CN105921886B - A kind of laser process machine of high recognition performance - Google Patents
A kind of laser process machine of high recognition performance Download PDFInfo
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- CN105921886B CN105921886B CN201610525719.6A CN201610525719A CN105921886B CN 105921886 B CN105921886 B CN 105921886B CN 201610525719 A CN201610525719 A CN 201610525719A CN 105921886 B CN105921886 B CN 105921886B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
- B23K26/08—Devices involving relative movement between laser beam and workpiece
- B23K26/0869—Devices involving movement of the laser head in at least one axial direction
- B23K26/0876—Devices involving movement of the laser head in at least one axial direction in at least two axial directions
- B23K26/0884—Devices involving movement of the laser head in at least one axial direction in at least two axial directions in at least in three axial directions, e.g. manipulators, robots
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
- B23K26/70—Auxiliary operations or equipment
- B23K26/702—Auxiliary equipment
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Abstract
The present invention provides a kind of laser process machines of high recognition performance,The Target Identification Unit being connected including laser process machine and with laser process machine,Target is identified tracking in Target Identification Unit view-based access control model feature,Including sequentially connected suspection Target Acquisition module,Colouring information processing module,Profile information processing module,Feature evaluation module,Wherein colouring information processing module carries out the original hardwood image from RGB color to the conversion in hsv color space and builds tonal color model of the suspection target in hsv color space,The area type that profile information processing module is used to carry out the actual profile of the original hardwood image characteristic area and non-characteristic area divides,Adjacent same type region is merged,And the wave filter for choosing different parameters is smoothed the characteristic area after merging and non-characteristic area respectively.The present invention has the advantages that accuracy of identification is high, recognition speed is fast.
Description
Technical field
The present invention relates to field of laser processing, and in particular to a kind of laser process machine of high recognition performance.
Background technology
In the relevant technologies, target in positioning accuracy and is tracked successfully into line trace using radar on laser process machine
Have very big advantage in rate, but be only difficult that clarification of objective is distinguished from the range information that radar obtains, especially in mesh
Mark is blocked under multi-target condition, is difficult to realize target effective recognition and tracking.Using visual information (such as color, the wheel of target
Exterior feature etc.) target signature is portrayed, it is the effective way to solve the above problems target to be identified based on target visual feature tracking.
Invention content
In view of the above-mentioned problems, the present invention provides a kind of laser process machine of high recognition performance.
The purpose of the present invention is realized using following technical scheme：
A kind of laser process machine of high recognition performance, the mesh being connected including laser process machine and with laser process machine
Identification device is marked, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
The mean radius of curvature of profile starting point arrived；F (t) is to judge whether profile point is characterized characteristic function a little, the table of f (t)=1
Show that the profile point is characterized a little, f (t)=0 represents the profile point as non-characteristic point, NF (t)=1It represents possessed by selection area
The number of characteristic point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function
Actual profile curvature obtained from carrying out neighborhood averaging to actual profile, max | k'N(t) | represent the absolute of actual profile curvature
The maximum value of value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Preferably, the profile information processing module includes the first filter being smoothed to all characteristic areas
With the second filter being smoothed to all non-characteristic areas, the length of the confidence interval of the first filter is institute
Have 1/2 of the minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
1/2 of minimum development length in domain；Different according to the curvature of difference, development length correspondingly automatic adaptive change has
Effect reduces the distortion phenomenon after merging, convenient for more accurately target is identified.
Beneficial effects of the present invention are：
1st, tracking target is described in a manner that colouring information and profile information are combined, is had to the variation of extraneous illumination
Very strong robustness is avoided and target is described using single features, improves the precision of identification；
2nd, revised color space conversion formula is more in line with the visual effect of the mankind, can reflect more rich letter
Breath, is easy to implement quick recognition and tracking, and space weight is introduced in tonal color model and is divided, repeatedly filters, makes model more
Science, practicability are stronger；
3rd, set profile information processing module, for the actual profile of the original hardwood image carry out characteristic area with it is non-
The area type of characteristic area is divided, adjacent same type region is merged, and choose the wave filter pairing of different parameters
Characteristic area after and is smoothed respectively with non-characteristic area, and calculation amount is simultaneously uncomplicated, smooth except effect of making an uproar is good, is considered
Otherness of the profile between different type region obtains good balance between inhibiting noise and retaining details, according to
The curvature of difference is different, and development length correspondingly automatic adaptive change effectively reduces the distortion phenomenon after merging, is convenient for
More accurately target is identified.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not form any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the Target Identification Unit module connection diagram of the present invention.
