CN111179221A - Method and device for detecting welding groove and storage medium - Google Patents
Method and device for detecting welding groove and storage medium Download PDFInfo
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Abstract
The invention discloses a method, equipment and a storage medium for detecting a welding groove, wherein the method for detecting the welding groove comprises the steps of acquiring parameter information of a visual sensing system arranged above the welding groove and acquiring point cloud data obtained by scanning the welding groove by the visual sensing system; acquiring a global characteristic inflection point, starting point position information, end point position information and a detection dead point region characteristic inflection point of a welding groove through point cloud data and a parameter system of a visual sensing system; the method solves the technical problems of poor welding groove detection accuracy and universality in the prior art, and provides the welding groove detection method with high accuracy and strong applicability.
Description
Technical Field
The invention relates to the technical field of welding, in particular to a method and equipment for detecting a welding groove and a storage medium.
Background
With the rapid development of scientific technology, automation technology is widely applied to various technical fields. The traditional manual welding is gradually replaced by automatic welding equipment represented by a numerical control special machine, a robot and the like due to factors such as poor welding seam uniformity, low welding efficiency, high labor intensity and the like.
Welding groove detection and identification are key technologies in automatic welding, single-layer single-channel welding groove detection relying on an electric arc type sensor and a contact type sensor cannot meet the requirements of the automatic welding technology, the accuracy and universality of the detection are limited by a welding object, and the detection of multilayer multi-channel welding grooves cannot be met. Therefore, how to solve the above technical problems becomes a problem to be overcome by those skilled in the art.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides the detection method of the welding groove, which has high accuracy and strong applicability.
In a first aspect, an embodiment of the present invention provides a method for detecting a welding groove, including:
acquiring a deflection angle of a visual sensing system arranged above a welding groove, and acquiring point cloud data obtained by scanning the welding groove by the visual sensing system and distance information of the visual sensing system from the welding groove;
obtaining a global characteristic inflection point of the welding groove according to the point cloud data;
obtaining starting point position information and end point position information of the welding groove according to the deflection angle, the point cloud data and the distance information;
acquiring connecting plate position information according to the point cloud data, and acquiring a detection dead point area according to the connecting plate position information;
extracting the global characteristic inflection point outside the detection dead point area to obtain a local characteristic inflection point;
and obtaining the characteristic inflection point of the detected dead point region by mathematically calculating the local characteristic inflection point.
The detection method of the welding groove of the embodiment of the invention at least has the following beneficial effects:
the invention provides a method for detecting a welding groove, which comprises the steps of obtaining parameter information of a visual sensing system arranged above the welding groove and obtaining point cloud data obtained by scanning the welding groove by the visual sensing system; acquiring a global characteristic inflection point, starting point position information, end point position information and a detection dead point region characteristic inflection point of a welding groove through point cloud data and a parameter system of a visual sensing system; the method solves the technical problems of poor welding groove detection accuracy and universality in the prior art, and provides the welding groove detection method with high accuracy and strong applicability.
According to the detection method of the welding groove of the other embodiments of the present invention, the visual sensing system includes a line laser light source device and a CCD camera;
the line laser light source device emits line laser to obtain the distance information, and the line laser scans the welding groove to generate the point cloud data;
an inertial sensor is arranged on the line laser light source device and used for acquiring the deflection angle;
the CCD camera is used for acquiring the point cloud data.
According to the detection method of the welding groove in other embodiments of the present invention, a spatial coordinate system is established with the cross-sectional direction of the welding groove as an X-axis direction, the extending direction of the welding groove as a Y-axis direction, and the depth direction of the welding groove as a Z-axis direction, and the line laser scans from a preset starting point to a preset end point along the Y-axis direction;
in a preset range of the preset starting point, the line laser light source device rotates at a constant speed along the X-axis direction, and the line laser scans the welding groove to obtain starting point segment point cloud data;
in a preset linear range, the line laser light source device moves at a constant speed along the Z-axis direction, and the line laser scans the welding groove to obtain linear-segment point cloud data;
in a preset range of the preset end point, the line laser light source device rotates at a constant speed along the X-axis direction, and the line laser scans the welding groove to obtain end point section point cloud data;
the point cloud data comprises the starting point segment point cloud data, the straight line segment point cloud data and the end point segment point cloud data.
