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CN103846606A - Special testing device and method for correcting welding track based on machine vision - Google Patents

Special testing device and method for correcting welding track based on machine vision Download PDF

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Publication number
CN103846606A
CN103846606A CN201410053434.8A CN201410053434A CN103846606A CN 103846606 A CN103846606 A CN 103846606A CN 201410053434 A CN201410053434 A CN 201410053434A CN 103846606 A CN103846606 A CN 103846606A
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machine vision
welding
axis direction
image
axis
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CN103846606B (en
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李琳
李春
邹焱飚
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South China University of Technology SCUT
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South China University of Technology SCUT
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Priority to PCT/CN2014/092796 priority patent/WO2015120734A1/en
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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
    • B23K37/00—Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass
    • B23K37/04—Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
    • B23K37/0461—Welding tables
    • 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
    • B23K37/00—Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J13/00—Controls for manipulators
    • B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/401—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control arrangements for measuring, e.g. calibration and initialisation, measuring workpiece for machining purposes
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/45—Nc applications
    • G05B2219/45135—Welding

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Optics & Photonics (AREA)
  • General Physics & Mathematics (AREA)
  • Robotics (AREA)
  • Manufacturing & Machinery (AREA)
  • Automation & Control Theory (AREA)
  • Manipulator (AREA)
  • Image Processing (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

本发明公开了一种基于机器视觉的焊接轨迹校正专用测试装置及方法，所述装置包括工作台、精密定位机构、机器视觉采集设备和控制设备，所述精密定位机构和机器视觉采集设备分别与控制设备连接，所述精密定位机构、机器视觉采集设备和控制设备设置在工作台上，所述机器视觉采集设备位于精密定位机构的上方；所述精密定位机构包括x轴方向驱动单元、y轴方向驱动单元、x轴方向位置检测单元以及y轴方向位置检测单元。本发明装置能实现基于机器视觉技术完成焊接工件轨迹在x轴和y轴方向偏移量检测，并对检测结果进行评估和验证，分析误差产生的原因，不断优化机器视觉技术中的图像处理方法，从而实现焊接轨迹偏移量准确检测的目的。

The invention discloses a special testing device and method for welding trajectory correction based on machine vision. The device includes a workbench, a precision positioning mechanism, a machine vision acquisition device and a control device. The precision positioning mechanism and the machine vision acquisition device are respectively connected with the The control equipment is connected, and the precision positioning mechanism, machine vision acquisition equipment and control equipment are arranged on the workbench, and the machine vision acquisition equipment is located above the precision positioning mechanism; the precision positioning mechanism includes an x-axis direction drive unit, a y-axis A direction drive unit, a position detection unit in the x-axis direction, and a position detection unit in the y-axis direction. The device of the present invention can realize the detection of the offset of the welding workpiece trajectory in the x-axis and y-axis directions based on machine vision technology, evaluate and verify the detection results, analyze the cause of errors, and continuously optimize the image processing method in machine vision technology , so as to achieve the purpose of accurate detection of welding track offset.

Description

Welding track based on machine vision is proofreaied and correct Special testing device and method
Technical field
The present invention relates to a kind of welding track and proofread and correct Special testing device, especially a kind of welding track based on machine vision is proofreaied and correct Special testing device and method, belongs to welding track alignment technique field.
Background technology
Because artificial welding exists severe operational environment, the amount of labour is large, with problems such as inefficiencies, automobile at home of current robot welding, engineering machinery, and many fields such as container production have progressively obtained application, welding robot adopts the work of teaching reproduction mode conventionally, " teach programming " refers to complete by following manner the establishment of program: completed the action of expection by artificial guiding robot end effector (as: welding gun) Lai Shi robot, " task program " is one group of motion and miscellaneous function instruction, specifically expect operation in order to determine robot." reproduction " refers to that robot obtains task program according to teach programming, constantly repetition.
Implement at concrete welding surroundings for guaranteeing " teaching reproduction " this mode of operation, in front operation, need to complete welding work pieces location by artificial spot welding, this can cause position error, thus robot trajectory while causing teach programming acquisition robot welding track to depart from reproduction.
For addressing the above problem, conventionally need to adopt mechanical vision inspection technology to proofread and correct the welding track reproducing, as shown in Figure 1.Machine vision technique refers to by industrial camera 1 and converts welded part 2 to picture signal, sends image processing system to, according to the information such as pixel distribution and brightness, color, is transformed into digitized signal; Picture system carries out various computings to these signals and carrys out the feature of extracting objects, thereby determines and reproduce welding track side-play amount, and welding robot 3 can accurately be welded welding work pieces 2; But this accuracy evaluation of being determined welding track side-play amount by machine vision technique but occurs there are no relevant apparatus with verifying, therefore need to develop a set of Special testing device, can the welding track side-play amount precision of being determined by machine vision technique be assessed and be verified, and the reason of analytical error generation, thereby continue to optimize the image processing method in machine vision technique, make to realize the accurate testing requirement of welding track side-play amount.
