CN117308781A - On-line visual detection device and detection method for transformer coil die - Google Patents
On-line visual detection device and detection method for transformer coil die Download PDFInfo
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- CN117308781A CN117308781A CN202311264861.6A CN202311264861A CN117308781A CN 117308781 A CN117308781 A CN 117308781A CN 202311264861 A CN202311264861 A CN 202311264861A CN 117308781 A CN117308781 A CN 117308781A
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- 238000001514 detection method Methods 0.000 title claims abstract description 44
- 230000000007 visual effect Effects 0.000 title claims abstract description 20
- 230000003287 optical effect Effects 0.000 claims abstract description 11
- 238000005259 measurement Methods 0.000 claims description 17
- 238000000034 method Methods 0.000 claims description 14
- 238000011179 visual inspection Methods 0.000 claims description 8
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 claims description 3
- YTAHJIFKAKIKAV-XNMGPUDCSA-N [(1R)-3-morpholin-4-yl-1-phenylpropyl] N-[(3S)-2-oxo-5-phenyl-1,3-dihydro-1,4-benzodiazepin-3-yl]carbamate Chemical compound O=C1[C@H](N=C(C2=C(N1)C=CC=C2)C1=CC=CC=C1)NC(O[C@H](CCN1CCOCC1)C1=CC=CC=C1)=O YTAHJIFKAKIKAV-XNMGPUDCSA-N 0.000 claims description 3
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- 239000000284 extract Substances 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 description 11
- 230000007547 defect Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
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- 230000014759 maintenance of location Effects 0.000 description 1
- 238000004062 sedimentation Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
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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
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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
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Abstract
The online visual detection device comprises a base, wherein a rotary table is arranged on the base, a six-axis robot is arranged on the outer side of the rotary table, a support and an industrial personal computer are arranged on the outer side of the base, an optical tracker is arranged at the top of the support, a tracking type three-dimensional scanning system is arranged at the front end of the six-axis robot, and a 3D camera is further arranged on a six-axis robot clamping jaw; the detection method adopts a mode that the six-axis robot and the rotary table are mutually matched, can detect the coil mould from different angles, adopts a 3D camera, can rapidly scan the whole target in a 3D space, extracts key parameters such as various sizes, shapes, positions and the like of the coil mould of the dry-type transformer with high precision, and can rapidly obtain high-quality 3D point cloud data, so that the efficiency of measuring the size of the mould is remarkably improved; the robot automatic control processing mode is adopted, and the dependence on limiting factors such as manpower, level and state of the robot automatic control processing mode is not needed, so that labor cost is reduced, and meanwhile consistency and stability of a measuring result are ensured.
Description
Technical Field
The invention relates to the technical field of transformer manufacturing detection, in particular to an online visual detection device and method for a transformer coil die.
Background
At present, for size detection of a dry-type transformer die, a manual measurement mode is mainly relied on, the manual measurement error is large, the efficiency is low, and meanwhile effective data retention cannot be formed. Although some manufacturers have begun to use machine vision technology for quality inspection in production processes, two-dimensional still image recognition is currently mainly limited, and two-dimensional image measurement has the following defects and shortcomings:
1. the spatial relationship between the three-dimensional shape of the object and the plurality of faces cannot be truly reflected;
2. the lack of complete three-dimensional information, limited dimensional and scale information for several facets can only be obtained by computer processing and inference, resulting in limited accuracy of the results;
3. the problems of misidentification and the like are likely to occur under the influence of factors such as light, angle, shielding, distortion and the like.
The prior art has the defects of long detection time and data error.