According to the detection method of the welding groove in other embodiments of the present invention, the obtaining the global characteristic inflection point of the welding groove according to the point cloud data specifically includes:
performing Gaussian filtering on the straight line point cloud data to obtain target straight line point cloud;
calculating the slope of each point in the target straight line point cloud;
and two adjacent points of which the slope difference value meets a set threshold are the global characteristic inflection points.
According to the detection method of the welding groove in other embodiments of the present invention, obtaining the start position information and the end position information of the welding groove according to the deflection angle, the point cloud data, and the distance information specifically includes:
performing Gaussian filtering processing on the starting point section point cloud data to obtain a target starting point cloud;
performing curve fitting on the target starting point cloud to obtain a starting point fitting curve;
performing a first order derivation on the target starting point cloud located on the starting point fitting curve;
the starting point location information is expressed as:
xq＝x1-tanθ1*Δy1
wherein x is1Is the preset starting point, theta1The deflection angle, Δ y, for a value of 0 to first-order derivative of the target origin point cloud located on the origin-fitting curve1The distance information when the value of the first derivative for the target starting point cloud located on the starting point fitting curve is 0;
performing Gaussian filtering on the point cloud data of the end point section to obtain a target end point cloud;
performing curve fitting on the target endpoint cloud to obtain an endpoint fitting curve;
performing a first order derivation on the target endpoint point cloud located on the endpoint fitting curve;
the end point position information is expressed as:
xz＝x2-tanθ2*Δy2
wherein x is2To the preset end point, theta2The deflection angle, Δ y, for a value of 0 to first derivative the target endpoint cloud located on the endpoint-fitting curve2The distance information when the value of the first derivative for the target end point cloud located on the end point fitting curve is 0.
According to another embodiment of the present invention, the method for detecting a welding groove, wherein the obtaining of the position information of the connection plate according to the point cloud data specifically includes:
performing Gaussian filtering on the straight line point cloud data to obtain target straight line point cloud;
calculating the height average value of each frame of point cloud data in the target linear point cloud;
and comparing each height average value, wherein the position where the height average value is mutated corresponds to the position information of the connecting plate.
In a second aspect, an embodiment of the present invention provides a welding groove detection apparatus, including:
at least one processor, and,
a memory communicatively coupled to the at least one processor, wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method for detecting a weld groove.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the method for detecting a welding groove.
Drawings
Fig. 1 is a schematic flow chart of an embodiment of a method for detecting a welding groove according to the present invention;
FIG. 2 is a schematic diagram of a specific embodiment of a positional relationship between a visual sensing system and a welding groove in a method for detecting a welding groove according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a specific embodiment of a positional relationship between a connecting plate and a detection dead point region in a detection method of a welding groove in an embodiment of the present invention.
Detailed Description
The concept and technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments to fully understand the objects, features and effects of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and those skilled in the art can obtain other embodiments without inventive effort based on the embodiments of the present invention, and all embodiments are within the protection scope of the present invention.
In the description of the embodiments of the present invention, if "a number" is referred to, it means one or more, if "a plurality" is referred to, it means two or more, if "greater than", "less than" or "more than" is referred to, it is understood that the number is not included, and if "greater than", "lower" or "inner" is referred to, it is understood that the number is included. References to "first", "second", "third", etc., are to be understood as being used to distinguish between technical features and are not intended to indicate or imply relative importance or to implicitly indicate a number of indicated technical features or to implicitly indicate a precedence relationship of the indicated technical features.