Summary of the invention
The object of the invention is the defect in order to solve above-mentioned prior art, provide a kind of can realization based on machine vision technique to complete welding track based on the machine vision correction Special testing device of welding work pieces track in x axle and the detection of y direction of principal axis side-play amount.
Another object of the present invention is to provide a kind of welding track based on machine vision to proofread and correct the method for testing of Special testing device.
Object of the present invention can be by taking following technical scheme to reach:
Welding track based on machine vision is proofreaied and correct Special testing device, it is characterized in that: comprise workbench, precision positioning mechanism, machine vision collecting device and control appliance, described precision positioning mechanism is connected with control appliance respectively with machine vision collecting device, described precision positioning mechanism, machine vision collecting device and control appliance are arranged on workbench, and described machine vision collecting device is positioned at the top of precision positioning mechanism; Described precision positioning mechanism comprises x direction of principal axis driver element, y direction of principal axis driver element, x direction of principal axis position detection unit and y direction of principal axis position detection unit; In the time of test, described y direction of principal axis driver element drives welding work pieces to move along y direction of principal axis, and described x direction of principal axis driver element drives y direction of principal axis driver element that welding work pieces is moved along x direction of principal axis.
Preferably, described x direction of principal axis driver element comprises the first AC servo motor, the first shaft coupling and the first ball screw that connect successively, is provided with x direction of principal axis travelling carriage on described the first ball screw; Described y direction of principal axis driver element comprises the second AC servo motor, the second shaft coupling and the second ball screw that connect successively, is provided with y direction of principal axis travelling carriage on described the second ball screw; Described y direction of principal axis driver element is placed on x direction of principal axis travelling carriage, and described y direction of principal axis travelling carriage is used for placing welding work pieces in the time of test; Described x direction of principal axis position detection unit and y direction of principal axis position detection unit adopt respectively the first linear grid ruler and the second linear grid ruler, described the first linear grid ruler is arranged on a side of x direction of principal axis driver element, and described the second linear grid ruler is arranged on a side of y direction of principal axis driver element.
Preferably, described machine vision collecting device comprises industrial camera, camera lens and light source, and described camera lens is connected with industrial camera and aims at precision positioning mechanism, and described distribution of light sources is around camera lens.
Preferably, described control appliance comprises industrial control host, motion controller, the first AC servo driver and the second AC servo driver, described the first AC servo driver is connected with the first AC servo motor, described the second AC servo driver is connected with the second AC servo motor, described the first AC servo driver and the second AC servo driver are set up communication by motion controller and industrial control host respectively, described the first linear grid ruler is connected with motion controller by communication interface respectively with the second linear grid ruler, described industrial control host is connected with industrial camera by bus communication card, described industrial control host is connected with the display for realizing man-machine interaction.
Preferably, described workbench adopts frame structure, one side of this frame structure is provided with vertical supports, in described vertical supports, be vertically fixed with horizontal support, described precision positioning mechanism is arranged in the top planes of frame structure, described control appliance is arranged on the inside of frame structure, and described machine vision collecting device is fixed on horizontal support.
Preferably, the bottom of described frame structure is provided with four wheels that can make movable workbench.
Preferably, the frame structure that the frame structure that described workbench adopts is 1000*800*700mm.
Another object of the present invention can be by taking following technical scheme to reach:
The method of testing of proofreading and correct Special testing device based on the welding track of machine vision, is characterized in that comprising the following steps:
1) adopt scaling board to demarcate, obtain industrial camera intrinsic parameter and outer parameter;
2) welding work pieces is positioned on the y direction of principal axis travelling carriage of precision positioning mechanism, according to the current location of welding work pieces, captures welding work pieces image and set up welding work pieces template by industrial camera;
3) set welding work pieces x axle and the y axle offset amount on workbench by industrial control host, controlling the first AC servo motor and the first ball screw drives welding work pieces to move to the x axle offset amount position of setting, control the y axle offset amount position that the second AC servo motor and the second ball screw driving welding work pieces move to setting, obtain respectively x axle and the y axle real offset (x of current welding work pieces by the first linear grid ruler and the second linear grid ruler r, y r);
4) after welding work pieces skew, again capture the welding work pieces image of current location by industrial camera, and adopt image noise reduction algorithm to process image;
5) adopt the template matching algorithm based on gray value, obtain x axle and the y axial side-play amount (x of welding work pieces with respect to template workpiece m, y m);
6) compare (x r, y r) and (x m, y m) value, reproduce process allowable error according to welding robot, judge whether the precision of Machine Vision Detection meets the demands, judge whether to meet | x m - x r | < [ &Delta;x ] \ y m - y r | < [ &Delta;y ] , Wherein Δ x and Δ y are the error that welding system allows; If meet the demands, can be integrated in industrial robot control system and apply; If do not meet the demands, the reason that analytical error produces, is optimized from industrial camera demarcation, image noise reduction Processing Algorithm and template matching algorithm, improves certainty of measurement, thereby meets instructions for use.
