CN115106260A - Automatic gluing and detecting method based on 3D vision - Google Patents
Automatic gluing and detecting method based on 3D vision Download PDFInfo
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- CN115106260A CN115106260A CN202210825722.5A CN202210825722A CN115106260A CN 115106260 A CN115106260 A CN 115106260A CN 202210825722 A CN202210825722 A CN 202210825722A CN 115106260 A CN115106260 A CN 115106260A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1005—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to condition of liquid or other fluent material already applied to the surface, e.g. coating thickness, weight or pattern
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1015—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to a conditions of ambient medium or target, e.g. humidity, temperature ; responsive to position or movement of the coating head relative to the target
- B05C11/1018—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to a conditions of ambient medium or target, e.g. humidity, temperature ; responsive to position or movement of the coating head relative to the target responsive to distance of target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
-
- 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
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention belongs to the field of glue coating detection processes in the industrial field, and particularly relates to an automatic glue coating and detection method based on 3D vision, aiming at the problem that the quality of an adhesive tape is detected in real time by two or three 2D cameras, because the 2D cameras are greatly influenced by illumination, the detection is easy to make mistakes, and the detection can be carried out only after the glue coating is finished, so that the beat is increased; the automatic gluing and detecting method based on the 3D vision is provided, an embedded platform is arranged in the 3D vision, point cloud data can be output in real time through a network, glue height, glue width and glue volume can be effectively detected, abnormal conditions such as glue breaking, glue leakage and wire drawing can be efficiently and accurately judged, and the production efficiency of enterprises is improved.
Description
Technical Field
The invention relates to the technical field of gluing detection processes in the industrial field, in particular to an automatic gluing and detecting method based on 3D vision; the method is widely applied to automobiles, electronic products and the like.
Background
With the rapid development of industrial production in China and the rapid improvement of the automation degree, the automatic gluing system gradually replaces manual gluing. The automatic gluing detection system on the market at present is divided into 2 types, the first type is to detect the quality of the adhesive tape in real time through two or three 2D cameras, because the 2D cameras are greatly influenced by illumination, the detection is easy to make mistakes, and the detection can be carried out only after the glue is coated, so that the beat is increased; the second is a plurality of cameras add a plurality of lasers, but needs every camera all to link to each other with the industrial computer is direct, and the winding displacement is more in disorder, has restricted industrial robot's working range, and can appear camera line joint and become flexible scheduling problem easily.
Disclosure of Invention
The automatic gluing and detecting method based on the 3D vision solves the problem that the quality of an adhesive tape is detected in real time through two or three 2D cameras in the prior art, and because the 2D cameras are greatly influenced by illumination, detection errors are easy to occur, and the detection can be performed only after the adhesive is coated, so that the beat is increased; the cameras and the lasers are required to be directly connected with the industrial personal computer, so that the wiring is disordered, the working range of the industrial robot is limited, and the problems that the line joints of the cameras are easy to loosen and the like can occur; the glue height, the glue width and the glue volume can be effectively detected, and the abnormal conditions such as glue breaking, glue leakage and wire drawing can be accurately judged efficiently.
In order to achieve the purpose, the invention adopts the following technical scheme:
an automatic gluing and detecting method based on 3D vision comprises the following steps:
s1: the 3D vision sensor is arranged at the tail end of a mechanical arm of the industrial robot, and is calibrated according to the robot and the 3D vision sensor before the system works;
s2: before the system works, dividing a path to be detected into N sections according to a gluing process, teaching the path to be detected by a robot, setting a signal point at each gluing completion position, and outputting a glue section number, a glue gun tail end pose, a glue gun pressure value and the like to upper computer vision software when a robot program is executed to the signal point position;
s3: before the system works, according to the glue segment information of S2, the upper computer vision software sets relevant parameters respectively;
s4: when the system works, the upper computer vision software opens the four cameras on the 3D vision sensor and sets the four laser lines to be normally bright;
s5: selecting two cameras in the gluing direction to collect images according to the glue segment parameters preset in S3, respectively extracting laser line data in the two camera images by using a 3D vision sensor, respectively generating point cloud data, and transmitting the point cloud data to upper computer software in real time;
s6: the method comprises the following steps that visual software of an upper computer receives point cloud data transmitted by a 3D sensor in real time, on one hand, the distance from a glue gun to a gluing position point is calculated according to the point cloud data of a front-end camera along a gluing direction, and the offset in the Z direction is calculated through a pid algorithm according to the calculated height in the Z direction and the preset height in the Z direction;
s7: calculating glue height, glue width and glue volume in real time by upper computer software according to point cloud data of a rear-end camera, wherein the glue height is the maximum height from a reference surface, the glue width is the projection of the glue strip on the reference surface, and the glue volume is calculated by a tangent plane method;
s8: and repeating the step S5 to realize real-time detection.
