CN209148564U - A kind of transparent component defect detecting device - Google Patents
A kind of transparent component defect detecting device Download PDFInfo
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- CN209148564U CN209148564U CN201821738996.6U CN201821738996U CN209148564U CN 209148564 U CN209148564 U CN 209148564U CN 201821738996 U CN201821738996 U CN 201821738996U CN 209148564 U CN209148564 U CN 209148564U
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Abstract
The utility model discloses a kind of transparent component defect detecting devices, described device includes positioning drive unit, laser emitter, light transmission workbench, detection video camera, deep learning arithmetic element, ARM embedded controller and combined aural and visual alarm, laser emitter is connect with positioning drive unit, by CAN bus and ARM embedded controller communication connection, detection video camera shoots against light transmission working machine and obtains image for positioning drive unit, detection video camera, deep learning arithmetic element and acoustic-optic alarm.The utility model detection performance is stablized, and detects quality and detection efficiency is higher.
Description
Technical field
The utility model belongs to surface defects of products detection technique field, and specifically a kind of 3C industry transparent component produces
Quality defect detecting device and method.
Background technique
China is 3C Product manufacture big country, and the application of transparent component in the industry is also more and more, and the quality of product
It is required that also higher and higher.But the detection for 3C transparent component defect, it is most of also to rest on by artificial eye identification
In the stage, that there are labor intensity is larger, optical pollution is serious, has injury to the eyesight of testing staff, and due to testing staff's
Experience is inconsistent, and there are the risks of missing inspection.In addition, China's human resources are burst weary, cost is constantly soaring, and there is an urgent need to 3C industries
Detection device intelligentized updating reduces the probability of part defect, yields is improved, to promote the profit of enterprise.
Currently, transparent purchase part defects detection on the market is most of based on artificial, a small amount of detection for having automation is set
It is standby, based on optical detection, by disposable one integral piece product illumination (based on visible light), then with camera collection image, carry out
Defect is analyzed and judges whether there is, but since 3C transparent component size is small, defect is unobvious, to pass through normal optical original
Reason is detected, and recognition accuracy needs to be further improved.Thus, there is an urgent need to a kind of new detection methods, promote letter
It makes an uproar ratio, it is easier to recognize subtle product defects, promote yields for relevant industry and enterprise, reduce cost, to be 3C row
The development of industry is contributed share.
Utility model content
The technical problem to be solved by the present invention is to provide a kind of transparent component defect detecting device, detection performance is steady
It is fixed, it detects quality and detection efficiency is higher.
In order to solve the above-mentioned technical problem, the utility model takes following technical scheme:
A kind of transparent component defect detecting device, described device include positioning drive unit, laser emitter, light transmission work
Platform, detection video camera, deep learning arithmetic element, ARM embedded controller and combined aural and visual alarm, laser emitter and positioning are driven
Dynamic device connection, positioning drive unit, detection video camera, deep learning arithmetic element and acoustic-optic alarm pass through CAN bus
With ARM embedded controller communication connection, video camera is detected against light transmission working machine and shoots acquisition image.
It is additionally provided on the light transmission workbench in the total reflection for clamping transparent component to be measured under auxiliary member and total reflection
Auxiliary member is totally reflected lower auxiliary member and is located on light transmission workbench, and transparent component to be measured is located at the upper auxiliary member of total reflection and total reflection
Between lower auxiliary member, there is exposed gap portion in total reflection between auxiliary member and transparent component to be measured.
The positioning drive unit include microcontroller, X to motor, X to positioning screw rod, Y-direction motor, Y-direction positioning screw rod,
X positions stepper motor to load platform, Y-direction load platform and angle, and X is connected to positioning screw rod and X to motor and mounted in X to negative
On carrying platform, Y-direction load platform is mounted in X on positioning screw rod by swivel nut, and Y-direction positioning screw rod connect with Y-direction motor and mounted in Y
To on load platform, angle positions stepper motor through link block on Y-direction positioning screw rod, and laser emitter and angle position
The driving axis connection of stepper motor, X are connect with microcontroller respectively to motor, Y-direction motor, angle positioning stepper motor, micro-control
Device processed passes through CAN bus and ARM embedded controller communication connection, is connected with grating scale on microcontroller.
