CN110567963B - Alloy analysis visual positioning method and device and alloy analysis system - Google Patents
Alloy analysis visual positioning method and device and alloy analysis system Download PDFInfo
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- CN110567963B CN110567963B CN201911073340.6A CN201911073340A CN110567963B CN 110567963 B CN110567963 B CN 110567963B CN 201911073340 A CN201911073340 A CN 201911073340A CN 110567963 B CN110567963 B CN 110567963B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/254—Projection of a pattern, viewing through a pattern, e.g. moiré
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- 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
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
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- 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
Abstract
The invention discloses an alloy analysis visual positioning method, an alloy analysis visual positioning device and an alloy analysis system, wherein when a robot controls an image acquisition device to move towards a sample to be detected, the distance between the image acquisition device and the sample to be detected is obtained; wherein the image acquisition device is provided with a structured light source; if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image; extracting a plurality of structural light stripes from the sample image; determining an optimal detection point according to the central point set of each structural light stripe, and calculating the three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structured light stripes. According to the invention, the three-dimensional position coordinates of the optimal detection point can be calculated by only shooting one sample image in the detection area, the calculation amount is reduced, a complex image processing process is not needed, and the calculation and positioning efficiency is higher.
Description
Technical Field
The invention relates to the technical field of visual detection, in particular to an alloy analysis visual positioning method, an alloy analysis visual positioning device and an alloy analysis system.
Background
With the development of technologies such as optics, computers, image processing and the like, the optical non-contact measurement set has the advantages of high measurement speed, high measurement precision and the like, and is widely applied to various fields. For example, in the steel industry, due to the diversification of products, the production level of the steel wire rod tends to be automated and refined, and the alloy component analysis of the finished wire rod is needed to prevent different steel grades from being mixed.
When alloy analysis is carried out, a structured light measuring system is mostly adopted to position the optimal detection point on the surface of a sample at present, and the structured light measuring system mainly comprises a structured light projection device, a camera and an image acquisition and processing system. The measuring principle is that light with a certain structure, such as a point light source, a line light source or a grating, is projected to a measured object, the structured light is modulated by the surface information of the measured object to generate deformation, and a camera is used for acquiring a deformed structured light stripe image, so that the three-dimensional position information of an optimal detection point is obtained.
When a structured light measurement system is used for positioning and calculating an optimal detection point, a phase measurement method is generally adopted at present, and the principle of the method is to calculate a phase value of each pixel in an image through a plurality of grating fringe images with certain phase differences and then calculate three-dimensional information of an object according to the phase value. However, in the actual production process, the diameter variation ranges of the finished product wire rod and the finished product coil are large, namely 5mm to 34mm and 1.2m to 1.5m, and when the finished product wire rod and the finished product coil with different specifications are combined, at least three raster images of the light bars need to be shot to calculate a phase value, so that the calculation amount is large, and the positioning efficiency is low.
Disclosure of Invention
In order to solve the problems in the background art, the invention provides an alloy analysis visual positioning method, an alloy analysis visual positioning device and an alloy analysis system.
In a first aspect, the present invention provides a method for visual localization of alloy analysis, the method comprising:
when the robot controls the image acquisition equipment to move towards the sample to be detected, acquiring the distance between the image acquisition equipment and the sample to be detected; wherein the image acquisition device is provided with a structured light source;
if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image; the structural light generated by the structural light source is reflected by the surface of the sample to be detected and then received by the image acquisition equipment, so that the sample image comprises structural light stripes carrying the surface deformation characteristics of the sample to be detected;
extracting a plurality of structural light stripes from the sample image;
determining an optimal detection point according to the central point set of each structural light stripe, and calculating a three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structural light stripe.
Optionally, the extracting the plurality of structured light stripes from the sample image includes:
acquiring the brightness value of a pixel point in the sample image;
judging whether the brightness value is larger than a threshold value;
if the brightness value is larger than the threshold value, the pixel point is a target point;
and extracting all target points in the sample image to obtain a plurality of the structural light stripes.
Optionally, the determining a best detection point according to the set of central points of each of the structural light stripes includes:
screening out the most salient points of the surface of the sample to be measured in the shooting area of the image acquisition equipment according to the central point set of each structured light stripe and the deformation characteristic of the structured light generated by the modulation of the surface of the sample to be measured;
and taking the most salient point as the best detection point.