Preferably, in S1, the 3D vision sensor is provided with four cameras and four laser lines inside, the four cameras are distributed on the circumference at 90 degrees, the laser projection mode is vertical incidence mode, i.e., the incident light is vertical to the measured surface, the cameras acquire laser line images from the other side in an inclined manner, and the 3D vision sensor is provided with an embedded platform inside, which can receive images in real time and generate three-dimensional point cloud data, and transmit the three-dimensional point cloud data to the upper computer through a network.
Preferably, in S2, the upper computer is connected to the 3D vision sensor and the robot through a network cable, respectively.
Preferably, in S7, the upper computer software calculates the glue height, the glue width, and the glue volume in real time according to the point cloud data of the rear-end camera, where the glue height is the maximum height from the reference surface, the glue width is the projection of the glue strip on the reference surface, and the glue volume is calculated by a tangent plane method, and if the calculated glue height, glue width, and glue volume exceed the preset parameter range, the glue strip quality is considered to be unqualified, and the current glue strip NG is displayed on the upper computer vision software, and meanwhile, the upper computer software performs real-time splicing according to the point cloud data of the rear-end camera and the operating speed of the robot end glue gun, and the point cloud data of the glue strip NG displays red, so that an operator can conveniently judge the error position of the glue strip.
Preferably, in S1, the 3D vision sensor is installed at the end of a mechanical arm of the industrial robot, and before the system works, calibration is performed according to the robot and the 3D vision sensor, where the calibration method is a triangulation principle.
Preferably, in S3, before the system works, the upper computer vision software sets the glue height, glue width, glue product range, camera number, exposure, gain, Z-direction threshold, and other relevant parameters of each glue segment according to the glue segment information of S1.
Preferably, in S6, the upper computer vision software receives the point cloud data transmitted by the 3D sensor in real time, calculates, along the gluing direction, a distance from the glue gun to the gluing position point according to the point cloud data of the front-most camera, calculates an offset in the Z direction by a pid algorithm according to the calculated Z-direction height and a preset Z-direction height, and modifies the pose information of the end of the glue gun if the offset exceeds a preset range.
Preferably, the unqualified gluing quality includes abnormal conditions such as glue breaking, glue leakage and wire drawing. Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the 3D vision sensor is connected with the upper computer through the network cable, so that the connection of a plurality of cameras with the upper computer is avoided, and the wiring complexity is reduced. Whether the adhesive tape is qualified or not is detected in the gluing process, and compared with the prior art that the adhesive tape is coated firstly and then detected, the working cycle is greatly reduced. According to different gluing processes, the method is suitable for a plurality of gluing tracks and can detect gluing sections. Host computer vision software can show in real time whether height, gluey width, colloid volume and current adhesive tape of gluing of current adhesive tape are qualified to carry out splice display with real-time detection's adhesive tape, carry out the red processing of mark to unqualified adhesive tape, make things convenient for operating personnel to know the current rubber coated condition directly perceived, improved enterprise production efficiency.
The invention can effectively detect the glue height, the glue width and the glue volume, efficiently and accurately judge abnormal conditions such as glue breaking, glue leakage, wire drawing and the like, improves the production efficiency of enterprises, reduces the production cost and increases the competitiveness of the enterprises.