The X further respectively has to one end of load platform, Y-direction load platform and passes with the zero-bit of microcontroller communication connection
Sensor.
Meet laser between auxiliary member three under auxiliary member, transparent component to be detected, total reflection in the total reflection to be all-trans
The requirement penetrated that is to say that the laser light incident angle C for being incident on transparent component to be detected meets
C≥sin-1(n2/n1),
Wherein n2To be totally reflected upper auxiliary member and being totally reflected the refractive index of lower auxiliary member, n1For the refraction of transparent component to be measured
Rate.
The laser emitter is equipped with the laser head of at least three different sizes side by side, for measuring the to be measured of different-thickness
Transparent component.
The detection video camera is located at the lower section of light transmission workbench, and detects video camera periphery equipped with sheet metal shell.
The utility model has the following beneficial effects:
1) it is based on optical total-reflection principle, the strong visible laser of user's tropism examines 3C transparent component to be detected
It surveys, since the defect on inside transparent component or surface can all cause laser generation to reflect, reflect, spread and penetrate, thus fraction of laser light
It is unsatisfactory for total reflection condition, is leaked out from transparent component surface, detected video camera captures, and takes pictures and mention for intellectual analysis below
For basic data.
2) for the transparent purchase machine of the 3C for detecting different-thickness, using the laser head of different specification size, to detect automatically
Detection efficiency can be also taken into account in view of detection quality.
3) total reflection principle and its laser positioning auxiliary device are utilized, the utility model patent can not only detect plane type
3C transparent component, moreover it is possible to the 3C transparent component of curved surface type is detected.
4) the 3C transparent component intelligent testing technology for using deep learning completes transparent component precision, online automatic detection,
The inconsistency of artificial detection is overcome, so that quality is stablized in detection process.
Detailed description of the invention
Attached drawing 1 is the catenation principle schematic diagram of utility model device；
Attached drawing 2 is the structural schematic diagram of the utility model positioning drive unit；
Attached drawing 3 is the catenation principle schematic diagram of the utility model positioning drive unit；
Attached drawing 4 is the structural schematic diagram of the utility model light transmission workbench；
Attached drawing 5-1 is the light path schematic diagram that defect is not present in component to be measured；
Attached drawing 5-2 is the light path schematic diagram of component surface existing defects to be measured；
Attached drawing 5-3 is the light path schematic diagram of component inside existing defects to be measured；
Attached drawing 6-1 is the light path schematic diagram of plane component to be measured；
Attached drawing 6-2 is the refraction of light path schematic diagram of the transparent component to be measured of curved face type；
Attached drawing 7-1, Fig. 7-2, Fig. 7-3 are deep learning schematic network structure；
Attached drawing 8 is detection zone division principle schematic diagram.
Specific embodiment
For the feature, technological means and specific purposes achieved, function that can further appreciate that the utility model, below
The utility model is described in further detail in conjunction with attached drawing and specific embodiment.
As shown in attached drawing 1-4, the utility model discloses a kind of transparent component defect detecting device, and described device includes fixed
Position driving device, laser emitter 1, light transmission workbench 3, detection video camera, deep learning arithmetic element, ARM embedded Control
Device and combined aural and visual alarm, laser emitter are connect with positioning drive unit, positioning drive unit, detection video camera, deep learning
Arithmetic element and acoustic-optic alarm detect video camera against light transmission by CAN bus and ARM embedded controller communication connection
Working machine shooting obtains image.Positioning drive unit positions laser emitter, makes laser emitter in accurate position
Emit laser, it is ensured that laser accurately enters in transparent component to be measured.
Auxiliary member 41 and total reflection in the total reflection for clamping transparent component to be measured are additionally provided on the light transmission workbench 3
Lower auxiliary member 42 is totally reflected lower auxiliary member 41 and is located on light transmission workbench 3, and transparent component 5 to be measured is located at the upper auxiliary member of total reflection
Between 41 and the lower auxiliary member 41 of total reflection, there is exposed gap portion in total reflection between auxiliary member 41 and transparent component to be measured 5.