Patent application CN201911244166.7 discloses a method and apparatus for distributed visual inspection, the method comprising: a) Installing visual detection equipment on production equipment; b) The visual detection equipment reads the default configuration; c) The vision detection equipment is registered to the server; d) The vision detection equipment acquires images; e) The vision detection equipment sends the acquired image to a server; f) The server performs image recognition and analysis on the received image; g) The server feeds the identification result back to the visual detection equipment; h) The visual detection equipment outputs the identification result to the production equipment; i) And ending the detection. The visual inspection equipment is simplified, standardized and low in cost, but cannot monitor and track in real time to provide monitoring and analysis of internal and external dimension parameters of the mold and deposit data, so that good technical support and numerical management resources are provided for enterprise manufacturing.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide an online visual detection device and a detection method for a transformer coil mould, which adopt a mode that a robot and a tracking three-dimensional scanning system are mutually matched, can detect the coil mould from different angles, rapidly scan the whole target finished product in a 3D space, extract key parameters such as various sizes, shapes, positions and the like of the dry type transformer coil mould with high precision, and can rapidly obtain high-quality 3D point cloud data, so that the efficiency of mould measurement is obviously improved; the robot automatic control processing mode is adopted, and the dependence on limiting factors such as manpower, level and state of the robot automatic control processing mode is not needed, so that labor cost is reduced, and meanwhile consistency and stability of a measuring result are ensured.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the utility model provides an online visual inspection device of transformer coil mould, includes base 1, is equipped with revolving stage 2 on the base 1, and the base is gone up and the revolving stage 2 outside is provided with six robots 3, and the base 1 outside is equipped with support 4 and industrial computer 7, and the support 4 top is equipped with optical tracker 5, and six robots 3 front ends are equipped with tracking three-dimensional scanning system 6, still are equipped with 3D camera on the 3 clamping jaws of six robots.
The data output end of the tracking type three-dimensional scanning system 6 and the 3D camera are connected with the data receiving end of the industrial personal computer 7 through a PLC, a display screen is arranged on the industrial personal computer 7, the data output end of the industrial personal computer 7 displays shooting data and identification results of the tracking type three-dimensional scanning system 6 and the 3D camera in real time through the display screen, and the control end of the industrial personal computer 7 controls the rotary table 2, the six-axis robot 3 and the optical tracker 5 to operate respectively through the PLC.
The bottom of the rotary table 2 is provided with a supporting roller 8.
The control end of the industrial personal computer 7 is provided with a 3D detection program, and the 3D detection program can realize 3D visual detection of the dry-type transformer coil mould during operation.
A detection method of a 3D visual detection device based on a dry-type transformer coil mould specifically comprises the following steps:
step 1: initializing the industrial personal computer 7, transmitting the rotation times of the rotary table to the industrial personal computer 7 by the PLC and the MES system, butting the industrial personal computer 7 with the MES through an HTTP protocol, transmitting the product ID to the MES system through the industrial personal computer 7, searching the related measurement standard value and allowable deviation value of the position to be measured by the MES system through the ID number, and transmitting the measurement standard value and allowable deviation value to the industrial personal computer 7;
step 2: the PLC sends an opening signal to the six-axis robot 3 through a TCP/IP protocol;
step 3: the six-axis robot 3 moves to a designated position, and transmits an in-place signal to the industrial personal computer 7 through a TCP/IP protocol;
step 4: the industrial personal computer 7 triggers a 3D camera to shoot, acquires 3D point cloud information, processes an image by using a 3D algorithm to obtain a coordinate point of a transformer coil mould, and confirms the distance between the coil mould and the 3D camera by using a 3D ranging algorithm;
step 5: the industrial personal computer 7 obtains the coordinate point location information of the transformer coil mould according to the step 4, and automatically adds offset for the coil mould product, and plans the motion path of the six-axis robot 3;
step 6: the industrial personal computer 7 controls the six-axis robot 3 to move according to the planned motion path;
step 7: after the industrial personal computer 7 is in place, transmitting an in-place feedback signal to the industrial personal computer 7 through a TCP/IP protocol;
step 8: the industrial personal computer 7 controls the tracking type three-dimensional scanning system 6 through a TCP/IP protocol, and sends a starting signal to the tracking type three-dimensional scanning system 6;
step 9: the industrial personal computer 7 controls the six-axis robot 3 to run and scan according to a preset track through a TCP/IP protocol to obtain point cloud data of a coil mould;
step 10: after scanning, the six-axis robot runs to a shooting pose preset by the 3D camera, the distance between the 3D camera of the coil mould is obtained, and the motion path of the six-axis robot 3 is planned again;
step 11: after the coil mould is operated, the six-axis robot 3 transmits an operation signal to the PLC through a TCP/IP protocol;
step 12: the PLC transmits a signal for completing the operation of the six-axis robot 3 to the industrial personal computer 7 through a TCP/IP protocol;
step 13: the PLC controls the turntable to rotate by a preset angle, the tracking three-dimensional scanning system 6 scans from top to bottom, the optical tracker and the coil mould rotate along with the turntable, and the whole coil mould is scanned;
step 14: cycling the steps 3 to 13;
step 15: after the circulation is completed, the industrial personal computer 7 closes the tracking three-dimensional scanning system 6, and the point cloud data is dropped; after the tracking three-dimensional scanning system 6 scans the complete coil, the point cloud data is automatically stored and stored in a local disk, and the industrial personal computer 7 automatically reads the data of the local disk for detection;
step 16: the industrial personal computer 7 takes the point cloud from the drive letter to the algorithm to measure and display the result: aiming at the characteristics of the coil mold point cloud, the coil 3D point cloud acquired by the visual detection equipment is extracted based on the characteristics, the measured value of each required position is calculated, and the measured data is transmitted to an MES system through an interface to save and judge the result.