Preferably, step 4) specific as follows:
After welding work pieces skew, again capture the welding work pieces image of current location by industrial camera, this image is 24bit coloured image, transfer the gray level image of 256 grades to by image binaryzation, adopt again mean filter to complete noise reduction process, wherein mean filter mask size is m × n, and in image, any point (x, y) response is:
g ( x , y ) = 1 mn ( &Sigma; i = - a a &Sigma; j = - b b f ( x + i , y + j ) )
Wherein, g (x, y) is mask pixel average,
Figure BDA0000466542580000033
Preferably, step 5) specific as follows:
A) adopt the template matching algorithm based on gray value, by calculating normalizated correlation coefficient NCC, determine the similarity of current welding work pieces image and template image coupling, determine thus welding work pieces with respect to the side-play amount of template workpiece x axle and y axle in image coordinate system (x ' m, y ' m):
NCC ( x , y ) = 1 n &Sigma; ( i , j ) &Element; T t ( i , j ) - m t s t 2 &CenterDot; f ( x + i , y + j ) - m f ( x , y ) s f 2 ( x , y )
Wherein, t (i, j) is welding work pieces template gray value, and f (x+i, y+j) is current welding work pieces gradation of image value, m ttemplate average gray value,
Figure BDA0000466542580000042
the variance of all gray values of template, m f(x, y) and m f(x, y) is average gray value and the variance of each point in the current welding work pieces template of translation; In the time of normalizated correlation coefficient NCC=± 1, between welding work pieces template and current welding work pieces image, mate completely, and normalizated correlation coefficient NCC absolute value more approaches 1, represent that welding work pieces template is more approaching with the welding work pieces image detecting;
B) industrial camera obtains intrinsic parameter and outer parameter after demarcating, x axle above-mentioned steps a) being obtained through seven submatrixs conversion and affine transformation and the side-play amount of y axle (x ' m, y ' m) be converted to x axle and y axle offset amount (x in tool coordinates system m, y m).
The present invention has following beneficial effect with respect to prior art:
Welding track based on machine vision of the present invention is proofreaied and correct Special testing device, by precision positioning mechanism and machine vision collecting device are set, can realize based on machine vision technique and complete welding work pieces track in x axle and the detection of y direction of principal axis side-play amount, and utilize industrial control host testing result is assessed and verified, in the time meeting required precision, can be integrated in industrial robot control system and apply, the reason that analytical error produces in the time not meeting required precision, continue to optimize the image processing method in machine vision technique, thereby realize the object that welding track side-play amount accurately detects.
Accompanying drawing explanation
Fig. 1 is the welding robot operative scenario schematic diagram that applied for machines vision technique carries out welding track correction.
Fig. 2 is that the welding track based on machine vision of the present invention is proofreaied and correct Special testing device structural representation.
Fig. 3 is that the welding track based on machine vision of the present invention is proofreaied and correct Special testing device structural principle block diagram.
Fig. 4 is that the welding track based on machine vision of the present invention is proofreaied and correct Special testing device control circuit figure.
Fig. 5 is that the welding track based on machine vision of the present invention is proofreaied and correct Special testing device human-computer interaction interface figure.
Fig. 6 is the control software architecture diagram that the welding track based on machine vision of the present invention is proofreaied and correct Special testing device.
In Fig. 2 and Fig. 3,1-workbench (frame structure), 2-wheel, 3-vertical supports, 4-horizontal support, 5-x direction of principal axis driver element, 6-y direction of principal axis driver element, 7-x direction of principal axis position detection unit (the first linear grid ruler), 8-y direction of principal axis position detection unit (the second linear grid ruler), 9-industrial camera, 10-camera lens, 11-light source, 12-industrial control host, 13-motion controller, 14-the first AC servo driver, 15-the second AC servo driver, 16-bus communication card, 17-display.