Specific embodiment
The invention will be further described with the following Examples.
Embodiment 1
Referring to Fig. 1, a kind of laser process machine of high recognition performance of the present embodiment, including laser process machine and and laser
The Target Identification Unit that machining tool is connected, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
Profile starting point mean radius of curvature；F (t) is to judge the characteristic function whether profile point is characterized a little, and f (t)=1 represents
The profile point is characterized a little, and f (t)=0 represents the profile point as non-characteristic point, NF (t)=1Represent possessed spy in selection area
Levy the number of point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function pair
Actual profile carries out actual profile curvature obtained from neighborhood averaging, max | k'N(t) | represent the absolute value of actual profile curvature
Maximum value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Wherein, the profile information processing module include the first filter that all characteristic areas are smoothed and
To the second filter that all non-characteristic areas are smoothed, the length of the confidence interval of the first filter is all
1/2 of minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
In minimum development length 1/2；It is different according to the curvature of difference, development length correspondingly automatic adaptive change, effectively
The distortion phenomenon after merging is reduced, convenient for more accurately target is identified.
The present embodiment describes tracking target, the change to extraneous illumination in a manner that colouring information and profile information are combined
Changing has very strong robustness, avoids and target is described using single features, improve the precision of identification；Revised face
Colour space conversion formula is more in line with the visual effect of the mankind, can reflect more rich information, be easy to implement quick identification with
Track introduces weight division in space in tonal color model, repeatedly filters, make model more science, practicability is stronger；Setting wheel
Wide message processing module, the wave filter for choosing different parameters carry out smoothly the characteristic area after merging and non-characteristic area respectively
Processing, it is contemplated that otherness of the profile between different type region obtains good between inhibiting noise and retaining details
Balance, different according to the curvature of difference, development length correspondingly automatic adaptive change effectively reduces the distortion after merging
Phenomenon, convenient for more accurately target is identified, wherein settingWidth for 3, the value of weights T is 0.2, identification essence
Degree improves 2%, and recognition speed improves 1%.
Embodiment 2
Referring to Fig. 1, a kind of laser process machine of high recognition performance of the present embodiment, including laser process machine and and laser
The Target Identification Unit that machining tool is connected, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
The mean radius of curvature of profile starting point arrived；F (t) is to judge whether profile point is characterized characteristic function a little, the table of f (t)=1
Show that the profile point is characterized a little, f (t)=0 represents the profile point as non-characteristic point, NF (t)=1It represents possessed by selection area
The number of characteristic point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function
Actual profile curvature obtained from carrying out neighborhood averaging to actual profile, max | k'N(t) | represent the absolute of actual profile curvature
The maximum value of value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Wherein, the profile information processing module include the first filter that all characteristic areas are smoothed and
To the second filter that all non-characteristic areas are smoothed, the length of the confidence interval of the first filter is all
1/2 of minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
In minimum development length 1/2；It is different according to the curvature of difference, development length correspondingly automatic adaptive change, effectively
The distortion phenomenon after merging is reduced, convenient for more accurately target is identified.
The present embodiment describes tracking target, the change to extraneous illumination in a manner that colouring information and profile information are combined
Changing has very strong robustness, avoids and target is described using single features, improve the precision of identification；Revised face
Colour space conversion formula is more in line with the visual effect of the mankind, can reflect more rich information, be easy to implement quick identification with
Track introduces weight division in space in tonal color model, repeatedly filters, make model more science, practicability is stronger；Setting wheel
Wide message processing module, the wave filter for choosing different parameters carry out smoothly the characteristic area after merging and non-characteristic area respectively
Processing, it is contemplated that otherness of the profile between different type region obtains good between inhibiting noise and retaining details
Balance, different according to the curvature of difference, development length correspondingly automatic adaptive change effectively reduces the distortion after merging
Phenomenon, convenient for more accurately target is identified, wherein settingWidth for 4, the value of weights T is 0.3, identification essence
Degree improves 1%, and recognition speed improves 2%.
