bending grinding tool with rebound measurement, the measurement core of the tool is the application of a photoelectric length measuring instrument, the cost is extremely high, and the tool is a universal contact measuring instrument and is not suitable for measurement in a dynamic processing process.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a non-contact micron-scale vision measurement device based on the rebound of the surface of a machined workpiece.
The invention also provides a working method of the device.
The technical scheme of the invention is as follows:
the utility model provides a non-contact micron order vision measuring device, includes the base, and the base is rectangular frame, is equipped with the industry eyepiece on the base, and the industry eyepiece is connected with display device, and display device is used for showing the image that industry eyepiece gathered, and display device symmetry one side is equipped with the industry camera, and the industry camera is used for gathering display device's image.
Preferably, the industrial eyepiece is fixedly connected with the base through a clamping device.
Preferably, the industrial eyepiece is connected with the display device through a USB interface.
Preferably, a movable guide rail is arranged on the base, a connecting platform is connected to the movable guide rail, and the industrial camera is connected with the base through the connecting platform.
Further preferably, the number of the connecting platforms on the moving guide rail is two, and the two connecting platforms are respectively connected with the industrial camera.
The device can be used for completing measurement in a high-speed machining process; the method is not influenced by the geometric shape of the sample in the measurement, and can be suitable for deformation measurement of various materials; the portable and flexible test device can be integrated with various test equipment, and the utilization rate of the device is improved.
A working method using the non-contact micron-sized vision measuring device comprises the following steps:
the device is arranged on one side of a processing device and is not in contact with the processing device to be measured, and a display device displays each deformation stage of an object through an industrial eyepiece;
the industrial camera collects digital images of the object at all deformation stages, the digital image algorithm is utilized to match deformation points on the surface of the object, coordinates of the matching points are reconstructed, and then the resilience amount of the object is calculated according to displacement differences of different time points.
Preferably, the digital image algorithm is a gray gradient algorithm, and in practical situations, displacement and deformation of the structure surface generally occur on sub-pixels, so that by using the sub-pixel displacement measurement algorithm, since the sub-region of the image to be measured is small and small in displacement. A gray gradient algorithm (sub-pixel correlation function extremum algorithm) is selected. The basic idea is as follows: setting f, g to represent the sub-area images before and after deformation respectively, the sub-area can be approximately regarded as rigid motion, setting f (x, y), g (x ', y') to represent the gray values of the corresponding points of the sample sub-area before deformation and the target sub-area after deformation respectively, wherein x 'is x + u + delta x, y' is y + v + delta y,
u and v are integer pixel displacement of the whole sub-area along two directions of the coordinate system, and are obtained by an integer pixel search algorithm:
at coordinate point P (x)0,y0) A region of (2M +1) × (2M +1) pixels is selected for the center, and is defined as a sample sub-region, and the position corresponding to the sub-region found after the deformation is the target sub-region, as shown in fig. 2 and 3. The general formula of the displacement mapping function is:yi′＝yi+ω(xi,yj) Sit onWhen the punctuation point P moves to P', the displacement amounts on x and y are u and v respectively, and as the object makes rigid translation motion, namely the displacement amount of each point on the image is the same, the displacement amounts are expressed by a zeroth order mapping function, namely:ω(xi,yj) V, where (i, j-M: M), M is the pixel value of the sample sub-region;
the pair g (x ', y ') is expanded at the integer pixel displacement point by Taylor's formula, keeping only the first order term. Namely:
g(xi′,yj′)＝g(xi+u,yj+v)+Δu.gx(xi+u,yj+v)+Δv.gy(xi+u,yj+v)；
wherein g isxAnd gyIs the first order partial derivative at the integer pixel displacement point, and the calculation formula is as follows:
and obtaining delta x and delta y from g (x ', y') after deformation and f (x, y) before deformation, wherein the delta x and the delta y are sub-pixel displacement amounts, namely rebound resilience amounts. Namely the rebound amount of the target area in the designated time period.
Whole device and measurand thing non-contact, the base is built by the section bar, can install under different experimental scenes, and the commonality is strong.