The specific embodiment
Embodiment 1:
As shown in Figures 2 and 3, the welding track based on machine vision of the present embodiment is proofreaied and correct Special testing device, comprise workbench 1, precision positioning mechanism, machine vision collecting device and control appliance, described workbench 1 adopts frame structure 1, the frame structure that this frame structure 1 is 1000*800*700mm, adopt 40*40 standard aluminum section bar to form, its bottom is provided with four wheels 2 that can make workbench 1 move, one side is provided with vertical supports 3, in described vertical supports 3, be vertically fixed with horizontal support 4, described precision positioning mechanism is arranged in the top planes of frame structure 1, described control appliance is arranged on the inside of frame structure 1, described machine vision collecting device is fixed on horizontal support 4, described machine vision collecting device is positioned at the top of precision positioning mechanism, described precision positioning mechanism comprises x direction of principal axis driver element 5, y direction of principal axis driver element 6, x direction of principal axis position detection unit 7 and y direction of principal axis position detection unit 8,
Described x direction of principal axis driver element 5 comprises the first AC servo motor 5-1, the first shaft coupling 5-2 and the first ball screw 5-3 that connect successively, is provided with x direction of principal axis travelling carriage 5-4 on described the first ball screw 5-3; Described y direction of principal axis driver element 6 comprises the second AC servo motor 6-1, the second shaft coupling 6-2 and the second ball screw 6-3 that connect successively, is provided with y direction of principal axis travelling carriage 6-4 on described the second ball screw 6-3; It is upper that described y direction of principal axis driver element 6 is placed in x direction of principal axis travelling carriage 5-4, and described y direction of principal axis travelling carriage 6-4 is used for placing welding work pieces in the time of test; Described x direction of principal axis position detection unit 7 and y direction of principal axis position detection unit 8 adopt respectively the first linear grid ruler 7 and the second linear grid ruler 8, described the first linear grid ruler 7 is arranged on a side of x direction of principal axis driver element 5, and described the second linear grid ruler 8 is arranged on a side of y direction of principal axis driver element 6;
Described machine vision collecting device comprises industrial camera 9, camera lens 10 and light source 11, and described camera lens 10 is connected with industrial camera 9 and aims at precision positioning mechanism, and described light source 11 is distributed in camera lens 10 around;
Described control appliance comprises industrial control host 12, motion controller 13, the first AC servo driver 14 and the second AC servo driver 15.
In the present embodiment, the HC-KFS-23A model motor that described the first AC servo motor 5-1 is Japanese mitsubishi electric Co., Ltd, the HC-KFS-43A model motor that described the second AC servo motor 6-1 is Japanese mitsubishi electric Co., Ltd; Described the first ball screw 5-3 and the second ball screw 6-3 all adopt the KK6005P-600A1-FE-CS2 model screw mandrel of Taiwan Shang Yin Co., Ltd, and its helical pitch is 5mm, and effectively rail length is 600mm, and precision is ± 0.01mm; Described the first linear grid ruler 7 and the second linear grid ruler 8 all adopt the Spain MKT-52 of Fa Ge FAGOR company model, and effective travel is 520mm, and resolution ratio is 5um, and precision is ± 10um; Described industrial camera 9 adopts 800,000 pixel 1394 cameras of German Ying Meijing Co., Ltd (IMAGINGSOURCE), model is DMK31AF03, resolution ratio is 1024x768, Pixel Dimensions horizontal direction is 4.65um, vertical direction is 4.65um, camera lens 10 adopts the M2514-MP2 model mega pixel camera lens of Japanese Computar company, and focal length is 25mm; GTS-400-PV (G)-PCI movement sequence controller that described motion controller adopts solid High Seience Technology Co., Ltd. to produce; Described the first AC servo driver 14 adopts the MR-J2S-20A model servo-driver of Japanese mitsubishi electric Co., Ltd, and described the second AC servo driver 15 adopts the MR-J2S-40A model servo-driver of Japanese mitsubishi electric Co., Ltd.
Proofread and correct Special testing device control circuit figure in conjunction with the welding track based on machine vision shown in Fig. 4, described the first AC servo driver 14 is connected with the first AC servo motor 5-1, described the second AC servo driver 15 is connected with the second AC servo motor 6-1, described the first AC servo driver 14 and the second AC servo driver 15 are set up communication by motion controller 13 and industrial control host 12 respectively, described the first linear grid ruler 7 is connected with motion controller 13 with CN13 communication interface by CN12 respectively with the second linear grid ruler 8, described industrial control host 12 is connected with industrial camera 9 by 1394 bus communication cards 16, described industrial control host 12 is connected with display 17, can realize man-machine interaction, set the kinematic parameter of x axle and y axle by the man-machine interface shown in Fig. 5, motion controller 13 is exported pulse and direction signal to the first AC servo driver 14 and the second AC servo driver 15, drive the firstth AC servo motor 5-1 to drive x direction of principal axis travelling carriage 5-4, and drive the second AC servo motor 6-1 to drive y direction of principal axis travelling carriage 6-4 to arrive anchor point, the first linear grid ruler 7 and the second linear grid ruler 8 detect the x shaft position signal of x direction of principal axis travelling carriage 5-4 and the y shaft position signal of y direction of principal axis travelling carriage 6-4, and be input to motion controller 13 through 2 tunnel quadruple increment type auxiliaring coding devices, can obtain testing result in man-machine interface.