Embodiment 3
Referring to Fig. 1, a kind of laser process machine of high recognition performance of the present embodiment, including laser process machine and and laser
The Target Identification Unit that machining tool is connected, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
Profile starting point mean radius of curvature；F (t) is to judge the characteristic function whether profile point is characterized a little, and f (t)=1 represents
The profile point is characterized a little, and f (t)=0 represents the profile point as non-characteristic point, NF (t)=1Represent possessed spy in selection area
Levy the number of point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function pair
Actual profile carries out actual profile curvature obtained from neighborhood averaging, max | k'N(t) | represent the absolute value of actual profile curvature
Maximum value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Wherein, the profile information processing module include the first filter that all characteristic areas are smoothed and
To the second filter that all non-characteristic areas are smoothed, the length of the confidence interval of the first filter is all
1/2 of minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
In minimum development length 1/2；It is different according to the curvature of difference, development length correspondingly automatic adaptive change, effectively
The distortion phenomenon after merging is reduced, convenient for more accurately target is identified.
The present embodiment describes tracking target, the change to extraneous illumination in a manner that colouring information and profile information are combined
Changing has very strong robustness, avoids and target is described using single features, improve the precision of identification；Revised face
Colour space conversion formula is more in line with the visual effect of the mankind, can reflect more rich information, be easy to implement quick identification with
Track introduces weight division in space in tonal color model, repeatedly filters, make model more science, practicability is stronger；Setting wheel
Wide message processing module, the wave filter for choosing different parameters carry out smoothly the characteristic area after merging and non-characteristic area respectively
Processing, it is contemplated that otherness of the profile between different type region obtains good between inhibiting noise and retaining details
Balance, different according to the curvature of difference, development length correspondingly automatic adaptive change effectively reduces the distortion after merging
Phenomenon, convenient for more accurately target is identified, wherein settingWidth for 5, the value of weights T is 0.4, identification essence
Degree improves 2%, and recognition speed improves 3%.
Embodiment 4
Referring to Fig. 1, a kind of laser process machine of high recognition performance of the present embodiment, including laser process machine and and laser
The Target Identification Unit that machining tool is connected, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
Profile starting point mean radius of curvature；F (t) is to judge the characteristic function whether profile point is characterized a little, and f (t)=1 represents
The profile point is characterized a little, and f (t)=0 represents the profile point as non-characteristic point, NF (t)=1Represent possessed spy in selection area
Levy the number of point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function pair
Actual profile carries out actual profile curvature obtained from neighborhood averaging, max | k'N(t) | represent the absolute value of actual profile curvature
Maximum value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Wherein, the profile information processing module include the first filter that all characteristic areas are smoothed and
To the second filter that all non-characteristic areas are smoothed, the length of the confidence interval of the first filter is all
1/2 of minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
In minimum development length 1/2；It is different according to the curvature of difference, development length correspondingly automatic adaptive change, effectively
The distortion phenomenon after merging is reduced, convenient for more accurately target is identified.
The present embodiment describes tracking target, the change to extraneous illumination in a manner that colouring information and profile information are combined
Changing has very strong robustness, avoids and target is described using single features, improve the precision of identification；Revised face
Colour space conversion formula is more in line with the visual effect of the mankind, can reflect more rich information, be easy to implement quick identification with
Track introduces weight division in space in tonal color model, repeatedly filters, make model more science, practicability is stronger；Setting wheel
Wide message processing module, the wave filter for choosing different parameters carry out smoothly the characteristic area after merging and non-characteristic area respectively
Processing, it is contemplated that otherness of the profile between different type region obtains good between inhibiting noise and retaining details
Balance, different according to the curvature of difference, development length correspondingly automatic adaptive change effectively reduces the distortion after merging
Phenomenon, convenient for more accurately target is identified, wherein settingWidth for 5, the value of weights T is 0.5, identification essence
Degree improves 2%, and recognition speed improves 2.5%.
Embodiment 5
Referring to Fig. 1, a kind of laser process machine of high recognition performance of the present embodiment, including laser process machine and and laser
The Target Identification Unit that machining tool is connected, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are far from pedestal
One end connect a crossbeam, and formed a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X
Axle mould group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y
Axle mould group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement support
Plate is set on X-axis linear guides, and is threadedly coupled with X-axis ball screw.
Preferably, the laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, rotary table and the A being connected with each other
The axis servo motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis, wherein the fixed seat is set
In on Y-axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servos
Motor drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, time
Turn plane with rotary table to be connected, and rotary table can be driven to carry out in the horizontal direction by C axis servo motor
Rotation.
Preferably, the laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z
Axle mould group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, described
Z axis movement supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on connect with Z axis ball screw screw thread
It connects, the one side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for inciting somebody to action
The laser beam that laser is sent out imports scanning galvanometer.