The specific method for obtaining the point cloud in the steps 9 to 16 and then analyzing the point cloud to form the measurement data is as follows:
step a. Data are cleared: clearing data existing on the premise of last scanning or previous importing, and preparing for scanning;
step b, clearing the marked point library: the mark points which are scanned last time or imported before are cleared and used as preparation work before scanning;
step c, introducing mark points: the tracking type three-dimensional scanning system 6 assists in scanning initial positioning by setting a mark point in a working area, and the relative position of data acquired by the tracking type three-dimensional scanning system 6 in a three-dimensional space is determined;
step d, scanning and setting: the smaller the set point distance, namely the resolution value, the smaller the point distance, and the larger the laser exposure, namely the laser intensity exposure, the larger the laser intensity;
step e, turning on the laser of the tracking three-dimensional scanning system 6;
waiting for the end of the scan: carrying out sectional scanning, completing a section of scanning, enabling the robot to drive the tracking type three-dimensional scanning system 6 to return to the original point, triggering the rotary table 2 to rotate, enabling the robot to drive the tracking type three-dimensional scanning system 6 to continue scanning, and keeping the laser opening state of the tracking type three-dimensional scanning system 6 until the scanning is finished;
step g, closing the laser of the tracking three-dimensional scanning system 6;
stopping scanning: stopping collecting data after all scanning is completed;
deleting or removing data unrelated to the coil mold measurement data;
step j, grid packaging: connecting the point cloud data into a surface;
and k, storing data, and obtaining a detection result.
Compared with the prior art, the invention has the following technical effects:
1. and the key parameters such as various sizes, shapes, positions and the like of the coil mould of the dry-type transformer can be extracted in a 3D space with high precision by adopting a 3D visual detection technology.
2. High efficiency: the six-axis robot 3 and the rotary table are matched with each other, so that the whole target finished product can be rapidly scanned, high-quality 3D point cloud data can be rapidly obtained, and the efficiency of measuring the size of the finished product is remarkably improved.
3. And the automation is realized by adopting an automatic mode of robot control and point cloud data processing, and the dependence on limiting factors such as manpower, level and state thereof and the like is not needed, so that the labor cost is reduced, and the consistency and stability of the measurement result are ensured.
4. Traceability, namely, the obtained physical data can be uploaded to an MES system and integrated into an ERP system of an enterprise, so that the system has complete data record and history traceability, and the product quality is effectively improved.
5. Multiplex detection: the 3D visual detection device provided by the invention is not only suitable for detecting the size of the coil mould, but also can determine any angle, position and size in the three-dimensional space of the object, and reduces the influence of human factors on the production quality.
In summary, the invention can obviously improve the efficiency and quality of the production process of the dry-type transformer coil mould, reduce the labor cost and error, and can efficiently manage and write data by an automatic mode and the filing application of data manufacture, thereby improving the production and manufacturing process level of the dry-type transformer.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Fig. 2 is a flow chart of the method of the present invention.
In the figure: 1. a base; 2. a rotary table; 3. a six-axis robot; 4. a bracket; 5. an optical tracker; 6. a tracking three-dimensional scanning system; 7. an industrial personal computer; 8. and supporting the roller.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, an online visual inspection device for a transformer coil die comprises a base 1, wherein a rotary table 2 is arranged on the base 1, a six-axis robot 3 is arranged on the base and outside the rotary table 2, a support 4 and an industrial personal computer 7 are arranged on the outer side of the base 1, an optical tracker 5 is arranged at the top of the support 4, a tracking three-dimensional scanning system 6 is arranged at the front end of the six-axis robot 3, and a 3D camera is further arranged on a clamping jaw of the six-axis robot 3.