As shown in Figure 6, described industrial control host 12 is used Control System Software, and this software adopts Microsoft VisualStudio2005 platform development, is divided into four levels, and first level is Drivers Library, is provided by each equipment supplier; Second level is communication and monitoring programme, comprises monitoring module, communication module and fault diagnosis and alarm module, and it is responsible for real-time communication and operation monitoring between the each module of application program, and to diagnosing malfunction and warning; The 3rd level is control program layer, comprises motion-control module, position detecting module, Machine Vision Detection module and four parts of human-computer interaction module, and it is the core of whole control system; The 4th layer is primary control program layer, comprises main control module and file and data management module two parts, and wherein first, second, and third layer is real-time control module, and the 4th layer is coordinator, is non-real-time control routine.
The welding track based on machine vision of the present embodiment is proofreaied and correct the method for testing of Special testing device, it is characterized in that comprising the following steps:
1) adopt scaling board to demarcate, obtain industrial camera intrinsic parameter and outer parameter;
2) welding work pieces is positioned on the y direction of principal axis travelling carriage of precision positioning mechanism, according to the current location of welding work pieces, captures welding work pieces image and set up welding work pieces template by industrial camera;
3) set welding work pieces x axle and the y axle offset amount on workbench by industrial control host, moving control module for controlling the first AC servo motor and the first ball screw drive welding work pieces to move to the x axle offset amount position of setting, control the y axle offset amount position that the second AC servo motor and the second ball screw driving welding work pieces move to setting, obtain respectively x axle and the y axle real offset (x of current welding work pieces by the first linear grid ruler and the second linear grid ruler r, y r);
4) after welding work pieces skew, call Machine Vision Detection module, again capture the welding work pieces image of current location by industrial camera, and adopt image noise reduction algorithm to process image, specific as follows:
After welding work pieces skew, again capture the welding work pieces image of current location by industrial camera, this image is 24bit coloured image, transfer the gray level image of 256 grades to by image binaryzation, Machine Vision Detection module adopts mean filter to complete noise reduction process again, wherein mean filter mask size is m × n, and in image, any point (x, y) response is:
g ( x , y ) = 1 mn ( &Sigma; i = - a a &Sigma; j = - b b f ( x + i , y + j ) )
Wherein, g (x, y) is mask pixel average,
Figure BDA0000466542580000072
5) Machine Vision Detection module adopts the template matching algorithm based on gray value, obtains x axle and the y axial side-play amount (x of welding work pieces with respect to template workpiece m, y m), specific as follows:
A) adopt the template matching algorithm based on gray value, by calculating normalizated correlation coefficient NCC, determine the similarity of current welding work pieces image and template image coupling, determine thus welding work pieces with respect to the side-play amount of template workpiece x axle and y axle in image coordinate system (x ' m, y ' m):
NCC ( x , y ) = 1 n &Sigma; ( i , j ) &Element; T t ( i , j ) - m t s t 2 &CenterDot; f ( x + i , y + j ) - m f ( x , y ) s f 2 ( x , y )
Wherein, t (i, j) is welding work pieces template gray value, and f (x+i, y+j) is current welding work pieces gradation of image value, m ttemplate average gray value,
Figure BDA0000466542580000075
the variance of all gray values of template, m f(x, y) and s f(x, y) is average gray value and the variance of each point in the current welding work pieces template of translation; In the time of normalizated correlation coefficient NCC=± 1, between welding work pieces template and current welding work pieces image, mate completely, and normalizated correlation coefficient NCC absolute value more approaches 1, represent that welding work pieces template is more approaching with the welding work pieces image detecting;
B) industrial camera obtains intrinsic parameter and outer parameter after demarcating, x axle above-mentioned steps a) being obtained through seven submatrixs conversion and affine transformation and the side-play amount of y axle (x ' m, y ' m) be converted to x axle and y axle offset amount (x in tool coordinates system m, y m);
6) compare (x r, y r) and (x m, y m) value, reproduce process allowable error according to welding robot, judge whether the precision of Machine Vision Detection meets the demands, judge whether to meet | x m - x r | < [ &Delta;x ] | y m - y r | < [ &Delta;y ] , Wherein Δ x and Δ y are the error that welding system allows; If meet the demands, Machine Vision Detection module can be integrated in industrial robot control system and apply; If do not meet the demands, the reason that analytical error produces, is optimized from industrial camera demarcation, image noise reduction Processing Algorithm and template matching algorithm, improves the certainty of measurement of Machine Vision Detection module, thereby meets instructions for use.