The material selection flexible wear translucent material of auxiliary member and the lower auxiliary member of total reflection, hardness structure more transparent than 3C to be detected in total reflection
Part is low；It can configure auxiliary member and the lower auxiliary of total reflection in different types of mating total reflection according to the requirement of detection transparent component
Part, to realize all standing of the optical detection to 3C transparent component to be detected.Auxiliary member, transparent structure to be detected in the total reflection
Part is totally reflected the requirement for meeting laser total reflection between lower auxiliary member three, that is to say and is incident on swashing for transparent component to be detected
Angle of light C meets
C≥sin-1(n2/n1),
Wherein n2To be totally reflected upper auxiliary member and being totally reflected the refractive index of lower auxiliary member, n1For the refraction of transparent component to be measured
Rate.
In addition, the positioning drive unit includes microcontroller, X to motor 6, X to positioning screw rod 7, Y-direction motor 11, Y-direction
Positioning screw rod 12, X position stepper motor 2 to load platform 8, Y-direction load platform 9 and angle, and X is to positioning screw rod 7 and X to motor
6 connect and mounted in X on load platform 8, and Y-direction load platform 9 is mounted in X on positioning screw rod 7 by swivel nut, Y-direction positioning screw rod
12 connect with Y-direction motor 11 and are mounted on Y-direction load platform 9, and angle positions stepper motor 2 and positioned by link block mounted in Y-direction
On screw rod 12, the driving axis connection of laser emitter 1 and angle positioning stepper motor 2, X is positioned to motor, Y-direction motor, angle
Stepper motor is connect with microcontroller respectively, and microcontroller passes through CAN bus and ARM embedded controller communication connection, micro-control
Grating scale is connected on device processed, X further respectively has and microcontroller communication connection to one end of load platform, Y-direction load platform
Null pick-up.X drives X to rotate to positioning screw rod to motor, and then the adjustable movement of Y-direction load platform in the X direction
Stroke, so as to adjust laser emitter in the position of X-direction.The position of laser emitter in the Y direction is adjusted by Y-direction motor again
It sets, so as to adjust the position in the direction good X-Y, then stepper motor is positioned by angle and drives laser emitter rotation, adjust angle
Degree, so that laser emitter has been adjusted scheduled position.Grating scale can accurately control operation of the X to motor, Y-direction motor
Stroke.X constitutes a close loop control circuit to motor, Y-direction motor and grating scale, and stepper motor passes through angle null pick-up,
Correction is returned to zero again automatically after the completion of every transparent component to be measured, to realize that high fine positioning provides environment.
X is to suspending after the every minor tick of motor (1/5~1/10 3C transparent component width to be detected) fixed step size, and X is to electricity
In machine motion process, laser emitter persistently emits laser, detects video camera within the time of this detection process in exposure shape
State, after the movement in place of X-direction fixed step size, detection video camera is taken pictures.Angle positions stepper motor in every structure to be detected
Automatically home position is gone back to after the completion of part, is detected by angle null pick-up, is re-calibrated and is mentioned for angle positioning stepper motor
For benchmark；Microcontroller perceives the information for being detected component by CAN bus and ARM embedded controller communication connection, is it
Servo and positioning movement provide parameter.
Angle positioning stepper motor drives laser emitter to be rotated, and the angle of rotation is by ARM embedded controller
It is adjusted according to the dimension information of component to be detected and its position to be detected, enables detection laser full for area to be tested
Sufficient total reflection condition.
The laser emitter sets the laser head there are three different size side by side, for measuring the to be measured transparent of different-thickness
Component.In the present embodiment, laser head 1.5mm × 1.5mm, 3.5mm × 3.5mm and the 6mm × 6mm of three different sizes, point
The other 3C transparent component for being less than 1mm, 1~3mm and 3~5mm to different-thickness specification detects.
ARM embedded controller is carried out according to the dimension information of transparent component to be detected by component length and width direction
Sampling takes pictures by multiple (length samples number × width sampling number) and completes the detection of one integral piece component.
