Cable laying detection device and detection method

Abstract

The application discloses a cable laying detection device and a detection method, which comprise a handle and an image acquisition mechanism installed on the handle, the image acquisition mechanism comprises a mounting frame and visual cameras and a laser marker installed on the mounting frame, the number of the visual cameras is three, the mounting frame comprises a mounting portion, a base and a hinged seat, the base and the hinged seat are hinged to form a U-shaped image acquisition area, the visual cameras are installed on the inner walls of the base and the hinged seat and are arranged in a semi-ring array, the handle is a hollow cylindrical structure, a processor is arranged in the handle, a display is arranged on the outer wall of the handle, and the mounting portion is connected to the inner wall of the handle in a buckle type. Workers can replace detection heads according to different cable sizes, move the handheld acquisition device along the length direction of the cable to detect the cable, and utilize the multiple visual cameras to comprehensively detect the cable in the circumferential direction.

Description

Technical Field

[0001] This invention belongs to the field of cable appearance inspection technology, specifically relating to a cable laying inspection device and inspection method. Background Technology

[0002] Intelligent cable laying is a key technology in power grids, which can improve construction efficiency and meet the needs of large-scale power grid construction. Therefore, the quality of cable workmanship and the monitoring, analysis, judgment and feedback during construction are particularly important. The integrity of the cable's appearance is also one of the important factors that determine whether the overall cable will have faults after laying. Visual inspection of the cable is carried out using visual cameras. However, when inspecting cables, auxiliary equipment is often needed to support the cables.

[0003] For example, Chinese invention patent CN 219871061 U discloses a power cable testing device, including a base plate and a testing mechanism mounted on the base plate for testing the surface of the cable. The testing mechanism includes a mounting plate fixedly connected to the base plate, and a testing ring fixedly connected to the other end of the mounting plate. The testing ring is equipped with three vision sensors, which limit the testing area of ​​the cable under the limiting action of a limiting mechanism. However, operators cannot arbitrarily change the testing head according to different cable sizes, nor can they move the testing device along the length of the cable for testing. Furthermore, because this testing device needs to be fixed before testing the cable and has a complex testing structure, it cannot meet the requirement of allowing personnel to easily handhold and test the cable, nor can it meet the need for flexible changes in the order of testing positions as needed. Summary of the Invention

[0004] The purpose of this invention is to provide a cable laying detection device to solve the technical problem that existing cable detection devices have complex structures and cannot move along the length of the cable for detection.

[0005] The present invention also provides a detection method using a cable laying detection device.

[0006] The technical solution of this invention to solve its technical problem is as follows: A cable laying detection device includes a handle and an image acquisition mechanism mounted on the handle. The image acquisition mechanism includes a mounting frame and a vision camera and a laser marking device mounted on the mounting frame. The number of vision cameras is three. The mounting frame includes a mounting part, a base, and a hinge seat. The base and the hinge seat are hinged to form a U-shaped image acquisition area. The vision cameras are mounted on the inner walls of the base and the hinge seat and are distributed in a semi-circular array. The handle has a hollow cylindrical structure. A processor is installed inside the handle, and a display is installed on the outer wall of the handle. The mounting part is snap-fitted to the inner wall of the handle.

[0007] The outer wall of the mounting part is provided with elastic snaps and latches; the inner wall of the handle is provided with snap grooves and latches that cooperate with the elastic snaps and latches; the inner wall of the handle is also provided with vertical grooves for the mounting part to be inserted into and the handle to be removed.

[0008] The hinge seat is provided with a hinge shaft, and the hinge seat is hinged to the base through both ends of the hinge shaft. The hinge shaft is provided with a torsion spring. The base has a first pin hole on each of its front and rear sides, and the hinge seat has a second pin hole on each of its front and rear sides. The base and the front and rear sides of the hinge seat are connected by a limiting pin passing through the first pin hole and the second pin hole.