Preferably, the Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects target
Original hardwood image, including the infrared CCD being connect with field computer, the infrared CCD will be defeated
The picture signal gone out is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module carries out from RGB color to hsv color space the original hardwood image
Conversion and build the suspection target in the tonal color model in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is the pixel of original hardwood image in the RGB coordinate value of RGB color, virtual value model
Enclose is (0,1)；H is form and aspect component of the pixel in hsv color space, and s is saturation of the pixel in hsv color space
Component is spent, v is chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the rope in space
Draw, bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
Preferably, the Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-spy to the actual profile of the original hardwood image
The area type in sign region divides, adjacent same type region is merged, and chooses the wave filter of different parameters to merging
Characteristic area afterwards is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as feature
The decision condition in region is：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located at the selection area to be preset
Interior starting profile point, s are preset development length, the value of development length for selection area edge contour point to the starting
The distance of profile point,For being repaiied for correcting the real-time curvature of the development length s at starting profile point
Positive coefficient,To originate the radius of curvature of profile point,To be obtained by the window function that preset width range is [3,5]
Profile starting point mean radius of curvature；F (t) is to judge the characteristic function whether profile point is characterized a little, and f (t)=1 represents
The profile point is characterized a little, and f (t)=0 represents the profile point as non-characteristic point, NF (t)=1Represent possessed spy in selection area
Levy the number of point, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is by the window function pair
Actual profile carries out actual profile curvature obtained from neighborhood averaging, max | k'N(t) | represent the absolute value of actual profile curvature
Maximum value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target set in processed colouring information and profile information and database
Feature is compared matching and calculates matching degree, and the matching degree judges that the suspection target is when reaching preset matching threshold
Tracking target simultaneously exports judgement result；
Wherein, the profile information processing module include the first filter that all characteristic areas are smoothed and
To the second filter that all non-characteristic areas are smoothed, the length of the confidence interval of the first filter is all
1/2 of minimum development length in characteristic area, the length of the confidence interval of the second filter is all non-characteristic areas
In minimum development length 1/2；It is different according to the curvature of difference, development length correspondingly automatic adaptive change, effectively
The distortion phenomenon after merging is reduced, convenient for more accurately target is identified.
The present embodiment describes tracking target, the change to extraneous illumination in a manner that colouring information and profile information are combined
Changing has very strong robustness, avoids and target is described using single features, improve the precision of identification；Revised face
Colour space conversion formula is more in line with the visual effect of the mankind, can reflect more rich information, be easy to implement quick identification with
Track introduces weight division in space in tonal color model, repeatedly filters, make model more science, practicability is stronger；Setting wheel
Wide message processing module, the wave filter for choosing different parameters carry out smoothly the characteristic area after merging and non-characteristic area respectively
Processing, it is contemplated that otherness of the profile between different type region obtains good between inhibiting noise and retaining details
Balance, different according to the curvature of difference, development length correspondingly automatic adaptive change effectively reduces the distortion after merging
Phenomenon, convenient for more accurately target is identified, wherein settingWidth for 4, the value of weights T is 0.3, identification essence
Degree improves 2.5%, and recognition speed improves 3.5%.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention rather than the present invention is protected
The limitation of range is protected, although being explained in detail with reference to preferred embodiment to the present invention, those of ordinary skill in the art should
Work as understanding, technical scheme of the present invention can be modified or replaced equivalently, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (1)
1. a kind of laser process machine of high recognition performance, the target being connected including laser process machine and with laser process machine
Identification device, it is characterized in that, the laser process machine includes：
Pedestal is fixed with a laser and two root posts on the pedestal, wherein the two root posts are in one far from pedestal
One crossbeam of end connection, and form a gantry；
X-axis moves module, and the X-axis movement module includes X-axis servo motor, X-axis ball screw, X-axis linear guides, X-axis mould
Group pedestal and X-axis movement supporting plate, wherein the X-axis module pedestal is fixed by screws on crossbeam, the X-axis movement supporting plate is set