In addition, being sealed outside whole device by sheet metal component, interference of the external light source to testing result is reduced；Into one
Step detects camera placements below light transmission workbench, and a set of sheet metal shell is arranged again in periphery and is sealed, and reduces again
Interference.
The deep learning arithmetic element is realized using FPGA hardware, before incoming, by ARM embedded controller
Gray processing and dividing processing are carried out, by the specification of laser head, each image after segmentation is compressed to 64 × 64 × 1,128 respectively ×
In 128 × 1 or 256 × 256 × 1 three dimensional grey scale image space, then after carrying out cubic convolution and pondization operation, then two are carried out
The secondary neural network connected entirely, is output in 256 dimensional vectors, then is exported 256 dimensional vectors for vector (normally, by soft return
It is defective), and will test result and ARM embedded controller is transferred to by CAN bus communication module, and pass through combined aural and visual alarm
Inform testing staff.
The sample database that the deep learning arithmetic element is relied on is present in ARM embedded controller (internal NAND
Flash), can be by ARM embedded controller background update depth convolutional neural networks parameter, and depth is sent by CAN bus
It stores in study arithmetic element and is used in operation.
The off-line training sample database of the depth convolutional neural networks can increase sample size.Thus, 3C transparent component
Detection can be increased and decreased according to the actual conditions of sample, promote the accuracy in detection of specific standard component to be detected.
The depth convolutional neural networks can be trained in use update by user, also can choose by
Device manufacturer regularly updates；Utility model device supports the depth convolutional neural networks of multi version, can be by end user
It is independently selected according to practical application scene.
The servo motor in the direction X-Y drives positioning screw rod to carry out the movement of X-direction and Y-direction, and load platform is driven to carry out
The direction " X-Y " linkage, angle positioning stepper motor is mounted on load platform, then laser emitter is driven to be rotated, and is passed through
Laser emitter can be navigated to state to be detected, meet testing requirements by three-shaft linkage scheme.In detection process, X-direction is watched
Suspend after taking the every minor tick of motor (1/5~1/10 3C transparent component width to be detected) fixed step size, in the process, laser
Transmitter persistently emits laser, and detection video camera is in exposure status and detects video camera after the movement in place of X-direction fixed step size
It takes pictures；The material of upper auxiliary member is totally reflected by selection, so that refractive index n2For transparent component refractive index n to be detected11/
2 and its hereinafter, to reaching laser light incident angle C less than 45 degree, then it is directed to the thickness of transparent component to be detected, selection corresponding specification
Laser head, Y-direction single pass, which can be realized, to be covered, and specific rules are as follows:
A) the case where being less than 1mm for transparent component thickness to be detected selects 1.5mm by positioning drive unit microcontroller
× 1.5mm laser head works；
B) 1~3mm situation is in for transparent component thickness to be detected, is selected by positioning drive unit microcontroller
3.5mm × 3.5mm laser head works；
C) the case where being in 3~5mm for transparent component thickness to be detected, is selected by positioning drive unit microcontroller
6mm × 6mm laser head works.
D) above-mentioned positioning drive unit microcontroller is by CAN bus, by ARM embedded controller controls, by user's root
It is selected according to actual conditions.
After above-mentioned zone samples the laser head width of the mobile unit of Y-direction, repeats detection once, detect energy twice
Complete area in complete covering fixed step size.Similarly, remaining area to be tested is repeated the above process, is continued in X direction
Scanning Detction can cover entire transparent component region to be measured, complete detection, testing principle is as shown in figure 8, first in Fig. 8
Secondary detection and the detection twice being detected as in this sampling area along Y-direction for the second time.Thus, total number of taking pictures be 2* (5~
10) secondary.
As shown in Fig. 4, detection laser beam passes through positioning drive unit realization pair under ARM embedded controller controls
The position of detection laser beam adjusts, so that meeting fully reflective principle；Auxiliary member is stayed with 3C transparent component to be detected in total reflection
There is gap, usually 1.2~1.5 times of beam width, laser beam is injected inside transparent component to be detected；It is all-trans
It penetrates below lower auxiliary member and is provided with detection video camera, to there may be the light leakage of (defective detection is shown in there is light leakage phenomena) progress
It takes pictures.