Referring to fig. 1, in an embodiment of the present invention, a method for detecting a welding groove includes the following steps:
s100, obtaining a deflection angle and point cloud data, namely distance information;
the deflection angle is the deflection angle of a visual sensing system arranged above the welding groove, the visual sensing system scans the welding groove to obtain point cloud data, and distance information between the visual sensing system and the surface of the welding groove is obtained.
In some embodiments, the visual sensing system includes a line laser light source device and a CCD camera, the line laser light source emits line laser, the line laser scans the welding groove according to a predetermined scanning step length, so that distance information between the visual sensing system and the surface of the welding groove can be obtained, and point cloud data generated by scanning the welding groove with the line laser can be obtained by the CCD camera. In the embodiment of the invention, the inertial sensor is arranged in the line laser light source device and is used for acquiring the deflection angle of the line laser light source device.
S200, obtaining a global characteristic inflection point of the welding groove according to the point cloud data;
according to the embodiment of the invention, the global characteristic inflection point of the welding groove is obtained through point cloud data, wherein the characteristic inflection point comprises a right-angle inflection point and an oblique-angle inflection point. In the detection of the welding groove, the right angle inflection point and the bevel inflection point can reflect the shape change point of the welding groove, and the right angle inflection point and the bevel inflection point of the welding groove are detected to be used as important welding parameters in the subsequent welding work.
S300, obtaining starting point position information and end point position information of the welding groove according to the deflection angle, the point cloud data and the distance information;
in the embodiment of the invention, the starting position information and the end position information of the welding groove are further obtained through the obtained data information, so that the welding area during welding is determined.
S400, obtaining connecting plate position information according to the point cloud data, and obtaining a detection dead point area according to the connecting plate position information;
in the embodiment of the invention, the position information of the connecting plate is calculated through the point cloud data, and the CCD camera has a part of detection dead point area due to the existence of the connecting plate, so that the influence of the detection dead point area needs to be considered in the detection of the welding groove in order to improve the accuracy of the detection of the welding groove.
S500, extracting global characteristic inflection points outside the detection dead point area to obtain local characteristic inflection points;
in step S200, since the acquired global feature inflection point includes an erroneous feature inflection point in the detected dead point region, and the erroneous feature inflection point in the detected dead point region obviously cannot reflect the shape change of the welding groove, it is necessary to exclude the erroneous feature inflection point in the detected dead point region.
S600, obtaining the feature inflection point of the detected dead point region by mathematically calculating the local feature inflection point.
In step S500, the local feature inflection point is obtained by excluding the false feature inflection point of the detected dead center region obtained in step S200, and the detected dead center region feature inflection point of the detected dead center region can be obtained by mathematically calculating the local feature inflection point.
Through the steps, the method for detecting the welding groove can acquire the information such as the starting position information, the end position information, the characteristic inflection point and the like of the welding groove, and provides accurate welding parameters for subsequent welding work.
Referring to fig. 2 and fig. 3, a process principle implemented by a detection method for a welding groove according to an embodiment of the present invention is described below by taking a welding groove as a V-shaped groove 400 as an example:
as shown in fig. 2, in the embodiment of the present invention, a spatial coordinate system is established with the cross-sectional direction of the welding groove as the X-axis direction, the extending direction of the welding groove as the Y-axis direction, and the depth direction of the welding groove as the Z-axis direction. When the welding groove is detected, the line laser light source device in the vision sensing system 100 emits line laser to scan from a preset starting point to a preset end point along the Y-axis direction. In the scanning process, the line laser light source device rotates along the X-axis direction within the preset range of the preset starting point of the vision sensing system, the line laser light source device and the CCD camera are controlled by the same mechanical arm, that is, the whole vision sensing system 100 rotates along the X-axis direction at this time, before the vision sensing system 100 rotates along the X-axis direction, the preset starting point position and the preset end point position are determined according to the detection range of the vision sensing system 100 in the Z-axis direction (refer to fig. 3, that is, the field range 600 of the CCD camera), and the preset starting point and the preset end point are respectively located at two ends of the detection range. After the preset starting point position is determined, a preset range is set, in the preset range, the line laser light source device rotates along the X-axis direction, and line laser 200 emitted by the line laser light source device scans the V-shaped groove 400 to obtain starting point section point cloud data. After the preset end point position is determined, another preset range is set, in the preset range, the line laser light source device rotates along the X-axis direction, and line laser 200 emitted by the line laser light source device scans the V-shaped groove 400 to obtain end point section point cloud data. And then determining a preset range of a preset starting point and a preset range of an end point, so as to obtain a preset linear range, wherein in the preset linear range, the linear laser light source device moves at a constant speed along the Z-axis direction, and linear laser 200 emitted by the linear laser light source device scans the V-shaped groove 400 to obtain linear segment point cloud data. In the embodiment of the invention, the point cloud data is three-segment point cloud data comprising starting point segment point cloud data, end point segment point cloud data and straight line segment point cloud data.