Optionally, screening out the most salient point on the surface of the sample to be measured in the shooting area of the image acquisition device includes:
sorting the y coordinates of each pixel point in the central point set to obtain the pixel point coordinate (x) corresponding to the maximum y coordinate valuei，yi) (ii) a Wherein the content of the first and second substances,iserial number for indicating structured light stripe，1≦iN, N is the number of structured light fringes extracted from the sample image;
calculating (x) by using a triangulation distance measuring method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be measuredi，yi) Corresponding depth coordinate Zi；
From the depth coordinate ZiAnd screening out a minimum depth coordinate, and taking a pixel point corresponding to the minimum depth coordinate as the most salient point.
Optionally, the acquiring the three-dimensional position coordinates of the best detection point includes:
acquiring a conversion relation between an image coordinate system and a world coordinate system;
obtaining the corresponding coordinates (X, Y) of the optimal detection point in the sample image in a world coordinate system according to the conversion relation;
and calculating the depth coordinate Z of the optimal detection point by using a triangular distance measurement method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be detected to obtain the three-dimensional position coordinate (X, Y, Z) of the optimal detection point.
Optionally, the method further comprises:
setting an interested area of the structured light stripe, wherein the interested area is a stripe area except for two side edge areas in the structured light stripe;
and forming the central point set by the pixel points included in the region of interest.
Optionally, the method further comprises: marking the best detection point in the sample image.
In a second aspect, the present invention further provides an alloy analysis visual positioning apparatus, for implementing the alloy analysis visual positioning method according to the first aspect, including an image acquisition device, a structural light source, a laser ranging sensor and a controller, wherein the alloy analysis visual positioning apparatus is connected to a robot, and the structural light source, the robot, the image acquisition device and the laser ranging sensor are respectively electrically connected to the controller; the laser ranging sensor is used for detecting the distance between the image acquisition equipment and a sample to be detected;
wherein the controller is configured to perform the following program steps:
controlling the image acquisition equipment to move towards the sample to be detected;
acquiring the distance between the image acquisition equipment and a sample to be detected;
if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image; the structural light generated by the structural light source is reflected by the surface of the sample to be detected and then received by the image acquisition equipment, so that the sample image comprises structural light stripes carrying the surface deformation characteristics of the sample to be detected;
extracting a plurality of structural light stripes from the sample image;
determining an optimal detection point according to the central point set of each structural light stripe, and calculating a three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structural light stripe.
Optionally, the device further comprises a bottom plate and an outer shield, wherein a front panel of the outer shield is transparent, and a rear end of the outer shield is fixed on the bottom plate; the image acquisition equipment and the structural light source are fixed on the bottom plate and are positioned inside the outer shield; the laser ranging sensor is arranged at the top of the outer shield.
Optionally, the axes of the image acquisition device and the structured light source are on the same vertical plane.
In a third aspect, the present invention further provides an alloy analysis system, which includes a robot, a support, an alloy analyzer, and the alloy analysis visual positioning apparatus according to the second aspect, wherein the robot is connected to the alloy analyzer through the support, the alloy analysis visual positioning apparatus is disposed on the support, the alloy analyzer and the alloy analysis visual positioning apparatus are disposed adjacent to each other and both face a sample to be measured, and the controller is further electrically connected to the alloy analyzer;
wherein the controller is configured to perform the following program steps:
controlling the robot to move so that the alloy analyzer moves to a position corresponding to the three-dimensional position coordinate of the optimal detection point;
and controlling the alloy analyzer to start so as to analyze the alloy at the optimal detection point.