As shown in attached drawing 5-1, for 3C transparent component to be detected, if internal or surface does not have defect, detection swashs
Light beam meets total reflection working principle, laser total reflection up and down inside transparent component, without assisting in the total reflection of laser directive
Part descends auxiliary member with total reflection, so that the detection video camera being arranged under total reflection below auxiliary member cannot obtain detection
Laser signal.On the contrary, such as attached drawing 5-2 transparent component surface existing defects to be measured, shown in Fig. 5-3, inside transparent component to be detected
Existing defects, then reflection, refraction, scattering phenomenon occur for some detection laser beam, so that total reflection cannot be fully met
Condition, the detection video camera under total reflection below auxiliary member is arranged in this way can capture detection laser signal.
Fig. 6 only gives the placement schematic diagram of planar transparent component, for curved surface transparent component, not according to test object
Together, two sets of total reflection up/down auxiliary members are needed to configure, are respectively completed the detection of curved surface and plane, since principle is identical, herein not
It repeats again.
It is the light path schematic diagram of plane transparent component and curved face type transparent component respectively as shown in attached drawing 6-1, Fig. 6-2.
For plane 3C transparent component, laser head is only needed to will test laser beam with a fixed angle and injects transparent structure to be detected
The detection of one integral piece component can be completed by moving loaded work piece platform in X direction in part inside；But it is saturating for curved surface 3C
Bright component needs to detect planar section and curvature portion respectively, by ARM embedded controller according to the geometry of building to be detected
Dimension information calculates separately the laser beam incidence angle of plane and curvature portion, then drives servo electricity by driving device microcontroller
Machine and stepper motor movement, so that laser head reaches the angle of calculating, especially curvature portion, the laser for selecting dimensions small
Head is detected.
ARM embedded controller had both received the information of microcontroller, while also sending control instruction to microcontroller, realized
The positioning of laser head angle, and load platform is made to drive laser head interval sampling along the X direction in the detection process, to make
Camera shooting function must be detected to take pictures to detection imaging.
Specific detection operation are as follows:
Transparent component to be measured is placed between the upper auxiliary member of total reflection and the lower auxiliary of total reflection and is placed in light transmission workbench
On.
Laser emitter is moved to predetermined position, rotation adjusts the angle of laser emitter, laser emitter is determined
Position is to state to be detected, and then laser emitter persistently emits laser towards transparent component to be measured, and laser light incident is to be measured transparent
In component.
Detection video camera, which is taken pictures, obtains image, image transmitting to ARM embedded controller is carried out image preprocessing, then will
Image is transmitted to deep learning arithmetic element, automatically identifies power and the position of light leakage, to detect structure to be detected automatically
The defect type of part and its position.
As shown in attached drawing 7-1, Fig. 7-2, Fig. 7-3, deep learning arithmetic element is realized using FPGA hardware, incoming
Before, gray processing and dividing processing are carried out by ARM embedded controller, each image point by the specification of laser head, after segmentation
It is not compressed in 64 × 64 × 1,128 × 128 × 1 or 256 × 256 × 1 three dimensional grey scale image space, then carries out three secondary volumes
After the operation of long-pending and pondization, then the neural network connected entirely twice, it is output in 256 dimensional vectors, then returned by soft by 256
Dimensional vector output is vector (normal, defective), and the flow chart of data processing of network is as follows:
A) in order to improve identification precision, three networks of off-line training, that is to say and respectively correspond three kinds of different sizes respectively
Laser head, the input picture of three networks are 64 × 64 × 1,128 × 128 × 1 or 256 × 256 × 1 Three-Dimensional Gray respectively
Specification.
B) deep learning arithmetic element can single treatment multiple images.Thus, the settable a batch of the image divided is simultaneously
32 are input in the network of FPGA realization, the identification time is reduced by concurrent processing.