After the three-segment point cloud data is obtained, the three-segment point cloud data needs to be processed to obtain the start position information, the end position information and the characteristic inflection point of the V-groove 400. The method comprises the following steps of performing Gaussian filtering processing on straight-line-segment point cloud data, removing noise in the acquired data to obtain target straight-line point cloud, and calculating the slope of each point in each frame of target straight-line point cloud, wherein the specific calculation formula is as follows:
after the slopes of each point in the target linear point cloud are calculated according to the formula (1), when the difference value between the slopes of two adjacent points meets a preset threshold, the two adjacent points are global feature inflection points, and after the two adjacent points of the target linear point cloud in all the frames are traversed and judged, a set of the global feature inflection points can be obtained.
After the starting point section point cloud data is obtained, performing Gaussian filtering processing on the starting point section point cloud data, removing noise in the obtained data to obtain a target starting point cloud, performing curve fitting on the obtained target starting point cloud to obtain a starting point fitting curve, and performing first-order derivation on the target starting point cloud on the starting point fitting curve to obtain starting point position information:
xq＝x1-tanθ1*Δy1(2)
wherein x is1Is a predetermined starting point, theta1For a deflection angle (obtained by an inertial sensor) of 0 for the first derivative of the target starting point cloud on the starting point fitting curve, Δ y1Distance information (obtained by line laser 200 scanning) at a value of 0 for first-order derivation of a target starting point cloud located on a starting point fitting curve.
After the end point cloud data is obtained, performing Gaussian filtering on the end point cloud data, removing noise in the obtained data to obtain a target end point cloud, performing curve fitting on the obtained target end point cloud to obtain an end point fitting curve, and performing first-order derivation on the target end point cloud on the end point fitting curve to obtain end point position information:
xz＝x2-tanθ2*Δy2(3)
wherein x is2To preset end point, θ2Deflection angle, Δ y, of 0 value for first order derivation of a target endpoint cloud located on an endpoint-fitting curve2Distance information with a value of 0 for first-order derivation of a target endpoint cloud located on an endpoint-fitting curve.
Referring to fig. 3, since the existence of the connecting plate 300 causes the occurrence of the detected dead point region 500, an erroneous feature inflection point in the detected dead point region 500 is obtained from the set of global feature inflection points obtained as described above, and therefore, it is necessary to extract a local feature inflection point obtained by removing the erroneous feature inflection point in the detected dead point region 500, and then calculate the local feature inflection point by a mathematical calculation method to obtain the detected dead point region feature inflection point in the detected dead point region 500. The method specifically comprises the following steps:
calculating the height average value of each frame of point cloud data in the target linear point cloud;
comparing the obtained plurality of height average values, and enabling the height average values to suddenly change to be the positions corresponding to the connecting plates 300;
after the position of the connecting plate 300 is obtained, the position information of the CCD camera is combined to obtain a detection dead point area 500;
extracting global characteristic inflection points outside the detection dead point region 500 to obtain local characteristic inflection points;
and finally, performing linear fitting on the local characteristic inflection point by a least square method to obtain the characteristic inflection point of the detected dead point region 500.
