Automatic part online detection system and method based on full-automatic control platform

Abstract

The invention discloses an automobile part on-line detection system and method based on a full-automatic control platform, and relates to the technical field of automobile part detection platforms, and the key points of the technical scheme are that the system comprises a measurement unit which comprises a vision measurement sensor, a searchlight and a laser point vision auxiliary instrument used for rapidly locking a measurement area, the transfer unit is used for driving the to-be-detected part to be transferred in the detection process and comprises a clamping robot used for adjusting the position of the to-be-detected part and a detection robot used for fixing a vision measuring instrument, the information acquisition unit is used for receiving the standard 3D digital-analog size of the to-be-detected part, and the calibration unit is used for calibrating the to-be-detected part. The calibration unit is used for calibrating the moving tracks of the clamping robot and the detection robot according to the standard 3D digital-analog size, received by the information acquisition unit, of the to-be-detected part, and the data analysis system has the effects that the visual measurement technology and the automobile part detection process are closely combined, and effective connection among a plurality of links is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile parts detection platform, and more specifically, to an automobile parts online detection system and method based on a full-automatic control platform. Background Art

[0002] With the rapid development of the automotive industry, the precision and quality requirements of automotive parts are increasing day by day. Although traditional detection methods, such as contact measuring tools (such as vernier calipers, micrometers, etc.) and two-dimensional image measuring instruments, can meet the detection needs to a certain extent, they often seem to be unable to cope with complex shapes, high-precision requirements and harsh detection environments. These traditional methods not only have low detection efficiency, but may also damage the surface of the tested parts due to physical contact, increasing production costs and quality control difficulties.

[0003] In this context, visual measurement technology, as a non-contact measurement method based on the principle of machine vision, has gradually attracted widespread attention in the industry. By combining computer vision and image processing technology, visual measurement technology can achieve fast and accurate detection of parts. This technology uses a high-precision camera to capture images of parts, inputs the image data into a computer for complex image processing and analysis, and finally extracts the size information of the parts, including key parameters such as length, width, height, and angle.

[0004] However, although visual measurement technology has shown great potential in the field of automotive parts inspection, there are still some problems in the practical application of existing technologies. Specifically, existing technologies often fail to closely integrate visual measurement technology with the automotive parts inspection process, resulting in the overall inspection process being cumbersome, inefficient, and difficult to effectively manage. These problems are mainly reflected in the following aspects:

[0005] First, insufficient process integration: In the traditional automotive parts inspection process, visual measurement technology often exists as an independent link, lacking effective connection with other inspection steps. This not only increases the complexity of the operation, but may also lead to errors in the transmission of inspection data between different links, affecting the accuracy of the final inspection results.

[0006] Secondly, the detection efficiency is limited: due to the failure to deeply integrate visual measurement technology with the detection process, during the actual detection process, the detection personnel need to frequently switch between different devices and software and perform repeated operations. This not only wastes precious time resources, but also reduces the detection efficiency, making it difficult to meet the rapid detection needs of large-scale production lines.

[0007] Furthermore, management becomes more difficult. The cumbersome testing process and lack of a unified management platform make it very difficult to collect, analyze and archive test data. This not only increases management costs, but may also affect product quality traceability and continuous improvement due to data loss or incorrect processing.

[0008] Therefore, in order to solve the above technical problems, the present invention proposes an online detection system and method for automobile parts based on a fully automatic control platform. Summary of the invention

[0009] In view of the deficiencies in the prior art, the object of the present invention is to provide an online detection system and method for automobile parts based on a fully automatic control platform.

[0010] To achieve the above-mentioned purpose, the present invention provides the following technical solution: an online detection system and method for automobile parts based on a fully automatic control platform, comprising:

[0011] A measuring unit, which includes a visual measuring sensor, a searchlight, and a laser point visual aid for quickly locking the measuring area;

[0012] A circulation unit, which is used to drive the transportation of the parts to be tested during the testing process. The circulation unit includes a clamping robot for adjusting the position of the parts to be tested and a detection robot for fixing the visual measuring instrument;

[0013] An information acquisition unit, which is used to receive the standard 3D digital model dimensions of the component to be tested;

[0014] A calibration unit, which is used to calibrate the running tracks of the gripping robot and the detection robot according to the standard 3D digital model size of the component to be tested received by the information acquisition unit;

[0015] This running trajectory is set in advance according to the size and type of parts, and the entire measurement process and measurement parameters can be adjusted and recorded, and learning can be performed to adjust and optimize the trajectory;

[0016] The data analysis system is used to connect with each unit and process, analyze, compare and evaluate the large amount of data obtained during the measurement process, and generate measurement reports and error analysis reports.

[0017] Furthermore, the circulation unit also includes a transmission belt A, a transmission belt B, a transmission belt C and a transfer robot, wherein the transmission belt A is set up corresponding to the position of the clamping robot, and a pickup point for the clamping robot is provided on the transmission belt A, and the transmission belt B and the transmission belt C are both used to transport the inspected parts, and the transfer robot is set up corresponding to the positions of the transmission belts B and the transmission belts C, and a defective product box for storing faulty products is also provided next to the transfer robot.