In sum, welding track based on machine vision correction Special testing device of the present invention can be realized based on machine vision technique and complete welding work pieces track in x axle and the detection of y direction of principal axis side-play amount, and testing result is assessed and verified, the reason that analytical error produces, continue to optimize the image processing method in machine vision technique, thereby realize the object that welding track side-play amount accurately detects.
The above; it is only patent preferred embodiment of the present invention; but the protection domain of patent of the present invention is not limited to this; anyly be familiar with those skilled in the art in the disclosed scope of patent of the present invention; according to the present invention, the technical scheme of patent and inventive concept thereof are equal to replacement or are changed, and all belong to the protection domain of patent of the present invention.

Claims (10)

1.基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：包括工作台、精密定位机构、机器视觉采集设备和控制设备，所述精密定位机构和机器视觉采集设备分别与控制设备连接，所述精密定位机构、机器视觉采集设备和控制设备设置在工作台上，所述机器视觉采集设备位于精密定位机构的上方；所述精密定位机构包括x轴方向驱动单元、y轴方向驱动单元、x轴方向位置检测单元以及y轴方向位置检测单元；在测试时，所述y轴方向驱动单元带动焊接工件沿y轴方向移动，所述x轴方向驱动单元带动y轴方向驱动单元使焊接工件沿x轴方向移动。1. The special test device for welding trajectory correction based on machine vision is characterized in that: it comprises workbench, precision positioning mechanism, machine vision acquisition equipment and control equipment, and described precision positioning mechanism and machine vision acquisition equipment are connected with control equipment respectively, so The precision positioning mechanism, machine vision acquisition equipment and control equipment are arranged on the workbench, and the machine vision acquisition equipment is located above the precision positioning mechanism; the precision positioning mechanism includes x-axis direction drive unit, y-axis direction drive unit, x A position detection unit in the axial direction and a position detection unit in the y-axis direction; during testing, the driving unit in the y-axis direction drives the welding workpiece to move along the y-axis direction, and the driving unit in the x-axis direction drives the driving unit in the y-axis direction to make the welding workpiece move along the y-axis direction. Move in the x-axis direction. 2.根据权利要求1所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述x轴方向驱动单元包括依次连接的第一交流伺服电机、第一联轴器和第一滚珠丝杆，所述第一滚珠丝杆上设置有x轴方向移动台；所述y轴方向驱动单元包括依次连接的第二交流伺服电机、第二联轴器和第二滚珠丝杆，所述第二滚珠丝杆上设置有y轴方向移动台；所述y轴方向驱动单元置于x轴方向移动台上，所述y轴方向移动台在测试时用于放置焊接工件；所述x轴方向位置检测单元和y轴方向位置检测单元分别采用第一线性光栅尺和第二线性光栅尺，所述第一线性光栅尺设置在x轴方向驱动单元的一侧，所述第二线性光栅尺设置在y轴方向驱动单元的一侧。2. The special test device for welding trajectory correction based on machine vision according to claim 1, characterized in that: the drive unit in the x-axis direction includes a first AC servo motor, a first coupling and a first ball connected in sequence screw, the first ball screw is provided with a moving table in the x-axis direction; the drive unit in the y-axis direction includes a second AC servo motor, a second coupling, and a second ball screw connected in sequence, and the The second ball screw is provided with a y-axis direction moving table; the y-axis direction driving unit is placed on the x-axis direction moving table, and the y-axis direction moving table is used to place welding workpieces during testing; the x-axis The direction position detection unit and the y-axis direction position detection unit respectively adopt a first linear grating ruler and a second linear grating ruler, the first linear grating ruler is arranged on one side of the drive unit in the x-axis direction, and the second linear grating ruler It is arranged on one side of the drive unit in the y-axis direction. 3.根据权利要求2所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述机器视觉采集设备包括工业相机、镜头和光源，所述镜头与工业相机连接且对准精密定位机构，所述光源分布在镜头的周围。3. The special test device for welding trajectory correction based on machine vision according to claim 2, characterized in that: the machine vision acquisition device includes an industrial camera, a lens and a light source, and the lens is connected with the industrial camera and aligned with precise positioning mechanism, the light source is distributed around the lens. 4.