In summary, in the embodiment of the present invention, parameter information of the visual sensing system disposed above the welding groove is obtained, and point cloud data obtained by scanning the welding groove by the visual sensing system is obtained; acquiring a global characteristic inflection point, starting point position information, end point position information and a detection dead point region characteristic inflection point of a welding groove through point cloud data and a parameter system of a visual sensing system; the method solves the technical problems of poor welding groove detection accuracy and universality in the prior art, and provides the welding groove detection method with high accuracy and strong applicability.
Example two:
the embodiment of the invention provides a detection device for a welding groove, which comprises:
at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the processor can execute the method for detecting the welding groove according to the first embodiment.
Example three:
the embodiment of the invention provides a computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium and used for enabling a computer to execute the welding groove detection method in the first embodiment.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention. Furthermore, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
Claims (8)
1. A method for detecting a welding groove, comprising:
acquiring a deflection angle of a visual sensing system arranged above a welding groove, and acquiring point cloud data obtained by scanning the welding groove by the visual sensing system and distance information of the visual sensing system from the welding groove;
obtaining a global characteristic inflection point of the welding groove according to the point cloud data;
obtaining starting point position information and end point position information of the welding groove according to the deflection angle, the point cloud data and the distance information;
acquiring connecting plate position information according to the point cloud data, and acquiring a detection dead point area according to the connecting plate position information;
extracting the global characteristic inflection point outside the detection dead point area to obtain a local characteristic inflection point;
and obtaining the characteristic inflection point of the detected dead point region by mathematically calculating the local characteristic inflection point.
2. The detection method of a welding groove according to claim 1, wherein the visual sensing system comprises a line laser light source device and a CCD camera;
the line laser light source device emits line laser to obtain the distance information, and the line laser scans the welding groove to generate the point cloud data;
an inertial sensor is arranged on the line laser light source device and used for acquiring the deflection angle;
the CCD camera is used for acquiring the point cloud data.
3. The method for detecting a welding groove according to claim 2, wherein a spatial coordinate system is established with the cross-sectional direction of the welding groove as an X-axis direction, the extending direction of the welding groove as a Y-axis direction, and the depth direction of the welding groove as a Z-axis direction, and the line laser scans from a preset starting point to a preset end point along the Y-axis direction;
in a preset range of the preset starting point, the line laser light source device rotates at a constant speed along the X-axis direction, and the line laser scans the welding groove to obtain starting point segment point cloud data;
in a preset linear range, the line laser light source device moves at a constant speed along the Z-axis direction, and the line laser scans the welding groove to obtain linear-segment point cloud data;
in a preset range of the preset end point, the line laser light source device rotates at a constant speed along the X-axis direction, and the line laser scans the welding groove to obtain end point section point cloud data;
the point cloud data comprises the starting point segment point cloud data, the straight line segment point cloud data and the end point segment point cloud data.
4. The method for detecting a welding groove according to claim 3, wherein the obtaining of the global characteristic inflection point of the welding groove according to the point cloud data specifically comprises:
performing Gaussian filtering on the straight line point cloud data to obtain target straight line point cloud;
calculating the slope of each point in the target straight line point cloud;
and two adjacent points of which the difference value of the slopes meets a set threshold are the global feature inflection points.
5. The method for detecting a welding groove according to claim 3 or 4, wherein obtaining start position information and end position information of the welding groove according to the deflection angle, the point cloud data, and the distance information specifically includes:
performing Gaussian filtering processing on the starting point section point cloud data to obtain a target starting point cloud;
performing curve fitting on the target starting point cloud to obtain a starting point fitting curve;
performing a first order derivation on the target starting point cloud located on the starting point fitting curve;
the starting point location information is expressed as:
xq＝x1-tanθ1*Δy1
wherein x is1Is the preset starting point, theta1The deflection angle, Δ y, for a value of 0 to first-order derivative of the target origin point cloud located on the origin-fitting curve1The distance information when the value of the first derivative for the target starting point cloud located on the starting point fitting curve is 0;
performing Gaussian filtering on the point cloud data of the end point section to obtain a target end point cloud;
performing curve fitting on the target endpoint cloud to obtain an endpoint fitting curve;
performing a first order derivation on the target endpoint point cloud located on the endpoint fitting curve;
the end point position information is expressed as:
xz＝x2-tanθ2*Δy2
wherein x is2To the preset end point, theta2The deflection angle, Δ y, for a value of 0 to first derivative the target endpoint cloud located on the endpoint-fitting curve2The distance information when the value of the first derivative for the target end point cloud located on the end point fitting curve is 0.