[0009] The processor includes: a scanning module, used to acquire visual images of the cable identification obtained by the visual camera when the detection is started, and to combine the visual images along the circumferential direction of the cable to form a target image; The analysis module is configured with a point cloud model to construct a 3D model of the cable and target image, and performs point cloudification processing on the 3D model to form appearance feature sampling and obtain point cloud features under point cloudification; the analysis strategy configured in the analysis module is used to analyze the point cloud features, determine whether there are anomalies in the target image corresponding to the point cloud features, and generate anomaly data when anomalies are found. The marking module is used to generate marking information based on the acquired abnormal data, and then use a laser marking device to mark the abnormal location on the cable according to the marking information.

[0010] A detection method using a cable laying detection device includes the following steps: S1: Identify cable materials, determine cable colloids, and establish a standard colloid 3D model; use a sampling function to sample the surface of the colloid 3D model to obtain sampled point cloud data; S2: Configure point cloud discrete boxes based on the sampled point cloud data, use the point cloud discrete boxes to cover the 3D point cloud model to construct a 3D point cloud model network, obtain the point cloud concentrated area within each point cloud discrete box based on the 3D point cloud model network, and extract the feature information of normal vector, curvature, and cross-sectional contour line within the point cloud concentrated area to form standard point cloud features. S3: The visual camera collects information about the cable to be inspected. Based on the scanning strategy configured in the scanning module of the processor, the images collected by the visual camera are synthesized to form a target image. The analysis module compares the point cloud features of the cable to be inspected with the standard point cloud features to determine whether the point cloud feature values ​​of the cable to be inspected exceed the set range. If so, the cable segment is abnormal, and the abnormal data is sent to the marking module. The marking module issues an instruction, and the laser marking device marks the abnormal position with laser after receiving the instruction. If not, the cable segment is not abnormal, and the remaining cable is inspected.

[0011] The sampling function in step S1 is: Where a is the distance weight, x is the number of sampling points, L is the spacing between point cloud data, and a1 is the perimeter weight of the cable.

[0012] The scanning strategy in step S3 is as follows: D1: Label the vision camera and the images captured by the vision camera, and construct a cable model in space with the cable axis and the cable cross-section as the reference. D2: Fit all acquired images to the cable model, delete overlapping areas, and form the target image.

[0013] The scanning strategy also includes centering logic, which involves making a tangent along the cable at the intersection point, connecting the center of the cable to the intersection point and drawing a perpendicular line to the tangent line, and identifying the intersection point of the centering camera's recognition center point and the cable.

[0014] The standard point cloud features in step S2 also include texture parameters. The texture parameters are compared with the corresponding surface textures in the texture database to determine whether there are any abnormalities, and abnormal data is generated when an abnormality occurs.

[0015] The specific steps of the laser marking are as follows: Q1: Create initial markers on the display and generate alignment paths; Q2: The moving handle displays the position of the laser marker on the alignment path. When the laser marker moves to an abnormal position, an alignment signal is generated. Q3: Using the initial marking as a reference, laser mark the abnormal locations.

[0016] The beneficial effects of this invention are as follows: By setting a handle and an image acquisition mechanism mounted on the handle, cable inspection becomes more convenient. Operators can replace the image acquisition mechanism on the handle according to different cable sizes. The handle is hinged to the base at both ends via a hinge shaft, which is equipped with a torsion spring. The front and rear sides of the base and hinge are connected and fixed by limiting pins passing through the first and second pin holes. This makes it easier to secure the cable during inspection and remove it after inspection. The outer wall of the mounting part is equipped with snaps and latches, and the inner wall of the handle has a hollow cylindrical structure with vertical grooves, snap grooves, and latching grooves. The mounting part is snapped into the inner wall of the handle, making it easier to replace the image acquisition mechanism on the handle. Operators can use a handheld acquisition device to move and inspect the cable along its length, and multiple vision cameras can be used to achieve comprehensive circumferential inspection of the cable.