The invention has the following beneficial effects: when the robot controls the image acquisition equipment to move towards the sample to be measured, the distance between the image acquisition equipment and the sample to be measured is obtained, and if the distance is equal to the preset distance, the image acquisition equipment can be moved to the optimal shooting position so as to ensure the shooting effect of the structured light stripes. The invention extracts a plurality of structural light stripes from the sample image, thereby separating the background from the structural light stripes so as to improve the accuracy and efficiency of positioning the optimal detection point in the subsequent image processing. After extracting a plurality of structural light stripes, acquiring coordinates of other pixel points except pixel points in edge areas at two sides in each structural light stripe to obtain a central point set of each structural light stripe, and determining the surface roughness of the sample to be detected by combining the deformation characteristic of structured light modulated by the surface of the sample to be detected according to the central point set of each structural light stripe so as to screen out an optimal detection point and finally obtain the three-dimensional position coordinate of the optimal detection point. According to the method and the device, the three-dimensional position coordinates of the optimal detection point can be calculated only by shooting one sample image in the detection area, the calculated amount is reduced, a complex image processing process is not needed, and the calculation and positioning efficiency is higher.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart illustrating a method for visual positioning of an alloy analysis according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an image of a sample with structured light stripes according to an embodiment of the present invention;
FIG. 3 is a schematic view of a sample image after marking the sweet spot according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating a detection principle of the depth coordinate Z of the optimal detection point according to an embodiment of the present invention;
FIG. 5 is a control flow diagram of an alloy analysis visual positioning apparatus according to another embodiment of the present invention;
FIG. 6 is a schematic front view of an alloy analysis visual positioning device according to another embodiment of the present invention;
FIG. 7 is a schematic structural diagram of the back side of an alloy analysis visual positioning device according to another embodiment of the present invention;
FIG. 8 is a schematic structural view of an alloy analysis system according to yet another embodiment of the present invention;
fig. 9 is a schematic view of a connection structure of a bracket, an alloy analysis visual positioning device and an alloy analyzer according to still another embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides an alloy analysis visual positioning method, including:
step S10, when the robot controls the image acquisition equipment to move towards the sample to be measured, the distance between the image acquisition equipment and the sample to be measured is obtained; wherein the image acquisition device is provided with a structured light source.
Because the invention adopts visual positioning, the image of the surface of the sample to be measured needs to be shot by the image acquisition equipment so as to determine the optimal detection point, so the robot can be used for controlling the image acquisition equipment to move towards the sample to be measured so as to adjust the relative position and distance between the image acquisition equipment and the sample to be measured, thereby the shooting position of the image acquisition equipment is positioned, and a distance measuring device can be selected to detect the distance between the image acquisition equipment and the sample to be measured, such as a laser distance meter, an optical fiber distance meter and the like, and the embodiment does not limit the distance measuring mode.
The image acquisition device in the invention can be an industrial camera, and the sample to be detected can be a wire rod or a coil or other samples needing alloy analysis, which is not limited in the invention. When the surface image of the sample is collected, the equipped light source is a structural light source which can generate structural light, and based on the characteristic principle that the structural light is modulated by the surface of the sample to be detected to generate deformation, the structural light is reflected by the surface of the sample to be detected and then is received by the image collecting equipment, so that the sample image shot by the image collecting equipment has structural light stripes carrying the real deformation characteristics of the surface of the sample.
And step S20, if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image.
Before alloy analysis is carried out, the preset distance can be preset according to the characteristics of a sample to be detected, so that the image acquisition equipment can acquire a sample image at a better shooting distance, and the image shooting effect is ensured. In the process that the robot controls the image acquisition equipment to move towards the sample to be measured, the distance between the image acquisition equipment and the sample to be measured can be obtained in real time, whether the distance between the image acquisition equipment and the sample to be measured is equal to a preset distance or not is judged, if the judgment result is not equal to the preset distance, the robot needs to be continuously controlled to adjust the position of the image acquisition equipment until the judgment result is equal to the preset distance, the shooting position of the image acquisition equipment is positioned, the image acquisition equipment can be controlled to be started, the surface of the sample to be measured is shot, and therefore a sample image is acquired, and the sample image with the structural striations is shown in figure 2. Alternatively, the acquired sample image may be stored in a fixed path, so that the sample image stored in the path may be directly read during subsequent image processing. Optionally, the preset distance is 200 mm-400 mm.
Step S30, extracting a plurality of structured light stripes from the sample image.
Due to the imperfections of the imaging system, the transmission medium, the recording device, etc., the digital image is often contaminated by various noises during the formation, transmission and recording processes of the digital image, in order to eliminate the noises mixed in the image and identify and extract the image features, optionally, a filtering operation is performed by replacing the value of a pixel by the median value of the gray level in the neighborhood of the pixel, and the way of image noise reduction is not limited to the embodiment. In addition, a person skilled in the art may also perform other processing on the sample image according to actual processing requirements, such as image enhancement, and specifically refer to the existing image processing method, which is not described in detail in this embodiment.