C) for 64 × 64 × 1, the A1 convolutional layer being sent into convolutional network is generated after the operation of 3 × 3 window convolutions
12 width images of 62 × 62 pixels, then compression processing is carried out by the pond the A2 layer in module, generate 12 width figures of 31 × 31 pixels
Picture carries out second of convolution operation later, and the A3 convolutional layer being sent into convolutional network is operated using 3 × 3 window convolutions again
Afterwards, 36 width images of 29 × 29 pixels are generated, then compression processing is carried out by the pond the A4 layer in convolutional network, generate 14 × 14 pictures
36 width images of element carry out third time convolution operation later, and the A5 convolutional layer being sent into convolutional network uses 3 × 3 windows again
After mouth convolution operation, 72 width images of 12 × 12 pixels are generated, then compression processing is carried out by the pond the A6 layer in convolutional network, it is raw
At 72 width images of 6 × 6 pixels, further, is handled by the full articulamentum of the A7 of convolutional network, exports the vector of 1024 dimensions,
Further, it is handled by the full articulamentum of A8 in convolutional network, the vector of 256 dimensions is exported, finally, again by convolutional network
The soft recurrence layer of A9 export 2 dimensional vectors, indicate that transparent component to be detected belongs to the probability density distribution of 2 classes (normal, defective),
To recognize 3C transparent component to be checked with the presence or absence of defect.
D) for 128 × 128 × 1, the B1 convolutional layer being sent into convolutional network is raw after the operation of 5 × 5 window convolutions
Compression processing is carried out at 12 width images of 124 × 124 pixels, then by the pond the B2 layer in module, generates the 12 of 62 × 62 pixels
Width image carries out second of convolution operation later, and the B3 convolutional layer being sent into convolutional network uses 3 × 3 window convolutions again
After operation, generate 60 × 60 pixels 36 width images, then by convolutional network the pond B4 layer carry out compression processing, generation 30 ×
36 width images of 30 pixels carry out third time convolution operation later, the B5 convolutional layer being sent into convolutional network, again using 3 ×
After the operation of 3 window convolutions, 72 width images of 28 × 28 pixels are generated, then compression is carried out by the pond the B6 layer in convolutional network
Reason generates 72 width images of 14 × 14 pixels, further, handles by the full articulamentum of the B7 of convolutional network, exports 2048 dimensions
Vector further handled by the full articulamentum of B8 in convolutional network, the vector of 256 dimensions exported, finally, again by rolling up
The soft recurrence layer of B9 in product network exports 2 dimensional vectors, indicates that transparent component to be detected belongs to the probability of 2 classes (normal, defective)
Density Distribution, to recognize 3C transparent component to be checked with the presence or absence of defect.
E) for 256 × 256 × 1, the C1 convolutional layer being sent into convolutional network is raw after the operation of 5 × 5 window convolutions
Compression processing is carried out at 12 width images of 252 × 252 pixels, then by the pond the C2 layer in module, generates 126 × 126 pixels
12 width images carry out second of convolution operation later, and the C3 convolutional layer being sent into convolutional network is rolled up using 3 × 3 windows again
After product operation, 36 width images of 124 × 124 pixels is generated, then compression processing is carried out by the pond the C4 layer in convolutional network, generated
36 width images of 62 × 62 pixels carry out third time convolution operation later, and the C5 convolutional layer being sent into convolutional network is adopted again
After the operation of 3 × 3 window convolutions, 72 width images of 60 × 60 pixels are generated, then are pressed by the pond the C6 layer in convolutional network
Contracting processing, generates 72 width images of 30 × 30 pixels, further, handles by the full articulamentum of the C7 of convolutional network, output 4096
The vector of dimension further handles by the full articulamentum of C8 in convolutional network, the vector of 256 dimensions is exported, finally, again
2 dimensional vectors are exported by the soft recurrence layer of the C9 in convolutional network, indicate that transparent component to be detected belongs to 2 classes (normal, defective)
Probability density distribution, to recognize 3C transparent component to be checked with the presence or absence of defect.
Further, the off-line training sample database of convolutional network can increase sample size.Thus, the precision of detection can be with
The increase of sample size and further promoted；Convolutional network can also be trained in use update by user, can also be with
Selection is regularly updated by device manufacturer.