[0017] By identifying the cable material, a 3D model is established, and point cloud data of the 3D model is collected to obtain standard point cloud features. The point cloud features of the cable to be inspected are compared with the standard point cloud features to determine the abnormal location. The abnormal location is marked using a processor, monitor, and laser marking device to facilitate the handling of the abnormal location by the staff. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a schematic diagram illustrating the connection relationship between the image acquisition mechanism and the handle of the present invention; Figure 3 This is a three-dimensional structural diagram of the image acquisition mechanism of the present invention after it has been removed from the handle; Figure 4 This is a schematic diagram of the image acquisition mechanism of the present invention after the limiting pin base and hinge seat are removed; Figure 5 This is a three-dimensional structural diagram of the image acquisition mechanism of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0020] like Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 As shown, a cable laying detection device of the present invention includes a handle 1 and an image acquisition mechanism 2 mounted on the handle 1. The handle 1 is a hollow cylindrical structure, with a processor installed inside and a display installed on the outer wall of the handle 1. A cable passage hole is provided in the mounting part, and the image acquisition mechanism 2 is connected to the processor through the cable passage hole. The image acquisition mechanism 2 includes a mounting frame and a vision camera 3 and a laser marking device (not shown) mounted on the mounting frame. The laser marking device is positioned on the side of the vision camera used to acquire centering images. The mounting frame includes a mounting part 11, a base 4, and a hinge seat 5. The space enclosed by the base 4 and the hinge seat 5 forms a U-shaped image acquisition area, which also serves as the passage space for the cable during image acquisition. The vision cameras 3 are mounted on the inner walls of the base 4 and the hinge seat in a semi-circular array. Specifically, there are three vision cameras 3, equally spaced on the inner walls of the base 4 and the hinge seat. The viewing angles of the three vision cameras 3 compensate for each other, thereby achieving 360° detection of the cable circumference. The vision cameras 3 can be fixed by a clip-on mechanism.

[0021] The mounting part 11 is snap-fitted to the inner wall of the handle 1. Specifically, the upper part of the inner wall of the handle 1 is provided with a vertical groove 14, a snap groove 12, and a locking groove 13. The outer wall of the mounting part 11 is provided with a spring-loaded snap button 22 and a locking block 21. During installation, the snap button 22 and the locking block 21 are aligned with the vertical groove 14, so that the mounting part 11 is inserted into the upper part of the handle along the vertical groove 14. When the mounting part 11 is fully inserted into the handle, the positions of the snap button 22 and the snap groove 12, and the locking block 21 and the locking groove 13 correspond. By rotating the image acquisition mechanism 2, the snap button 22 is snapped into the snap groove 12 and rotates along the snap groove 12 to the end of the snap groove 12. At the same time, the locking block 21 rotates along the locking groove 13 to the end of the locking groove 13. Since both the snap button 22 and the locking block 21 are spring-loaded, the image acquisition mechanism 2 is firmly installed and fixed on the handle 1. Similarly, when disassembly is required, the image acquisition mechanism 2 is rotated in the reverse direction, causing the snap 22 and the locking block 21 to rotate to the openings of the snap groove 12 and the locking groove 13, respectively, so that the image acquisition mechanism 2 can be removed from the handle 1 along the vertical groove 14. By setting a detachable connection between the image acquisition mechanism 2 and the handle 1, the cable inspection device can quickly replace the image acquisition mechanism 2 when inspecting cables of different specifications.

[0022] The hinge seat 5 is equipped with a hinge shaft, and the hinge seat is hinged to the base 4 at both ends via the hinge shaft 51. A torsion spring 52 is mounted on the hinge shaft 51. The base 4 has a first pin hole 54 on each of its front and rear sides, and the hinge seat 5 has a second pin hole 53 on each of its front and rear sides. The base 2 and the hinge seat 5 are connected on their front and rear sides by a limiting pin 6 passing through the first pin hole 54 and the second pin hole 53. During cable inspection, the two limiting pins 6 are pulled out of the first and second pin holes, and the hinge seat 5 rotates outward under the action of the torsion spring 52. After the cable is placed in the U-shaped image acquisition area, the limiting pins 6 are reinserted into the first pin hole 54 and the second pin hole 53, forming a fixed connection between the hinge seat 5 and the base 4. The operator can then hold the entire structure and move it along the length of the cable for inspection. Similarly, when it is necessary to remove the cable from the cable laying detection device, pull the two limit pins 6 out of the first pin hole and the second pin hole again. The hinge seat 5 rotates outward under the action of the torsion spring 52, and the cable is taken out from one side of the image acquisition mechanism 2. After the cable is taken out of the U-shaped image acquisition area, reinsert the limit pins 6 into the first pin hole 54 and the second pin hole 53, waiting for the next use by the staff.