Drawings
Fig. 1 is a flowchart of an automatic gluing and detecting method based on 3D vision according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments.
Referring to fig. 1, an automatic gluing and detecting method based on 3D vision includes the following steps:
s1: the 3D vision sensor is arranged at the tail end of a mechanical arm of the industrial robot, and is calibrated according to the robot and the 3D vision sensor before the system works;
s2: before the system works, dividing a path to be detected into N sections according to a gluing process, teaching the path to be detected by a robot, setting a signal point at each gluing completion position, and outputting a glue section number, a glue gun tail end pose, a glue gun pressure value and the like to upper computer vision software when a robot program is executed to the signal point position;
s3: before the system works, according to the glue segment information of S1, the upper computer vision software sets relevant parameters respectively;
s4: when the system works, the upper computer vision software opens the four cameras on the 3D vision sensor and sets the four laser lines to be normally bright;
s5: selecting two cameras in the gluing direction to collect images according to the glue segment parameters preset in S3, respectively extracting laser line data in the two camera images by using a 3D vision sensor, respectively generating point cloud data, and transmitting the point cloud data to upper computer software in real time;
s6: the method comprises the following steps that visual software of an upper computer receives point cloud data transmitted by a 3D sensor in real time, on one hand, the distance from a glue gun to a gluing position point is calculated according to the point cloud data of a front-end camera along a gluing direction, and the offset in the Z direction is calculated through a pid algorithm according to the calculated height in the Z direction and the preset height in the Z direction;
s7: calculating glue height, glue width and glue volume in real time by upper computer software according to point cloud data of a rear-end camera, wherein the glue height is the maximum height from a reference surface, the glue width is the projection of the glue strip on the reference surface, and the glue volume is calculated by a tangent plane method;
s8: and repeating the step S5 to realize real-time detection.
In this embodiment, in S1, the 3D vision sensor is equipped with four cameras and four laser lines, the four cameras are distributed on the circumference at 90 degrees, the laser projection mode is vertical incidence mode, that is, the incident light is perpendicular to the measured surface, the cameras acquire laser line images from the other side in an inclined manner, and the 3D vision sensor is equipped with an embedded platform, which can receive images in real time and generate three-dimensional point cloud data, and transmit the three-dimensional point cloud data to the host computer through the network.
In this embodiment, in S2, the upper computer is connected to the 3D vision sensor and the robot through the network cable, respectively.
In this embodiment, in S7, the upper computer software calculates the glue height, the glue width, and the glue volume in real time according to the point cloud data of the rear-end camera, where the glue height is the maximum height from the reference surface, the glue width is the projection of the glue strip on the reference surface, and the glue volume is calculated by a tangent plane method.
In this embodiment, in S1, the 3D vision sensor is installed at the end of a mechanical arm of an industrial robot, and before the system works, calibration is performed according to the robot and the 3D vision sensor, where the calibration method is a triangulation principle.
In this embodiment, in S3, before the system works, according to the glue segment information of S2, the upper computer vision software sets the glue height, glue width, glue product range, camera number, exposure, gain, Z-direction threshold, and other relevant parameters of each glue segment.
In this embodiment, in S6, the upper computer vision software receives the point cloud data transmitted by the 3D sensor in real time, and along the gluing direction, on one hand, calculates the distance from the glue gun to the gluing position point according to the point cloud data of the front-end camera, calculates the offset in the Z direction through the pid algorithm according to the calculated Z-direction height and the preset Z-direction height, and modifies the pose information of the end of the glue gun if the offset exceeds the preset range.