根据权利要求3所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述控制设备包括工控主机、运动控制器、第一交流伺服驱动器和第二交流伺服驱动器，所述第一交流伺服驱动器与第一交流伺服电机连接，所述第二交流伺服驱动器与第二交流伺服电机连接，所述第一交流伺服驱动器和第二交流伺服驱动器分别通过运动控制器与工控主机建立通讯，所述第一线性光栅尺和第二线性光栅尺分别通过通讯接口与运动控制器连接，所述工控主机通过总线通讯卡与工业相机连接，所述工控主机连接有用于实现人机交互的显示器。4. The special test device for welding trajectory correction based on machine vision according to claim 3, characterized in that: the control equipment includes an industrial control host, a motion controller, a first AC servo driver and a second AC servo driver, the The first AC servo driver is connected to the first AC servo motor, the second AC servo driver is connected to the second AC servo motor, and the first AC servo driver and the second AC servo driver are respectively established with the industrial control host through a motion controller. communication, the first linear grating ruler and the second linear grating ruler are respectively connected to the motion controller through the communication interface, the industrial control host is connected to the industrial camera through the bus communication card, and the industrial control host is connected with a monitor. 5.根据权利要求1所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述工作台采用框架结构，该框架结构的一侧设置有竖向支架，在所述竖向支架上垂直固定有横向支架，所述精密定位机构设置在框架结构的顶部平面上，所述控制设备设置在框架结构的内部，所述机器视觉采集设备固定在横向支架上。5. The special test device for welding track correction based on machine vision according to claim 1, characterized in that: the workbench adopts a frame structure, one side of the frame structure is provided with a vertical bracket, and the vertical bracket A horizontal bracket is vertically fixed on the top, the precision positioning mechanism is set on the top plane of the frame structure, the control equipment is set inside the frame structure, and the machine vision acquisition equipment is fixed on the horizontal bracket. 6.根据权利要求5所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述框架结构的底部设置有四个可使工作台移动的轮子。6. The special test device for welding trajectory correction based on machine vision according to claim 5, characterized in that: the bottom of the frame structure is provided with four wheels that can move the workbench. 7.根据权利要求5所述的基于机器视觉的焊接轨迹校正专用测试装置，其特征在于：所述工作台采用的框架结构为1000*800*700mm的框架结构。7. The special test device for welding track correction based on machine vision according to claim 5, characterized in that: the frame structure adopted by the workbench is a frame structure of 1000*800*700mm. 8.基于机器视觉的焊接轨迹校正专用测试装置的测试方法，其特征在于包括以下步骤：8. The test method of the special test device for welding trajectory correction based on machine vision, characterized in that it comprises the following steps: 1)采用标定板进行标定，获得工业相机内参数和外参数；1) Use the calibration board for calibration to obtain the internal and external parameters of the industrial camera; 2)将焊接工件放置于精密定位机构的y轴方向移动台上，根据焊接工件的当前位置，通过工业相机抓取焊接工件图像并建立焊接工件模板；2) Place the welding workpiece on the y-axis direction mobile platform of the precision positioning mechanism, capture the image of the welding workpiece through an industrial camera and establish a welding workpiece template according to the current position of the welding workpiece; 3)通过工控主机设定工作台上的焊接工件x轴和y轴偏移量，控制第一交流伺服电机和第一滚珠丝杆驱动焊接工件移动到设定的x轴偏移量位置，控制第二交流伺服电机和第二滚珠丝杆驱动焊接工件移动到设定的y轴偏移量位置，通过第一线性光栅尺和第二线性光栅尺分别获得当前焊接工件的x轴和y轴实际偏移量(xr，yr)；3) Set the x-axis and y-axis offsets of the welding workpiece on the workbench through the industrial control host, control the first AC servo motor and the first ball screw to drive the welding workpiece to the set x-axis offset position, and control The second AC servo motor and the second ball screw drive the welding workpiece to move to the set y-axis offset position, and obtain the x-axis and y-axis actual values of the current welding workpiece through the first linear grating scale and the second linear grating scale respectively. offset(x r , y r ); 4)在焊接工件偏移后，通过工业相机重新抓取当前位置的焊接工件图像，并采用图像降噪算法对图像进行处理；4) After the welding workpiece is shifted, the image of the welding workpiece at the current position is recaptured through the industrial camera, and the image is processed by image noise reduction algorithm; 5)采用基于灰度值的模板匹配算法，获取焊接工件相对于模板工件的x轴和y轴方向的偏移量(xm，ym)；5) Using a gray value-based template matching algorithm to obtain the offset (x m , y m ) of the welding workpiece relative to the template workpiece in the x-axis and y-axis directions; 6)比较(xr，yr)和(xm，ym)的值，根据焊接机器人再现过程允许误差，判断机器视觉检测的精度是否满足要求，即判断是否满足 | x m - x r | < [ &Delta;x ] | y m - y r | < [ &Delta;y ] , 其中Δx和Δy为焊接系统允许的误差；若满足要求，则可集成到工业机器人控制系统中应用；若不满足要求，则分析误差产生的原因，从工业相机标定、图像降噪处理算法和模板匹配算法进行优化，提高测量精度，从而满足使用要求。