[0023] The processor includes: The scanning module is used to acquire the visual image of the cable identification obtained by the vision camera when the detection is started, and to combine the visual image along the circumference of the cable to form the target image. The analysis module is configured with a point cloud model to construct a 3D model of the cable and target image, and performs point cloudification processing on the 3D model to form appearance feature sampling and obtain point cloud features under point cloudification; the analysis module is configured to analyze the point cloud features to determine whether there are anomalies in the target image corresponding to the point cloud features, and generate anomaly data when anomalies are found. The marking module is used to generate marking information based on the acquired abnormal data, and then use a laser marking device to mark the abnormal location on the cable according to the marking information.

[0024] A detection method using a cable laying detection device according to the present invention includes the following steps: S1: Identify cable materials, determine cable colloids, and establish a standard colloid 3D model; use a sampling function to sample the surface of the colloid 3D model to obtain sampled point cloud data; S2: Configure point cloud discrete boxes based on the sampled point cloud data, use the point cloud discrete boxes to cover the 3D point cloud model to construct a 3D point cloud model network, obtain the point cloud concentrated area within each point cloud discrete box based on the 3D point cloud model network, and extract the feature information of normal vector, curvature, and cross-sectional contour line within the point cloud concentrated area to form standard point cloud features. S3: The vision camera collects information about the cable to be inspected. Based on the scanning strategy configured in the scanning module of the processor, the images collected by the vision camera are synthesized to form a target image. The analysis module compares the point cloud features of the cable to be inspected with the standard point cloud features to determine whether the point cloud feature values ​​of the cable to be inspected exceed the set range. If so, the cable segment is abnormal, and the abnormal data is sent to the marking module. The marking module issues an instruction, and the laser marking device marks the abnormal position with laser after receiving the instruction. If not, the cable segment is not abnormal, and the remaining cable is inspected.

[0025] The sampling function in step S1 is: Where a is the distance weight, x is the number of sampling points, L is the spacing between point cloud data, and a1 is the perimeter weight of the cable.

[0026] The scanning strategy in step S3 is as follows: D1: Label the vision camera and the images captured by the vision camera, and construct a cable model in space with the cable axis and the cable cross-section as the reference. D2: Fit all acquired images to the cable model, delete overlapping areas, and form the target image.

[0027] More specifically, the three visual cameras are numbered as Side Camera 1, Centering Camera, and Side Camera 2. The visual images include Side Camera 1, Side Camera 2, and Centering Image. The correspondence is as follows: Side Camera 1 is generated from cable identification by Side Camera 1, Side Camera 2 is generated from cable identification by Side Camera 2, and Centering Image is generated from cable identification by the Centering Camera. A cable model is constructed using the cable's axis and cross-section as a reference space. To obtain more accurate images, the scanning strategy also includes centering logic. The centering logic identifies the intersection point of the centering camera's identification midpoint and the cable. A tangent is drawn along the cable at the intersection point. A perpendicular line is drawn from the intersection point to the center of the cable, perpendicular to the tangent. This perpendicular line is the centering camera's focusing axis. The Centering Image is obtained by identifying the cable along the focusing axis direction. The first and second side images are retrieved and fitted into the cable model respectively. There is an overlapping area between the first and second side images, denoted as the first region. The boundary of the first region is determined and a first border is formed. The area value of the first border is obtained. The first border is centered and cut to obtain the first and second side borders. The first border is fitted to the first side image, and the second border is fitted to the second side image. After fitting, the first and second side borders are stitched together to form a lateral composite image representing the lateral appearance of the cable. The centering image is retrieved and fitted into the cable model together with the lateral composite image. There is an overlapping area between the lateral composite image and the centering image, denoted as the second region. The boundary of the second region is determined and a second border is formed. The position of the second border in the lateral composite image is identified, and a stitching line is formed along the lateral composite image. The portion of the centering image within the second border is obtained. The portion of the centering image within the second border is fitted onto the lateral composite image along the stitching line, thus forming a target image representing the appearance of the cable.