As shown in fig. 2, the image taken by taking the wire rod sample as an example mainly includes two parts, one part is the background of dark steel bars (i.e. black part in the figure), and the other part is the structural light stripe (i.e. multiple white stripes with deformation in the figure), because the structural light stripe and the black background have their respective obvious characteristics and different brightness, therefore, a threshold value T can be preset and used for distinguishing and segmenting the background and the structural light stripe, so that the invention needs to collect the brightness value f (x, y) at the pixel point (x, y) in the image and judge whether the brightness value f (x, y) is larger than the threshold value T or not, if f (x, y) is larger than T, the pixel point (x, y) is a target point which is a pixel point forming a plurality of structural light stripes, otherwise, the pixel point (x, y) is a background point. In this way, a series of target points can be extracted, and all the target points can be combined into a plurality of structured light stripes, for example, 7 structured light stripes are extracted from the sample image shown in fig. 2.
Step S40, determining an optimal detection point according to the central point set of each structural light stripe, and calculating the three-dimensional position coordinates of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structural light stripe.
Referring to fig. 2, each of the structured light stripes in the present invention may include two stripe regions, one is a left and a right side edge region, and the other is an intermediate stripe region except the left and right side edge regions, and the best detection point is generally selected in the intermediate stripe region. After extracting a plurality of structured light stripes, according to a region of interest (ROI) corresponding to the set structured light stripe, a stripe region in the middle of each structured light stripe is defined as the ROI, and then all pixel points included in the ROI form the central point set.
In practice, the applicant finds that the deformation characteristic of the structured light modulated by the surface of the sample to be measured is as follows: due to the fact that the surface of the sample to be detected is concave and convex, structured light irradiating the surface of the sample to be detected can be subjected to phase modulation, the light stripe pixel points corresponding to the more convex parts of the sample to be detected are more downward, and conversely, the light stripe pixel points corresponding to the more concave parts of the sample to be detected are more upward. Therefore, the structural light stripe information in the sample image can be used for analyzing the unevenness of the sample surface so as to determine the optimal detection point. According to the method, the most salient point of the surface of the sample to be detected in the shooting area of the image acquisition equipment is screened out according to the central point set of each structural light stripe and based on the deformation characteristic of the structural light caused by the modulation of the surface of the sample to be detected, and the most salient point is used as the optimal detection point.
Further, screening the most salient point on the surface of the sample to be measured in the shooting area of the image acquisition device comprises:
step (A): sorting the y coordinates of each pixel point in the central point set to obtain the pixel point coordinate corresponding to the maximum y coordinate value（xi，yi) (ii) a Wherein the content of the first and second substances,inumber of structural light stripe, 1 ≦iN, N is the number of structured light fringes extracted from the sample image;
step (B): calculating (x) by using a triangulation distance measuring method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be measuredi，yi) Corresponding depth coordinate Zi；
Step (C): from the depth coordinate ZiAnd screening out a minimum depth coordinate, and taking a pixel point corresponding to the minimum depth coordinate as the most salient point, wherein the most salient point is the best detection point.
In the specific implementation, after a plurality of structural light stripes are extracted, a central point set of each structural light stripe is obtained and is stored in a point set PointVector in a centralized manner; classifying the PointVector according to the number of the structured light stripes aiming at the point set PointVector to ensure that each structured light stripe corresponds to one central point set rowVectoriFor example, in fig. 2 and 3, 7 structured light stripes are extracted, that is, N =7, and there are 7 sets of center points, which are rowVector1, rowVector2, rowVector3, rowVector4, rowVector5, rowVector6, and rowVector 7; as shown in fig. 3, generally, the upper left corner of the image is used as the origin, an image coordinate system is established, for any one central point set, the y coordinates of the pixels in the set are sorted (in ascending or descending order), the maximum y coordinate value can be automatically screened out, and then the pixel coordinates (x coordinates) corresponding to the maximum y coordinate value are obtained (x coordinates)i，yi），（xi，yi) The pixel point with the most downward position in the y-axis direction in each structured light stripe can be screened to obtain 7 pixel point coordinates which are (x 1, y 1) (x 2, y 2), (x 3, y 3), (x 4, y 4), (x 5, y 5), (x 6, y 6) and (x 7, y 7).