It should be noted that it is practical new to be not limited to this above is only the preferred embodiment of the utility model
Type, although the utility model is described in detail referring to embodiment, for those skilled in the art, still
It can modify to technical solution documented by previous embodiment or equivalent replacement of some of the technical features,
But within the spirit and principle of the utility model, any modification, equivalent replacement, improvement and so on should be included in
Within the protection scope of the utility model.
Claims (7)
1. a kind of transparent component defect detecting device, which is characterized in that described device includes positioning drive unit, Laser emission
Device, light transmission workbench, detection video camera, deep learning arithmetic element, ARM embedded controller and combined aural and visual alarm, laser hair
Emitter is connect with positioning drive unit, positioning drive unit, detection video camera, deep learning arithmetic element and acoustic-optic alarm
By CAN bus and ARM embedded controller communication connection, video camera is detected against light transmission working machine and shoots acquisition image.
2. transparent component defect detecting device according to claim 1, which is characterized in that also set on the light transmission workbench
There is auxiliary member in the total reflection for clamping transparent component to be measured and be totally reflected lower auxiliary member, is totally reflected lower auxiliary member and is located at light transmission
On workbench, transparent component to be measured is located at the upper auxiliary member of total reflection and is totally reflected between lower auxiliary member, in total reflection auxiliary member and
There is exposed gap portion between transparent component to be measured.
3. transparent component defect detecting device according to claim 2, which is characterized in that the positioning drive unit includes
Microcontroller, X are to motor, X to positioning screw rod, Y-direction motor, Y-direction positioning screw rod, X to load platform, Y-direction load platform and angle
Degree positioning stepper motor, X are connected to positioning screw rod and X to motor and mounted in X on load platform, and Y-direction load platform passes through spiral shell
X is sleeved on on positioning screw rod, Y-direction positioning screw rod connect with Y-direction motor and on Y-direction load platform, and angle positions stepping
Motor by link block on the Y-direction positioning screw rod, the driving axis connection of laser emitter and angle positioning stepper motor, X to
Motor, Y-direction motor, angle positioning stepper motor are connect with microcontroller respectively, and microcontroller is embedded in by CAN bus and ARM
Formula controller communication connects, and is connected with grating scale on microcontroller.
4. transparent component defect detecting device according to claim 3, which is characterized in that the X is to load platform, Y-direction
One end of load platform further respectively has the null pick-up with microcontroller communication connection.
5. transparent component defect detecting device according to claim 4, which is characterized in that auxiliary member in the total reflection,
Transparent component to be detected is totally reflected the requirement for meeting laser total reflection between lower auxiliary member three, that is to say be incident on it is to be detected
The laser light incident angle C of transparent component meets
C≥sin-1(n2/n1),
Wherein n2To be totally reflected upper auxiliary member and being totally reflected the refractive index of lower auxiliary member, n1For the refractive index of transparent component to be measured.
6. transparent component defect detecting device according to claim 5, which is characterized in that the laser emitter is set side by side
There is the laser head of at least three different sizes, for measuring the transparent component to be measured of different-thickness.
7. transparent component defect detecting device according to claim 6, which is characterized in that the detection video camera is located at
The lower section of light workbench, and video camera periphery is detected equipped with sheet metal shell.
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| CN201821738996.6U CN209148564U (en) | 2018-10-25 | 2018-10-25 | A kind of transparent component defect detecting device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109100371A (en) * | 2018-10-25 | 2018-12-28 | 广东华中科技大学工业技术研究院 | A kind of the 3C transparent component defect detecting device and method of laser total reflection formula |
| CN111721216A (en) * | 2020-06-29 | 2020-09-29 | 河南科技大学 | Steel wire rope detection device based on three-dimensional image, surface damage detection method and rope diameter calculation method |
-
2018
- 2018-10-25 CN CN201821738996.6U patent/CN209148564U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109100371A (en) * | 2018-10-25 | 2018-12-28 | 广东华中科技大学工业技术研究院 | A kind of the 3C transparent component defect detecting device and method of laser total reflection formula |
| CN111721216A (en) * | 2020-06-29 | 2020-09-29 | 河南科技大学 | Steel wire rope detection device based on three-dimensional image, surface damage detection method and rope diameter calculation method |
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