In this embodiment, the unqualified gluing quality includes abnormal conditions such as glue breaking, glue leakage, wire drawing and the like.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. An automatic gluing and detecting method based on 3D vision is characterized by comprising the following steps:
s1: the 3D vision sensor is arranged at the tail end of a mechanical arm of the industrial robot, and is calibrated according to the robot and the 3D vision sensor before the system works;
s2: before the system works, dividing a path to be detected into N sections according to a gluing process, teaching the path to be detected by a robot, setting a signal point at each gluing completion position, and outputting a glue section number, a glue gun tail end pose and a glue gun pressure value to upper computer vision software when a robot program is executed to the signal point position;
s3: before the system works, according to the glue segment information of S2, the upper computer vision software sets relevant parameters respectively;
s4: when the system works, the upper computer vision software opens the four cameras on the 3D vision sensor and sets the four laser lines to be normally bright;
s5: selecting two cameras in the gluing direction to collect images according to the glue segment parameters preset in S3, respectively extracting laser line data in the two camera images by using a 3D vision sensor, respectively generating point cloud data, and transmitting the point cloud data to upper computer software in real time;
s6: the upper computer vision software receives the point cloud data transmitted by the 3D sensor in real time, on one hand, the distance from a glue gun to a gluing position point is calculated according to the point cloud data of the most front camera along the gluing direction, and the offset in the Z direction is calculated through a pid algorithm according to the calculated height in the Z direction and the preset height in the Z direction;
s7: calculating glue height, glue width and glue volume in real time by upper computer software according to point cloud data of a rear-end camera, wherein the glue height is the maximum height from a reference surface, the glue width is the projection of the glue strip on the reference surface, and the glue volume is calculated by a tangent plane method;
s8: and repeating the step S5 to realize real-time detection.
2. The automatic gluing and detecting method based on the 3D vision as claimed in claim 1, wherein in S1, the 3D vision sensor is provided with four cameras and four laser lines, the four cameras are distributed on the circumference at 90 degrees, and the 3D vision sensor is provided with an embedded platform capable of receiving images in real time and generating three-dimensional point cloud data and transmitting the three-dimensional point cloud data to an upper computer through a network.
3. The automatic gluing and detecting method based on 3D vision as claimed in claim 1, wherein in S2, the upper computer is connected with the 3D vision sensor and the robot through a net cord respectively.
4. The automatic gluing and detecting method based on 3D vision as claimed in claim 1, wherein in S7, the upper computer software calculates glue height, glue width and glue volume in real time according to the point cloud data of the rear-end camera, wherein the glue height is the maximum height from a reference surface, the glue width is the projection of the glue strip on the reference surface, the glue volume is calculated by a tangent plane method, if the calculated glue height, glue width and glue volume exceed the preset parameter range, the quality of the glue strip is considered to be unqualified, the current glue strip NG is displayed on the upper computer vision software, meanwhile, the upper computer software carries out real-time splicing according to the point cloud data of the rear-end camera and the running speed of the robot end glue gun, the point cloud data of the glue strip displays red color, and an operator can conveniently judge the position where the glue strip is wrong.
5. The automatic gluing and detecting method based on 3D vision as claimed in claim 1, wherein in S1, the 3D vision sensor is installed at the end of the mechanical arm of the industrial robot, and before the system works, calibration is performed according to the robot and the 3D vision sensor, and the calibration method is a triangulation principle.
6. The automatic gluing and detecting method based on 3D vision as claimed in claim 1, wherein in S3, before the system works, according to the glue segment information of S2, the upper computer vision software sets the glue height, glue width, glue volume range, and camera number, exposure, gain, and Z-direction threshold related parameters of each glue segment respectively.
7. The automatic gluing and detecting method based on the 3D vision as claimed in claim 1, wherein in S6, the upper computer vision software receives the point cloud data transmitted by the 3D sensor in real time, along the gluing direction, on one hand, the distance from the glue gun to the gluing position point is calculated according to the point cloud data of the front-end camera, on the other hand, the offset in the Z direction is calculated through a pid algorithm according to the calculated height in the Z direction and the preset height in the Z direction, and if the offset exceeds the preset range, the pose information of the tail end of the glue gun is modified.
8. The automatic gluing and detecting method based on the 3D vision is characterized in that the unqualified gluing quality comprises the abnormal conditions of glue breaking, glue leakage and wire drawing.
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2022
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