Then (x) is calculated by utilizing a triangular distance measurement method according to the relative position relation among the image acquisition equipment, the structural light source and the sample to be measuredi，yi) Corresponding depth coordinate ZiZ1, Z2, Z3, Z4, Z5, Z6 and Z7, respectively, and the depth coordinate calculation method can be referred to below and shown in fig. 4; from Z1, Z2, Z3, Z4,And (3) screening a minimum depth coordinate from Z5, Z6 and Z7, for example, if Z3 is minimum (corresponding to the third structural light stripe), and a pixel point corresponding to Z3 is (x 3, y 3), it is indicated that a sample surface position point corresponding to (x 3, y 3) is closest to the image acquisition device, that is, (x 3, y 3) is the most salient point of the sample surface in the shooting area, the most salient point of the sample surface is taken as an optimal detection point, and the true three-dimensional position information corresponding to the optimal detection point is the position point to be detected by the alloy analyzer probe. Alternatively, as shown in fig. 3, the sweet spot may be marked in the sample image according to the coordinates (x 3, y 3) of the pixel point in the image of the sweet spot, thereby providing a reference for the user.
The best detection point determined by the sample image is in an image coordinate system, and the best detection point is correspondingly converted into a real world coordinate system to obtain the three-dimensional position coordinate of the best detection point, so that the alloy analyzer is controlled by a robot to move to the best detection point for alloy analysis. Specifically, a conversion relation between an image coordinate system and a world coordinate system can be obtained in advance according to imaging characteristics, shooting positions and other related information of the image acquisition equipment, after pixel point coordinates (X, Y) of the optimal detection point in the sample image are obtained, the optimal detection point is converted into world coordinates suitable for robot movement according to the conversion relation, and accordingly coordinates (X, Y) corresponding to the optimal detection point in the world coordinate system are obtained, and an X-axis coordinate and a Y-axis coordinate in a three-dimensional position coordinate are obtained. As shown in fig. 4, according to the geometric relationships such as the reference position, the relative position parameters between the image acquisition device, the structured light source, the distance measurement device and the sample to be measured, the depth coordinate Z of the optimal detection point, i.e. the Z-axis coordinate in the three-dimensional position coordinate, is calculated by using the triangulation method, so as to obtain the three-dimensional position coordinate (X, Y, Z) of the optimal detection point. And after the three-dimensional position coordinates of the optimal detection point are positioned, controlling the robot to move the alloy analyzer, so that the probe of the alloy analyzer reaches the position corresponding to the three-dimensional position coordinates of the optimal detection point, and then carrying out alloy analysis to obtain an analysis result. In this embodiment, the triangular distance measurement method is a conventional distance measurement method, and reference may be specifically made to the related description of the prior art, which is not described in detail in this embodiment.
According to the technical scheme, when the robot controls the image acquisition equipment to move towards the sample to be measured, the distance between the image acquisition equipment and the sample to be measured is obtained, and if the distance is equal to the preset distance, the image acquisition equipment can be moved to the optimal shooting position, so that the shooting effect of the structured light stripes is ensured. The invention extracts a plurality of structural light stripes from the sample image, thereby separating the background from the structural light stripes so as to improve the accuracy and efficiency of positioning the optimal detection point in the subsequent image processing. After extracting a plurality of structural light stripes, acquiring coordinates of other pixel points except pixel points in edge areas at two sides in each structural light stripe to obtain a central point set of each structural light stripe, and determining the surface roughness of the sample to be detected by combining the deformation characteristic of structured light modulated by the surface of the sample to be detected according to the central point set of each structural light stripe so as to screen out an optimal detection point and finally obtain the three-dimensional position coordinate of the optimal detection point. According to the invention, the three-dimensional position coordinates of the optimal detection point can be calculated by only shooting one sample image in the detection area, the calculation amount is reduced, a complex image processing process is not needed, and the calculation and positioning efficiency is higher.
As shown in fig. 5 and fig. 6, another embodiment of the present invention provides an alloy analysis visual positioning apparatus, for implementing the alloy analysis visual positioning method described in the previous embodiment, including a structural light source 41, an image acquisition device 42, a laser ranging sensor 43, and a controller 5; the alloy analysis visual positioning device is connected with the robot 1, the robot 1 is electrically connected with the controller 5, and the controller 5 is used for controlling the movement, opening and closing of the robot 1; when the controller 5 controls the robot 1 to move, the robot 1 drives the structural light source 41, the image acquisition equipment 42 and the laser ranging sensor 43 to be linked; the controller 5 is electrically connected with the structural light source 41 and can control the on and off of the structural light source 41; the controller 5 is electrically connected with the image acquisition device 42, the controller 5 can open and close the image acquisition device 42, and the image acquisition device 42 sends the shot sample image to the controller 5, so that the controller 5 processes and calculates the sample image to determine an optimal detection point; the controller 5 is electrically connected with the laser ranging sensor 43, the controller 5 can control the on-off of the laser ranging sensor 43, the laser ranging sensor 43 is used for detecting the distance between the image acquisition device 42 and a sample to be detected, and the laser ranging sensor 43 can send a measurement signal to the controller 5, so that the controller 5 obtains the distance between the image acquisition device 42 and the sample to be detected to position the shooting position of the image acquisition device 42; the axes of the image acquisition device 42 and the structural light source 41 are on the same vertical plane, so that the shooting quality of the sample image can be improved, and optionally, the distance between the image acquisition device 42 and the structural light source 41 is 70 mm-100 mm.