The data output end of the tracking type three-dimensional scanning system 6 and the 3D camera are connected with the data receiving end of the industrial personal computer 7 through a PLC, a display screen is arranged on the industrial personal computer 7, the data output end of the industrial personal computer 7 displays shooting data and identification results of the tracking type three-dimensional scanning system 6 and the 3D camera in real time through the display screen, and the control end of the industrial personal computer 7 controls the rotary table 2, the six-axis robot 3 and the optical tracker 5 to operate respectively through the PLC.
The bottom of the rotary table 2 is provided with a supporting roller 8.
The control end of the industrial personal computer 7 is provided with a 3D detection program, and the 3D detection program can realize 3D visual detection of the dry-type transformer coil mould during operation; the efficiency and quality of the transformer die production process can be remarkably improved, the labor cost and error are reduced, and data for real-time monitoring and sedimentation are provided.
A detection method of a 3D visual detection device based on a dry-type transformer coil mould specifically comprises the following steps:
step 1: initializing the industrial personal computer 7, transmitting the rotation times of the rotary table to the industrial personal computer 7 by the PLC and the MES system, butting the industrial personal computer 7 with the MES through an HTTP protocol, transmitting the product ID to the MES system through the industrial personal computer 7, searching the related measurement standard value and allowable deviation value of the position to be measured by the MES system through the ID number, and transmitting the measurement standard value and allowable deviation value to the industrial personal computer 7;
step 2: the PLC sends an opening signal to the six-axis robot 3 through a TCP/IP protocol;
step 3: the six-axis robot 3 moves to a designated position, and transmits an in-place signal to the industrial personal computer 7 through a TCP/IP protocol;
step 4: the industrial personal computer 7 triggers a 3D camera to shoot, acquires 3D point cloud information, processes an image by using a 3D algorithm to obtain a coordinate point of a transformer coil mould, and confirms the distance between the coil mould and the 3D camera by using a 3D ranging algorithm;
step 5: the industrial personal computer 7 obtains the coordinate point location information of the transformer coil mould according to the step 4, and automatically adds offset for the coil mould product, and plans the motion path of the six-axis robot 3;
step 6: the industrial personal computer 7 controls the six-axis robot 3 to move according to the planned motion path;
step 7: after the industrial personal computer 7 is in place, transmitting an in-place feedback signal to the industrial personal computer 7 through a TCP/IP protocol;
step 8: the industrial personal computer 7 controls the tracking type three-dimensional scanning system 6 through a TCP/IP protocol, and sends a starting signal to the tracking type three-dimensional scanning system 6;
step 9: the industrial personal computer 7 controls the six-axis robot 3 to run and scan according to a preset track through a TCP/IP protocol to obtain point cloud data of a coil mould;
step 10: after scanning, the six-axis robot runs to a shooting pose preset by the 3D camera, the distance between the 3D camera of the coil mould is obtained, and the motion path of the six-axis robot 3 is planned again;
step 11: after the coil mould is operated, the six-axis robot 3 transmits an operation signal to the PLC through a TCP/IP protocol;
step 12: the PLC transmits a signal for completing the operation of the six-axis robot 3 to the industrial personal computer 7 through a TCP/IP protocol;
step 13: the PLC controls the turntable to rotate by a preset angle, the tracking three-dimensional scanning system 6 scans from top to bottom, the optical tracker and the coil mould rotate along with the turntable, and the whole coil mould is scanned;
step 14: cycling the steps 3 to 13;
step 15: after the circulation is completed, the industrial personal computer 7 closes the tracking three-dimensional scanning system 6, and the point cloud data is dropped; after the tracking three-dimensional scanning system 6 scans the complete coil, the point cloud data is automatically stored and stored in a local disk, and the industrial personal computer 7 automatically reads the data of the local disk for detection;
step 16: the industrial personal computer 7 takes the point cloud from the drive letter to the algorithm to measure and display the result: aiming at the characteristics of the coil mold point cloud, the coil 3D point cloud acquired by the visual detection equipment is extracted based on the characteristics, the measured value of each required position is calculated, and the measured data is transmitted to an MES system through an interface to save and judge the result.