[0028] The standard point cloud features in step S2 also include texture parameters. The texture parameters are compared with the corresponding surface textures in the texture database to determine whether there are any abnormalities, and abnormal data is generated when an abnormality occurs.

[0029] The analysis module is also equipped with a texture database, which records the surface textures of different cable colloids. During texture analysis, the 3D model of the colloid is retrieved, and the corresponding colloid in the texture database is matched based on the cable colloid represented in the 3D model. The texture parameters in the point cloud features are identified, and the texture parameters are compared with the corresponding surface textures in the texture database to determine if an anomaly has occurred. When an anomaly occurs, anomaly data is generated, including the anomaly location and the anomaly area. The anomaly location represents the position where the anomaly appears in the 3D model of the colloid, and the anomaly area represents the area value of the texture anomaly region.

[0030] The specific steps of the laser marking are as follows: Q1: Create initial markers on the display and generate alignment paths; Q2: The moving handle displays the position of the laser marker on the alignment path. When the laser marker moves to an abnormal position, an alignment signal is generated. Q3: Using the initial marking as a reference, laser mark the abnormal locations.

[0031] The specific method by which the analysis strategy in the processor analyzes point cloud features and generates anomalous data is as follows: The specific methods of laser marking based on anomalous data include: The process involves acquiring abnormal locations from the anomaly data, identifying the relative position of the laser marker within the colloidal 3D model based on these locations, forming an alignment path, and displaying this path on a monitor. An initial mark is created on the monitor, representing the real-time position of the laser marker. A moving handle drives the detection head circumferentially along the cable, displaying the laser marker's movement along the alignment path. When the laser marker reaches the corresponding abnormal location, an alignment signal is generated, causing the initial mark on the monitor to brighten in red, and a marking signal is generated. Based on this signal, the laser marker is controlled to form the laser mark. The process also involves acquiring the area of ​​the abnormal region from the anomaly data, determining the location of the cable's appearance anomaly based on this area, and then forming a laser mark on the area corresponding to the anomaly location. This allows for rapid identification of cable appearance anomalies during troubleshooting.

[0032] This invention uses a visual camera to detect the appearance of a cable as it moves along the cable. The detected visual image is fitted to form a target image that characterizes the cable's appearance. After obtaining the target image, a point cloud model is used to form point cloud features that characterize the cable's appearance. Based on the point cloud features, it is determined whether there is an appearance abnormality at the corresponding position in the target image. When an abnormality is detected, abnormal data is generated, and the abnormal data is used to control a laser marking device to move to the abnormal position and laser mark the abnormal area. This achieves the determination of the position after detection along the cable length, so that the appearance of the laser-marked position can be quickly identified and investigated during the inspection.

[0033] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

Claims

1. A cable laying detection device, characterized in that: The device includes a handle and an image acquisition mechanism mounted on the handle. The image acquisition mechanism includes a mounting frame and three vision cameras mounted on the mounting frame. The mounting frame includes a mounting part, a base, and a hinged seat. The base and hinged seat are hinged to form a U-shaped image acquisition area. The vision cameras are mounted on the inner walls of the base and hinged seat and are arranged in a semi-circular array. The handle has a hollow cylindrical structure. A processor is installed inside the handle, and a display is installed on the outer wall of the handle. The mounting part is snap-fitted to the inner wall of the handle. The outer wall of the mounting part is provided with elastic snaps and latches. The inner wall of the handle is provided with snap grooves and latches that cooperate with the elastic snaps and latches. The inner wall of the handle is also provided with vertical grooves for inserting and removing the mounting part from the handle.