Wherein the controller 5 is configured to execute the following program steps:
controlling the image acquisition equipment to move towards the sample to be detected;
acquiring the distance between the image acquisition equipment and a sample to be detected;
if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image;
extracting a plurality of structural light stripes from the sample image, and calculating the center point coordinate of each structural light stripe;
determining an optimal detection point according to the central point set of each structural light stripe, and calculating a three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structural light stripe.
The controller 5 is electrically connected with the robot 1, the robot 1 is fixedly connected with the alloy analyzer 3, and the controller 5 can generate a corresponding control instruction according to the three-dimensional position coordinates of the optimal detection point and send the control instruction to the robot 1; the robot 1 moves according to the control instruction, and drives the alloy analyzer 3 to be linked, so that the alloy analyzer 3 is moved to the three-dimensional position coordinate where the optimal detection point is located, and the alloy analyzer 3 performs alloy analysis on a sample to be detected.
Optionally, the controller 5 may be further configured to perform the following program steps:
acquiring the brightness value of a pixel point in the sample image;
judging whether the brightness value is larger than a threshold value;
if the brightness value is larger than the threshold value, the pixel point is a target point;
and extracting all target points in the sample image to obtain a plurality of the structural light stripes.
Optionally, the controller 5 may be further configured to perform the following program steps:
screening out the most salient points of the surface of the sample to be measured in the shooting area of the image acquisition equipment according to the central point set of each structured light stripe and the deformation characteristic of the structured light generated by the modulation of the surface of the sample to be measured;
and taking the most salient point as the best detection point.
Optionally, the controller 5 may be further configured to perform the following program steps:
sorting the y coordinates of each pixel point in the central point set to obtain the pixel point coordinate (x) corresponding to the maximum y coordinate valuei，yi) (ii) a Wherein the content of the first and second substances,inumber of structural light stripe, 1 ≦iN, N is the number of structured light fringes extracted from the sample image;
calculating (x) by using a triangulation distance measuring method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be measuredi，yi) Corresponding depth coordinate Zi；
From the depth coordinate ZiAnd screening out a minimum depth coordinate, and taking a pixel point corresponding to the minimum depth coordinate as the most salient point.
Optionally, the controller 5 may be further configured to perform the following program steps:
acquiring a conversion relation between an image coordinate system and a world coordinate system;
obtaining the corresponding coordinates (X, Y) of the optimal detection point in the sample image in a world coordinate system according to the conversion relation;
and calculating the depth coordinate Z of the optimal detection point by using a triangular distance measurement method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be detected to obtain the three-dimensional position coordinate (X, Y, Z) of the optimal detection point.
Optionally, the controller 5 may be further configured to perform the following program steps:
setting an interested area of the structured light stripe, wherein the interested area is a stripe area except for two side edge areas in the structured light stripe;
and forming the central point set by the pixel points included in the region of interest.
Optionally, the controller 5 may be further configured to perform the following program steps: marking the best detection point in the sample image.
Optionally, as shown in fig. 6 and 7, the alloy analysis visual positioning apparatus further includes a bottom plate 44 and an outer cover 45, a front end (i.e. front) panel of the outer cover 45 is transparent, the transparent front panel can ensure that the structured light emitted by the structured light source 41 can be incident on the surface of the sample to be measured, and ensure that the image acquisition device 42 can acquire an image, and the transparent front panel can also play a role of protection sealing; the rear end (i.e. the back) of the outer shield 45 is fixed on the bottom plate 44, the image acquisition device 42 and the structural light source 41 are located inside the outer shield 45, and the bottom plate 44 is used for installing the image acquisition device 42 and the structural light source 41 and sealing and protecting the rear end of the device; the laser ranging sensor 43 is disposed on top of the outer shield 45.