The specific method for obtaining the point cloud in the steps 9 to 16 and then analyzing the point cloud to form the measurement data is as follows:
step a. Data are cleared: clearing data existing on the premise of last scanning or previous importing, and preparing for scanning;
step b, clearing the marked point library: the mark points which are scanned last time or imported before are cleared and used as preparation work before scanning;
step c, introducing mark points: the tracking type three-dimensional scanning system 6 assists in scanning initial positioning by setting a mark point in a working area, and the relative position of data acquired by the tracking type three-dimensional scanning system 6 in a three-dimensional space is determined;
step d, scanning and setting: the smaller the set point distance, namely the resolution value, the smaller the point distance, and the larger the laser exposure, namely the laser intensity exposure, the larger the laser intensity;
step e, turning on the laser of the tracking three-dimensional scanning system 6;
waiting for the end of the scan: carrying out sectional scanning, wherein the scanning is completed for a section, the robot drives the tracking type three-dimensional scanning system 6 to return to the original point, the rotating table 2 is triggered to rotate, the robot drives the tracking type three-dimensional scanning system 6 to continue scanning, and the laser is kept in an open state in the process until the scanning is finished;
step g, closing the laser of the tracking three-dimensional scanning system 6;
stopping scanning: stopping collecting data after all scanning is completed;
deleting or removing data unrelated to the coil mold measurement data;
step j, grid packaging: connecting the point cloud data into a surface;
and k, storing data, and obtaining a detection result.
When the coil mould size detection is carried out, the coil mould is moved to a detection station, a start button is started, the six-axis robot 3 moves to a designated position, the tracking type three-dimensional scanning system 6 and the 3D camera are driven to carry out size scanning on the coil mould, after the robot is operated to a preset position of the 3D camera after scanning, the rotating table 2 continues to scan after rotating, the coil mould is scanned, a complete point cloud image is synchronously formed, actual data of the required coil mould size is obtained after processing by the industrial personal computer 7, the actual data is compared with standard size data, and then the actual data is pushed and displayed, and the coil mould with qualified size is transported and put in storage.
Claims (6)
1. The utility model provides an online vision detection device of transformer coil mould, includes base (1), is equipped with revolving stage (2) on base (1), and the revolving stage (2) outside is provided with six robots (3) on the base, and the base (1) outside is equipped with support (4) and industrial computer (7), and support (4) top is equipped with optical tracker (5), and six robots (3) front end is equipped with tracking three-dimensional scanning system (6), still is equipped with 3D camera on six robots (3) clamping jaw.
2. The on-line visual inspection device for a transformer coil mold according to claim 1, wherein: the tracking type three-dimensional scanning system (6) and the data output end of the 3D camera are connected with the data receiving end of the industrial personal computer (7) through the PLC, a display screen is arranged on the industrial personal computer (7), the data output end of the industrial personal computer (7) displays shooting data and identification results of the tracking type three-dimensional scanning system (6) and the 3D camera in real time through the display screen, and the control end of the industrial personal computer (7) respectively controls the rotary table (2), the six-axis robot (3) and the optical tracker (5) to operate through the PLC.
3. The on-line visual inspection device for a transformer coil mold according to claim 1, wherein: the bottom of the rotary table (2) is provided with a supporting roller (8).
4. The on-line visual inspection device for a transformer coil mold according to claim 1, wherein: the control end of the industrial personal computer (7) is provided with a 3D detection program, and the 3D detection program can realize 3D visual detection of the dry-type transformer coil mould during operation.