The invention has the beneficial effects that:
the method is non-contact vision measurement, is not influenced by a processing environment, reduces the influence of temperature on measurement, and ensures the measurement precision; the device is suitable for measuring samples of various materials and shapes, and the economy is greatly improved; and simple structure, portability, flexibility and convenient installation.
The method adopts a digital image correlation method, combines an industrial close-range shooting technology, adopts an industrial camera to collect digital images of all deformation stages of an object in real time, matches deformation points on the surface of the object by using a digital image correlation algorithm, and reconstructs coordinates of matching points. And smoothing the displacement field data and performing visual analysis on strain information, thereby realizing rapid, high-precision, real-time and non-contact full-field deformation measurement.
Drawings
FIG. 1 is a schematic diagram of the construction of a non-contact, micrometer-scale vision measuring device of the present application;
FIG. 2 is a pre-distorted image of a schematic of a digital image method of the present application;
FIG. 3 is a deformed image of a schematic diagram of a digital image method of the present application;
in the figure, 1, a base, 2, a display device, 3, a clamping device, 4, an industrial eyepiece, 5, a movable camera platform, 6 and an industrial camera.
Detailed Description
The present invention will be further described by way of examples, but not limited thereto, with reference to the accompanying drawings.
Example 1:
a non-contact micron-sized vision measuring device is shown in figure 1 and comprises a base, wherein the base is a rectangular frame and is built by section bars, and the size of the section bars can be adjusted according to the height of a machining workbench so as to facilitate measurement. Be equipped with the industry eyepiece on the base, the industry eyepiece is connected with display device, and display device is used for showing the image that industry eyepiece gathered, and display device symmetry one side is equipped with the industry camera, and the industry camera is used for gathering display device's image. The industrial ocular is fixedly connected with the base through the clamping device. The industrial eyepiece is connected with the display equipment through the USB interface, so that the amplified image is displayed on the display equipment. Be equipped with the movable guide on the base, be connected with connection platform on the movable guide, the industry camera passes through connection platform and links to each other with the base, is convenient for adjust suitable position in order to gather the image after enlargeing.
Example 2:
a non-contact micro-scale vision measuring device, which is constructed as described in embodiment 1, except that there are two connecting platforms on the moving guide rail, and the two connecting platforms are respectively connected to the industrial cameras.
Example 3:
a method of operation using the non-contact, micrometer-scale vision measuring device of embodiment 1, comprising the steps of:
the device is arranged on one side of the processing equipment and is not in contact with the processing equipment to be measured, and the display equipment displays each deformation stage of the object through the industrial eyepiece.
The industrial camera collects digital images of the object at all deformation stages, the digital image algorithm is utilized to match deformation points on the surface of the object, coordinates of the matching points are reconstructed, and then the resilience amount of the object is calculated according to displacement differences of different time points.
The digital image algorithm is a gray gradient algorithm, and because the displacement and the deformation of the structure surface usually occur on sub-pixels in actual conditions, the sub-pixel displacement measurement algorithm is utilized, and because the sub-region of the measured image is small and small displacement is performed. A gray gradient algorithm (sub-pixel correlation function extremum algorithm) is selected. The basic idea is as follows: setting f, g to represent the sub-area images before and after deformation respectively, the sub-area can be approximately regarded as rigid motion, setting f (x, y), g (x ', y') to represent the gray values of the corresponding points of the sample sub-area before deformation and the target sub-area after deformation respectively, wherein x 'is x + u + delta x, y' is y + v + delta y,
u and v are integer pixel displacement of the whole sub-area along two directions of the coordinate system, and are obtained by an integer pixel search algorithm:
at coordinate point P (x)0,y0) A region of (2M +1) × (2M +1) pixels is selected for the center, and is defined as a sample sub-region, the position corresponding to the sub-region found after the deformation is a target sub-region, as shown in fig. 2 and 3, point P, Q in fig. 2 and 3 is an exemplary coordinate point, and the general formula of the displacement mapping function is:yi′＝yi+ω(xi,yj) When the coordinate point P moves to P', the displacement amounts on x and y are u and v, respectively, and since the object makes rigid translation motion, that is, the displacement amount of each point on the image is the same, the displacement amount is expressed by a zeroth-order mapping function, that is:ω(xi,yj) V, where (i, j-M: M), M is the pixel value of the sample sub-region;
the pair g (x ', y ') is expanded at the integer pixel displacement point by Taylor's formula, keeping only the first order term. Namely:
g(xi′,yj′)＝g(xi+u,yj+v)+Δu.gx(xi+u,yj+v)+Δv.gy(xi+u,yj+v)；
wherein g isxAnd gyIs the first order partial derivative at the integer pixel displacement point, and the calculation formula is as follows:
and obtaining delta x and delta y by the g (x ', y') after deformation and the f (x, y) before deformation, wherein the delta x and the delta y are sub-pixel displacement quantities, namely rebound quantities of the target area in a specified time period.