As shown in fig. 7 to 9, another embodiment of the present invention provides an alloy analysis system, which includes a robot 1, a support 2, an alloy analyzer 3, and an alloy analysis visual positioning apparatus 4 according to the previous embodiment, wherein the robot 1 is connected to the alloy analyzer 3 through the support 2, the alloy analysis visual positioning apparatus 4 is disposed on the support 2, the alloy analyzer 3 and the alloy analysis visual positioning apparatus 4 are disposed adjacent to each other and both face a sample 100 to be measured, and the controller is further electrically connected to the alloy analyzer 3; the robot 1 can be a six-axis robot; optionally, the bracket 2 is an L-shaped bracket having two sides, one side of the bracket 2 is provided with a flange 21, the flange 21 is used for connecting the bracket 2 with the robot 1, the other side of the bracket 2 is connected with a bottom plate 44 through a mounting plate 22 so as to connect the bracket 2 with the alloy analysis visual positioning device 4, and the two sides of the bracket 2 are connected through a support rod 23 so as to strengthen the supporting structure of the bracket 2.
On the basis of the program that the controller is configured to execute in the foregoing embodiment, the controller in this embodiment is further configured to execute the following program steps:
controlling the robot to move so that the alloy analyzer moves to a position corresponding to the three-dimensional position coordinate of the optimal detection point;
and controlling the alloy analyzer to start so as to analyze the alloy at the optimal detection point.
In each embodiment of the present invention, optionally, a voice device may be disposed on the robot 1, the voice device is electrically connected to the controller 5, and the voice device is configured to broadcast a detection result of the alloy analyzer 3 on the sample to be detected, so that a field worker can know whether the sample to be detected is qualified. The controller 5 may be further configured to: and controlling the voice device to broadcast corresponding prompt information according to the detection result fed back by the alloy analyzer, and controlling the robot to return to the initial position. The prompt information can be preset in the voice device, for example, the prompt information can be set to be qualified or unqualified for the detection of a certain sample to be detected, and the specific content of the prompt information is not limited.
In each embodiment of the invention, the alloy analyzer adopts an X fluorescence analysis technology, and can quickly, accurately and nondestructively analyze various materials; the system has a wide and self-defined brand library, and a user can modify the existing brand library, add a new brand or create the brand library and can strictly control the analysis of light elements (magnesium, aluminum, silicon, phosphorus and sulfur); the system has a strong background data management function and can customize software according to requirements. The detection result and the report can be directly downloaded to a U disk, or data transmission can be realized through WiFi, USB or network cables.
In each embodiment of the present invention, the Controller may be a Programmable Logic Controller (PLC), and the PLC may be configured with functions such as a control program and an image processing system. Alternatively, the robot 1 can be an ABB IRB4600 type robot, the laser distance measuring sensor 43 can be a Panasonic HG-C1050 laser sensor, the structure light source 41 can be an OPT-SL10B type structure light source, the alloy analyzer 3 can be a Nitong XL2980 type alloy analyzer, and the image acquisition device 42 can be an AVT Mako G-192B type industrial camera.
The same or similar contents in the embodiments of the present invention may be referred to each other, and the related embodiments are not described in detail.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (10)
1. An alloy analysis visual positioning method, characterized in that the method comprises:
when the robot controls the image acquisition equipment to move towards the sample to be detected, acquiring the distance between the image acquisition equipment and the sample to be detected; wherein the image acquisition device is provided with a structured light source;
if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image; the structural light generated by the structural light source is reflected by the surface of the sample to be detected and then received by the image acquisition equipment, so that the sample image comprises structural light stripes carrying the surface deformation characteristics of the sample to be detected;
extracting a plurality of structural light stripes from the sample image;
determining an optimal detection point according to the central point set of each structural light stripe, and calculating a three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas at the two sides in the structured light stripes; the best detection point is the most salient point on the surface of the sample to be detected.
2. The method of claim 1, wherein extracting the plurality of structured light stripes from the sample image comprises:
acquiring the brightness value of a pixel point in the sample image;
judging whether the brightness value is larger than a threshold value;
if the brightness value is larger than the threshold value, the pixel point is a target point;
and extracting all target points in the sample image to obtain a plurality of the structural light stripes.
3. The method of claim 1, wherein determining the best detection point from the set of center points for each of the structured light stripes comprises:
screening out the most salient points of the surface of the sample to be measured in the shooting area of the image acquisition equipment according to the central point set of each structured light stripe and the deformation characteristic of the structured light generated by the modulation of the surface of the sample to be measured;
and taking the most salient point as the best detection point.