In on X-axis linear guides, and it is threadedly coupled with X-axis ball screw；
Y-axis moves module, and the Y-axis movement module includes Y-axis servo motor, Y-axis ball screw, Y-axis linear guides, Y-axis mould
Group pedestal and Y-axis movement supporting plate, wherein the Y-axis module pedestal is fixed by screws on pedestal, the Y-axis movement supporting plate is set
In on Y-axis linear guides, and it is threadedly coupled with Y-axis ball screw；
The laser process machine further includes：
Rotary oscillation head, the rotary oscillation head include fixed seat, oscillating deck, and rotary table and the A axis being connected with each other are watched
The motor and hollow rotary reducer of A axis, the C axis servo motor and hollow rotary reducer of C axis are taken, wherein the fixed seat is set on Y
On axis movement supporting plate, the plane of rotation of the hollow rotary reducer of A axis is connected with oscillating deck, and can pass through A axis servo electricity
Machine drives oscillating deck to be rotated in the vertical direction, and the hollow rotary reducer of C axis is fixed on oscillating deck, revolution
Plane is connected with rotary table, and rotary table can be driven to be revolved in the horizontal direction by C axis servo motor
Turn；
The laser process machine further includes：
Z axis moves module, and the Z axis movement module includes Z axis servo motor, Z axis ball screw, Z axis linear guides, Z axis mould
Group pedestal and Z axis movement supporting plate, move wherein the Z axis module pedestal is fixed on X-axis by connecting plate on supporting plate, the Z axis
Move supporting plate be set on Z axis linear guides on, towards the one side of Z axis module pedestal on be threadedly coupled with Z axis ball screw,
One side away from Z axis module pedestal is provided with scanning galvanometer by galvanometer connecting plate；And multiple speculums, for by laser
The laser beam that device is sent out imports scanning galvanometer；
The Target Identification Unit includes：
(1) Target Acquisition module is suspected, for target to be suspected in identification in monitor video and reading includes and suspects the original of target
Hardwood image, including the infrared CCD being connect with field computer, the infrared CCD is by output
Picture signal is input to field computer and is made whether there is the differentiation processing for suspecting target；
(2) colouring information processing module to the original hardwood image from RGB color to hsv color space turn
It changes and builds tonal color model of the suspection target in hsv color space, conversion formula is as follows：
V=Max (r, g, b)
Wherein, (r, g, b) is RGB coordinate value of the pixel in RGB color of original hardwood image, and valid value range is equal
For (0,1)；H is form and aspect component of the pixel in hsv color space, and s is the pixel saturation degree in hsv color space point
Amount, v are chrominance component of the pixel in hsv color space；
Tonal color model is as follows：
Herein
Wherein, function δ [d (xi)-w] it is pixel xiProjection in the region of w-th of subspace, w are characterized the index in space,
bwFor the weight of each subspace,It is with pixel xcCentered on kernel function in two dimensional image；
The Target Identification Unit further includes：
(3) profile information processing module, for carrying out characteristic area and non-characteristic area to the actual profile of the original hardwood image
The area type in domain divides, adjacent same type region is merged, and after choosing the wave filters of different parameters to merging
Characteristic area is smoothed respectively with non-characteristic area, and the selection area in the actual profile is judged as characteristic area
Decision condition be：
Herein
Wherein, t represents the profile point of the actual profile of the original hardwood image, t0It is located in the selection area to be preset
Originate profile point, s is preset development length, the value of development length for selection area edge contour point to the starting profile
The distance of point,To correct the real-time curvature amendment system of the development length s at starting profile point
Number,To originate the radius of curvature of profile point,For the wheel obtained by the window function that preset width range is [3,5]
The mean radius of curvature of wide starting point；F (t) is to judge the characteristic function whether profile point is characterized a little, and f (t)=1 represents the wheel
Exterior feature point is characterized a little, and f (t)=0 represents the profile point as non-characteristic point, Nf(t)=1Represent possessed characteristic point in selection area
Number, NyFor the number of characteristic point included as characteristic area needs of setting, k'N(t) it is to reality by the window function
Profile carries out actual profile curvature obtained from neighborhood averaging, max | k'N(t) | represent the absolute value of actual profile curvature most
Big value, the value range that T is weights and T is [0.2,0.5]；
(4) feature evaluation module, for the target signature set in processed colouring information and profile information and database
Matching is compared and calculates matching degree, the matching degree judges the suspection target for tracking when reaching preset matching threshold
Target simultaneously exports judgement result；
The profile information processing module includes the first filter being smoothed to all characteristic areas and to all non-
The second filter that characteristic area is smoothed, the length of the confidence interval of the first filter is all characteristic areas
In minimum development length 1/2, the length of the confidence interval of the second filter is the minimum in all non-characteristic areas
The 1/2 of development length.
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