6. The method for detecting a welding groove according to claim 3 or 4, wherein the obtaining of the connecting plate position information according to the point cloud data specifically comprises:
performing Gaussian filtering on the straight line point cloud data to obtain target straight line point cloud;
calculating the height average value of each frame of point cloud data in the target linear point cloud;
and comparing each height average value, wherein the position where the height average value is mutated corresponds to the position information of the connecting plate.
7. A detection apparatus for a welding groove, characterized by comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor, wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.
8. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1 to 6.
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| CN114485403A (en) * | 2022-01-29 | 2022-05-13 | 中石化石油机械股份有限公司沙市钢管分公司 | Follow-up measurement device and measurement method for machining size of edge milling groove of submerged-arc welded pipe |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0647540A (en) * | 1992-08-03 | 1994-02-22 | Nippon Steel Corp | Method and device for detecting welding groove shape |
| CN106624262A (en) * | 2016-12-31 | 2017-05-10 | 山东大学 | Method and device for intelligent welding of intersection curve of round pipes |
| CN107755937A (en) * | 2017-08-31 | 2018-03-06 | 中建钢构有限公司 | Luffing swings welding method, apparatus and welding robot |
| CN109352217A (en) * | 2018-10-29 | 2019-02-19 | 上海船舶工艺研究所(中国船舶工业集团公司第十研究所) | Robot on-line automatic welding equipment and weld job method are found by a kind of group |
| CN110245599A (en) * | 2019-06-10 | 2019-09-17 | 深圳市超准视觉科技有限公司 | A kind of intelligent three-dimensional weld seam Auto-searching track method |
| CN110455187A (en) * | 2019-08-21 | 2019-11-15 | 哈尔滨工业大学 | A kind of detection method of the box body workpiece weld seam based on 3D vision |
-
2019
- 2019-12-09 CN CN201911252476.3A patent/CN111179221B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0647540A (en) * | 1992-08-03 | 1994-02-22 | Nippon Steel Corp | Method and device for detecting welding groove shape |
| CN106624262A (en) * | 2016-12-31 | 2017-05-10 | 山东大学 | Method and device for intelligent welding of intersection curve of round pipes |
| CN107755937A (en) * | 2017-08-31 | 2018-03-06 | 中建钢构有限公司 | Luffing swings welding method, apparatus and welding robot |
| CN109352217A (en) * | 2018-10-29 | 2019-02-19 | 上海船舶工艺研究所(中国船舶工业集团公司第十研究所) | Robot on-line automatic welding equipment and weld job method are found by a kind of group |
| CN110245599A (en) * | 2019-06-10 | 2019-09-17 | 深圳市超准视觉科技有限公司 | A kind of intelligent three-dimensional weld seam Auto-searching track method |
| CN110455187A (en) * | 2019-08-21 | 2019-11-15 | 哈尔滨工业大学 | A kind of detection method of the box body workpiece weld seam based on 3D vision |
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| CN114485403A (en) * | 2022-01-29 | 2022-05-13 | 中石化石油机械股份有限公司沙市钢管分公司 | Follow-up measurement device and measurement method for machining size of edge milling groove of submerged-arc welded pipe |
| CN114485403B (en) * | 2022-01-29 | 2024-04-09 | 中石化石油机械股份有限公司沙市钢管分公司 | Follow-up measuring device and measuring method for machining dimension of edge milling groove of submerged arc welded pipe |
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