4. The method as claimed in claim 3, wherein the screening out the most salient point of the surface of the sample to be measured in the shooting area of the image acquisition device comprises:
sorting the y coordinates of each pixel point in the central point set to obtain the pixel point coordinate (x) corresponding to the maximum y coordinate valuei，yi) (ii) a Wherein the content of the first and second substances,inumber of structural light stripe, 1 ≦iN, N is the number of structured light fringes extracted from the sample image;
calculating (x) by using a triangulation distance measuring method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be measuredi，yi) Corresponding depth coordinate Zi；
From the depth coordinate ZiAnd screening out a minimum depth coordinate, and taking a pixel point corresponding to the minimum depth coordinate as the most salient point.
5. The method of claim 1, wherein said obtaining three-dimensional position coordinates of said best detection point comprises:
acquiring a conversion relation between an image coordinate system and a world coordinate system;
obtaining the corresponding coordinates (X, Y) of the optimal detection point in the sample image in a world coordinate system according to the conversion relation;
and calculating the depth coordinate Z of the optimal detection point by using a triangular distance measurement method according to the relative position relationship among the image acquisition equipment, the structural light source and the sample to be detected to obtain the three-dimensional position coordinate (X, Y, Z) of the optimal detection point.
6. The method of claim 1, further comprising:
setting an interested area of the structured light stripe, wherein the interested area is a stripe area except for two side edge areas in the structured light stripe;
and forming the central point set by the pixel points included in the region of interest.
7. The method of claim 1, further comprising: marking the best detection point in the sample image.
8. An alloy analysis visual positioning device for realizing the alloy analysis visual positioning method according to any one of claims 1 to 7, comprising an image acquisition device and a structural light source, and further comprising a laser ranging sensor and a controller, wherein the alloy analysis visual positioning device is connected with a robot, and the structural light source, the robot, the image acquisition device and the laser ranging sensor are respectively and electrically connected with the controller; the laser ranging sensor is used for detecting the distance between the image acquisition equipment and a sample to be detected;
wherein the controller is configured to perform the following program steps:
controlling the image acquisition equipment to move towards the sample to be detected;
acquiring the distance between the image acquisition equipment and a sample to be detected;
if the distance between the image acquisition equipment and the sample to be detected is equal to the preset distance, controlling the image acquisition equipment to shoot the surface of the sample to be detected to obtain a sample image; the structural light generated by the structural light source is reflected by the surface of the sample to be detected and then received by the image acquisition equipment, so that the sample image comprises structural light stripes carrying the surface deformation characteristics of the sample to be detected;
extracting a plurality of structural light stripes from the sample image;
determining an optimal detection point according to the central point set of each structural light stripe, and calculating a three-dimensional position coordinate of the optimal detection point; the central point set comprises other pixel points except the pixel points in the edge areas on the two sides in the structural light stripe.
9. The device of claim 8, further comprising a base plate and an outer shield, wherein a front panel of the outer shield is transparent and a rear end of the outer shield is secured to the base plate; the image acquisition equipment and the structural light source are fixed on the bottom plate and are positioned inside the outer shield; the laser ranging sensor is arranged at the top of the outer shield; the axes of the image acquisition equipment and the structural light source are on the same vertical plane.
10. An alloy analysis system, which is characterized by comprising a robot, a bracket, an alloy analyzer and the alloy analysis visual positioning device of claim 8 or 9, wherein the robot is connected with the alloy analyzer through the bracket, the alloy analysis visual positioning device is arranged on the bracket, the alloy analyzer and the alloy analysis visual positioning device are arranged adjacently and face towards a sample to be measured, and the controller is also electrically connected with the alloy analyzer;
wherein the controller is configured to perform the following program steps:
controlling the robot to move so that the alloy analyzer moves to a position corresponding to the three-dimensional position coordinate of the optimal detection point;
and controlling the alloy analyzer to start so as to analyze the alloy at the optimal detection point.
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| CN111272756B (en) * | 2020-03-09 | 2022-08-26 | 江苏金恒信息科技股份有限公司 | Alloy analysis system |
| CN111618855B (en) * | 2020-05-27 | 2021-10-08 | 江苏金恒信息科技股份有限公司 | Automatic listing system and method |
| CN111562262B (en) * | 2020-05-27 | 2020-10-13 | 江苏金恒信息科技股份有限公司 | Alloy analysis system and rechecking method thereof |
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