5. The detection method of the 3D visual detection device based on the dry-type transformer coil mould is characterized by comprising the following steps of: the method specifically comprises the following steps:
step 1: initializing an industrial personal computer (7), transmitting the rotation times of a rotary table to the industrial personal computer (7) by a PLC and an MES system, butting the industrial personal computer (7) with an MES through an HTTP protocol, transmitting a product ID to the MES system through the industrial personal computer (7), searching a relative measurement standard value and an allowable deviation value of a position to be measured by the MES system through an ID number, and transmitting the measurement standard value and the allowable deviation value to the industrial personal computer (7);
step 2: the PLC sends an opening signal to the six-axis robot 3 through a TCP/IP protocol;
step 3: the six-axis robot (3) moves to a designated position, and transmits an in-place signal to the industrial personal computer (7) through a TCP/IP protocol;
step 4: the industrial personal computer (7) triggers the 3D camera to shoot, acquires 3D point cloud information, processes an image by using a 3D algorithm to obtain a coordinate point of the transformer coil mould, and confirms the distance between the coil mould and the 3D camera by using a 3D ranging algorithm;
step 5: the industrial personal computer (7) obtains the coordinate point position information of the transformer coil mould according to the step 4, and automatically adds offset for the coil mould product, and plans the motion path of the six-axis robot (3);
step 6: the industrial personal computer (7) controls the six-axis robot (3) to move according to the planned motion path;
step 7: after the industrial personal computer (7) is in place, transmitting an in-place feedback signal to the industrial personal computer (7) through a TCP/IP protocol;
step 8: the industrial personal computer (7) controls the tracking type three-dimensional scanning system (6) through a TCP/IP protocol, and sends a starting signal to the tracking type three-dimensional scanning system (6);
step 9: the industrial personal computer (7) controls the six-axis robot (3) to run and scan according to a preset track through a TCP/IP protocol to obtain point cloud data of the coil mould;
step 10: after scanning, the six-axis robot runs to a shooting pose preset by the 3D camera, the distance between the 3D camera of the coil mould is obtained, and the motion path of the six-axis robot (3) is planned again;
step 11: after the coil mould is operated, the six-axis robot (3) transmits an operation signal to the PLC through a TCP/IP protocol;
step 12: the PLC transmits a running completion signal of the six-axis robot (3) to the industrial personal computer (7) through a TCP/IP protocol;
step 13: the PLC controls the turntable to rotate by a preset angle, the tracking three-dimensional scanning system (6) scans from top to bottom, the optical tracker and the coil mould rotate along with the turntable, and the whole coil mould is scanned;
step 14: cycling the steps 3 to 13;
step 15: after the circulation is completed, the industrial personal computer (7) closes the tracking three-dimensional scanning system (6) and the point cloud data falls on the disk; after the tracking three-dimensional scanning system (6) scans the complete coil, the point cloud data is automatically stored and stored in a local disk, and the industrial personal computer (7) automatically reads the data of the local disk for detection;
step 16: the industrial personal computer (7) takes the point cloud from the disk symbol to measure the algorithm and displays the result: aiming at the characteristics of the coil mold point cloud, the coil 3D point cloud acquired by the visual detection equipment is extracted based on the characteristics, the measured value of each required position is calculated, and the measured data is transmitted to an MES system through an interface to save and judge the result.
6. The method for on-line visual inspection of a transformer coil mold according to claim 5, wherein: the specific method for obtaining the point cloud in the steps 9 to 16 and then analyzing the point cloud to form the measurement data is as follows:
step a. Data are cleared: clearing data existing on the premise of last scanning or previous importing, and preparing for scanning;
step b, clearing the marked point library: the mark points which are scanned last time or imported before are cleared and used as preparation work before scanning;
step c, introducing mark points: the tracking type three-dimensional scanning system (6) assists in scanning initial positioning by setting mark points in a working area, and the relative position of data acquired by the tracking type three-dimensional scanning system (6) in a three-dimensional space is determined;
step d, scanning and setting: the smaller the set point distance, namely the resolution value, the smaller the point distance, and the larger the laser exposure, namely the laser intensity exposure, the larger the laser intensity;
step e, turning on the tracking type three-dimensional scanning system (6) laser;
waiting for the end of the scan: carrying out sectional scanning, wherein the scanning is completed for a section, the robot drives the tracking type three-dimensional scanning system (6) to return to the original point, the rotating table (2) is triggered to rotate, the robot drives the tracking type three-dimensional scanning system (6) to continue scanning, and the laser is kept in an open state in the process until the scanning is completed;
step g, closing the laser of the tracking three-dimensional scanning system (6);
stopping scanning: stopping collecting data after all scanning is completed;
deleting or removing data unrelated to the coil mold measurement data;
step j, grid packaging: connecting the point cloud data into a surface;
and k, storing data, and obtaining a detection result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311264861.6A CN117308781A (en) | 2023-09-28 | 2023-09-28 | On-line visual detection device and detection method for transformer coil die |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311264861.6A CN117308781A (en) | 2023-09-28 | 2023-09-28 | On-line visual detection device and detection method for transformer coil die |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117308781A true CN117308781A (en) | 2023-12-29 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311264861.6A Pending CN117308781A (en) | 2023-09-28 | 2023-09-28 | On-line visual detection device and detection method for transformer coil die |
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| Country | Link |
|---|---|
| CN (1) | CN117308781A (en) |
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2023
- 2023-09-28 CN CN202311264861.6A patent/CN117308781A/en active Pending
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