2. The cable laying detection device according to claim 1, characterized in that: The hinge seat is provided with a hinge shaft, and the hinge seat is hinged to the base through both ends of the hinge shaft. The hinge shaft is provided with a torsion spring. The base has a first pin hole on each of its front and rear sides, and the hinge seat has a second pin hole on each of its front and rear sides. The base and the front and rear sides of the hinge seat are connected by a limiting pin passing through the first pin hole and the second pin hole.

3. The cable laying detection device according to claim 1, characterized in that, The processor includes: a scanning module, used to acquire visual images of the cable identification obtained by the visual camera when the detection is started, and to combine the visual images along the circumferential direction of the cable to form a target image; The analysis module is configured with a point cloud model to construct a 3D model of the cable and target image, and performs point cloudification processing on the 3D model to form appearance feature sampling and obtain point cloud features under point cloudification; the analysis module is used to analyze the point cloud features, determine whether there are anomalies in the target image corresponding to the point cloud features, and generate anomaly data when anomalies are detected. The marking module is used to generate marking information based on the acquired abnormal data, and then use a laser marking device to mark the abnormal location on the cable according to the marking information.

4. A detection method using the cable laying detection device described in claims 1-3, characterized in that, Includes the following steps: S1: Identify cable materials, determine cable colloids, and establish a standard colloid 3D model; use a sampling function to sample the surface of the colloid 3D model to obtain sampled point cloud data; S2: Configure point cloud discrete boxes based on the sampled point cloud data, use the point cloud discrete boxes to cover the 3D point cloud model to construct a 3D point cloud model network, obtain the point cloud concentrated area within each point cloud discrete box based on the 3D point cloud model network, and extract the feature information of normal vector, curvature, and cross-sectional contour line within the point cloud concentrated area to form standard point cloud features. S3: The visual camera collects information about the cable to be inspected. Based on the scanning strategy configured in the scanning module of the processor, the images collected by the visual camera are synthesized to form a target image. The analysis module compares the point cloud features of the cable to be inspected with the standard point cloud features to determine whether the point cloud feature values ​​of the cable to be inspected exceed the set range. If so, the cable segment is abnormal, and the abnormal data is sent to the marking module. The marking module issues an instruction, and the laser marking device marks the abnormal position with laser after receiving the instruction. If not, the cable segment is not abnormal, and the remaining cable is inspected.

5. The detection method of the cable laying detection device according to claim 4, characterized in that: The sampling function in step S1 is: Where a is the distance weight, x is the number of sampling points, L is the spacing between point cloud data, and a1 is the perimeter weight of the cable.

6. The detection method of the cable laying detection device according to claim 4, characterized in that: The scanning strategy in step S3 is as follows: D1: Label the vision camera and the images captured by the vision camera, and construct a cable model in space with the cable axis and the cable cross-section as the reference. D2: Fit all acquired images to the cable model, delete overlapping areas, and form the target image.

7. The detection method of the cable laying detection device according to claim 6, characterized in that: The scanning strategy also includes centering logic, which involves making a tangent along the cable at the intersection point, connecting the center of the cable to the intersection point and drawing a perpendicular line to the tangent line, and identifying the intersection point of the centering camera's recognition center point and the cable.

8. The detection method of the cable laying detection device according to claim 4, characterized in that: The standard point cloud features in step S2 also include texture parameters. The texture parameters are compared with the corresponding surface textures in the texture database to determine whether there are any abnormalities, and abnormal data is generated when an abnormality occurs.

9. The detection method of the cable laying detection device according to claim 6, characterized in that: The specific steps of the laser marking are as follows: Q1: Create initial markers on the display and generate alignment paths; Q2: The moving handle displays the position of the laser marker on the alignment path. When the laser marker moves to an abnormal position, an alignment signal is generated. Q3: Using the initial marking as a reference, laser mark the abnormal locations.

Images