6) Compare the values of (x r , y r ) and (x m , y m ), and judge whether the accuracy of machine vision detection meets the requirements according to the allowable error of the welding robot reproduction process, that is, judge whether it meets the requirements | x m - x r | < [ &Delta;x ] | the y m - the y r | < [ &Delta;y ] , Among them, Δx and Δy are the allowable errors of the welding system; if the requirements are met, they can be integrated into the industrial robot control system for application; if the requirements are not met, the reasons for the errors are analyzed, from industrial camera calibration, image noise reduction processing algorithms and templates The matching algorithm is optimized to improve the measurement accuracy, so as to meet the requirements of use. 9.根据权利要求8所述的基于机器视觉的焊接轨迹校正专用测试装置的测试方法，其特征在于：步骤4)具体如下：9. the testing method of the welding locus correction special-purpose testing device based on machine vision according to claim 8, is characterized in that: step 4) is specifically as follows: 在焊接工件偏移后，通过工业相机重新抓取当前位置的焊接工件图像，该图像为24bit彩色图像，通过图像二值化转为256个等级的灰度图像，再采用均值滤波器完成降噪处理，其中均值滤波掩膜大小为m×n，图像中任意一点(x，y)响应为：After the welding workpiece is shifted, the image of the welding workpiece at the current position is re-captured through the industrial camera. The image is a 24bit color image, which is converted into a 256-level grayscale image through image binarization, and then the mean value filter is used to complete the noise reduction Processing, where the size of the mean filter mask is m×n, and the response of any point (x, y) in the image is: gg (( xx ,, ythe y )) == 11 mnmn (( &Sigma;&Sigma; ii == -- aa aa &Sigma;&Sigma; jj == -- bb bb ff (( xx ++ ii ,, ythe y ++ jj )) )) 其中，g(x，y)是掩膜像素平均值，
Figure FDA0000466542570000031
Among them, g(x, y) is the average value of mask pixels,
Figure FDA0000466542570000031
 10.根据权利要求8所述的基于机器视觉的焊接轨迹校正专用测试装置的测试方法，其特征在于：步骤5)具体如下：10. The testing method of the welding trajectory correction special testing device based on machine vision according to claim 8, characterized in that: step 5) is specifically as follows: a)采用基于灰度值的模板匹配算法，通过计算归一化相关系数NCC，确定当前焊接工件图像和模板图像匹配的相似度，由此确定焊接工件相对于模板工件在图像坐标系中x轴和y轴的偏移量(x′m，y′m)：a) Using the template matching algorithm based on the gray value, by calculating the normalized correlation coefficient NCC, determine the similarity between the current welding workpiece image and the template image matching, thereby determining the x-axis of the welding workpiece relative to the template workpiece in the image coordinate system and the offset of the y-axis (x′ m , y′ m ): NCCNCC (( xx ,, ythe y )) == 11 nno &Sigma;&Sigma; (( ii ,, jj )) &Element;&Element; TT tt (( ii ,, jj )) -- mm tt sthe s tt 22 &CenterDot;&CenterDot; ff (( xx ++ ii ,, ythe y ++ jj )) -- mm ff (( xx ,, ythe y )) sthe s ff 22 (( xx ,, ythe y )) 其中，t(i，j)为焊接工件模板灰度值，f（x+i，y+j)为当前焊接工件图像灰度值，mt是模板平均灰度值，
Figure FDA0000466542570000033
是模板所有灰度值的方差，mf(x，y)和mf(x，y)为平移当前焊接工件模板中各点的平均灰度值和方差；当归一化相关系数NCC=±1时，焊接工件模板与当前焊接工件图像之间完全匹配，而归一化相关系数NCC绝对值越接近1，表示焊接工件模板与正在检测的焊接工件图像越接近；Wherein, t (i, j) is the gray value of the welding workpiece template, f (x+i, y+j) is the gray value of the current welding workpiece image, m t is the average gray value of the template,
Figure FDA0000466542570000033
is the variance of all the gray values of the template, m f (x, y) and m f (x, y) are the average gray value and variance of each point in the current welding workpiece template; when the normalized correlation coefficient NCC=±1 When , the welding workpiece template is completely matched with the current welding workpiece image, and the closer the absolute value of the normalized correlation coefficient NCC is to 1, the closer the welding workpiece template is to the welding workpiece image being detected; b)工业相机标定后获得内参数和外参数，经过七次矩阵变换和仿射变换将上述步骤a)获得的x轴和y轴的偏移量(x′m，y′m)转换为工具坐标系中x轴和y轴偏移量(xm，ym)。b) After the industrial camera is calibrated, the internal parameters and external parameters are obtained, and the offsets (x′ m , y′ m ) of the x-axis and y-axis obtained in the above step a) are converted into tools through seven matrix transformations and affine transformations The x-axis and y-axis offset in the coordinate system (x m , y m ).
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