Claims (7)
1. The utility model provides a non-contact micron order vision measuring device, its characterized in that, includes the base, and the base is rectangular frame, is equipped with the industry eyepiece on the base, and the industry eyepiece is connected with display device, and display device is used for showing the image that industry eyepiece gathered, and display device symmetry one side is equipped with the industry camera, and the industry camera is used for gathering display device's image.
2. The non-contact, micrometer-scale vision measuring device of claim 1, wherein the industrial eyepiece is fixedly attached to the base by a clamping device.
3. The non-contact micron-scale vision measuring device of claim 1, wherein the industrial eyepiece is connected to the display device through a USB interface.
4. The non-contact micron-sized vision measuring device according to claim 1, wherein the base is provided with a moving guide rail, the moving guide rail is connected with a connecting platform, and the industrial camera is connected with the base through the connecting platform.
5. The non-contact micron-sized vision measuring device according to claim 4, wherein the number of the connecting platforms on the moving guide rail is two, and the two connecting platforms are respectively connected with the industrial camera.
6. A method of operation using the non-contact, micrometer-scale visual measuring device of any one of claims 1-5, comprising the steps of:
the device is arranged on one side of a processing device and is not in contact with the processing device to be measured, and a display device displays each deformation stage of an object through an industrial eyepiece;
the industrial camera collects digital images of the object at all deformation stages, the digital image algorithm is utilized to match deformation points on the surface of the object, coordinates of the matching points are reconstructed, and then the resilience amount of the object is calculated according to displacement differences of different time points.
7. The method of claim 6, wherein the digital image algorithm is a gray scale gradient algorithm, f and g are set to represent the sub-region images before and after deformation, respectively, the sub-regions are approximately regarded as rigid motion, f (x, y) and g (x ', y') are set to represent the gray scale values of the corresponding points of the sample sub-region before deformation and the target sub-region after deformation, respectively, x '═ x + u + Δ x, y' ═ y + v + Δ y,
u and v are integer pixel displacement of the whole sub-area along two directions of the coordinate system, and are obtained by an integer pixel search algorithm:
at coordinate point P (x)0,y0) Selecting a region of (2M +1) × (2M +1) pixels for the center, defining the region as a sample sub-region, and finding the position corresponding to the sub-region after deformation as a target sub-region, wherein the general formula of the displacement mapping function is as follows:yi′＝yi+ω(xi,yj) When the coordinate point P moves to P', the displacement amounts on x and y are u and v, respectively, and since the object makes rigid translation motion, that is, the displacement amount of each point on the image is the same, the displacement amount is expressed by a zeroth-order mapping function, that is:ω(xi,yj) V, where (i, j-M: M), M is the pixel value of the sample sub-region;
for g (x ', y ') expanded by Taylor's formula at the integer pixel displacement point, only the first order term is retained, i.e.:
g(xi′,yj′)＝g(xi+u,yj+v)+Δu.gx(xi+u,yj+v)+Δv.gy(xi+u,yj+v)；
wherein g isxAnd gyIs the first order partial derivative at the integer pixel displacement point, and the calculation formula is as follows:
and obtaining delta x and delta y by the g (x ', y') after deformation and the f (x, y) before deformation, wherein the delta x and the delta y are sub-pixel displacement quantities, namely rebound quantities of the target area in a specified time period.
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