[0018] Furthermore, the calibration unit can also adjust the safe measurement distance and detection speed between the detection robot and the clamping robot according to the standard 3D digital model size of the component to be tested.

[0019] Furthermore, the online detection method for automobile parts based on the fully automatic control platform also includes the following steps:

[0020] S1: Receive the standard 3D digital model dimensions of the parts to be tested and import them into the data analysis system;

[0021] S2: The clamping robot clamps the parts to be tested and adjusts the running trajectory of the parts to be tested according to the standard 3D digital model size, as well as the safe measurement distance and detection speed between the parts and the visual measurement sensor;

[0022] S3: The visual measurement sensor performs multi-angle visual imaging 3D measurement on the parts to be measured, and obtains the 3D point cloud data of the parts to be measured;

[0023] S4: Repeat the measurement steps in step S3 multiple times, and calculate the average of the multiple three-dimensional point cloud data measurements;

[0024] S4: Compare the average value of multiple 3D point cloud data measurements with the standard 3D digital model size originally received to determine the error value;

[0025] S5: If the error value exceeds the set range, the component is a defective product, and the transfer robot is controlled to discard the component into the defective product box; if the error value is within the set range, the component is a qualified product, and the transfer robot is controlled to place the component on the transmission belt B and the transmission belt C;

[0026] S6: In step S5, the data completed by the inspection is synthesized and converted through the AQDEF platform to generate the inspection report of the component and upload it to the system for recording;

[0027] S7: In step S6, qualified and unqualified parts are classified and filed. Qualified parts will generate a qualified report for easy traceability, and unqualified parts will be summarized to facilitate observation and improvement by staff.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. In the present invention, the data analysis system integrates the measurement unit, the circulation unit, the information acquisition unit, and the calibration unit, and performs automatic management of the whole process of grabbing, conveying, size detection, and sorting of the parts to be measured, realizing the close combination of visual measurement technology and the automobile parts detection process, and completing the effective connection between multiple links, thereby solving the problem in the prior art that the overall detection process of automobile parts using visual measurement technology is cumbersome and inefficient, which is not only difficult to effectively manage, but also affects the detection efficiency.

[0030] 2. In the present invention, the angle, position, and preset trajectory between the component to be measured and the visual measurement sensor are adjusted according to the standard 3D digital model size of the component to be measured, which is convenient for adjustment for different components, improves the accuracy and reliability of measurement, and avoids the problem of reduced detection efficiency caused by manual adjustment. DETAILED DESCRIPTION

[0031] The present invention provides an online detection system and method for automobile parts based on a fully automatic control platform, comprising a measuring unit, which includes a visual measurement sensor, a searchlight, and a laser point visual aid for quickly locking a measurement area;

[0032] A circulation unit, which is used to drive the transportation of the parts to be tested during the testing process. The circulation unit includes a clamping robot for adjusting the position of the parts to be tested and a detection robot for fixing the visual measuring instrument;

[0033] An information acquisition unit, which is used to receive the standard 3D digital model dimensions of the component to be tested;

[0034] A calibration unit, which is used to calibrate the running tracks of the gripping robot and the detection robot according to the standard 3D digital model size of the component to be tested received by the information acquisition unit;

[0035] Among them, this running trajectory is set in advance according to the size and type of parts. The calibration unit can also adjust and record the entire measurement process and measurement parameters, and can learn and adjust the optimization trajectory;

[0036] Data analysis system, which is used to connect with each unit and process, analyze, compare and evaluate the large amount of data obtained during the measurement process, and generate measurement reports and error analysis reports;

[0037] In summary, compared with the existing visual measurement technology in the overall inspection process of automobile parts, which is not perfect and has low circulation efficiency, in the present invention, the data analysis system integrates the measurement unit, the circulation unit, the information acquisition unit, and the calibration unit, and performs automatic management of the whole process of grabbing, conveying, size detection, and sorting of the parts to be measured. It can also generate analysis reports, which is convenient for observing and improving the overall process, and realizes the close integration of visual measurement technology and automobile parts inspection process, and completes the effective connection between multiple links;

[0038] At the same time, according to the obtained standard 3D digital model size of the part to be tested, the clamping robot that clamps the part to be tested and the detection robot with the visual measurement sensor fixed can also be adjusted. For example, when testing one surface of a part to be tested, one surface of the part to be tested can be divided into multiple areas according to the specific size of the part to be tested and the specifications of the visual measurement sensor, and the distance angle between the part to be tested and the visual measurement sensor can be adjusted according to the running trajectory of the clamping robot set in advance;

[0039] Among them, by adjusting the distance, you can perform fine measurement on the points that need to be measured for different parts. It should be noted that the area divided for each part is different, and the size of the divided area is not necessarily the same. It needs to be judged according to the specific part type;

[0040] Among them, the three-dimensional structure of the parts can be detected by adjusting the angle. For example, when observing the concave part on the surface of the part on a plane, only the surface size, length, width or diameter and other planar data of the concave part can be detected, and it is difficult to detect the depth of the concave part. By tilting the part to be tested and the visual measurement sensor, the depth of the concave part can be observed. In particular, by detecting from multiple angles, the depth of the concave part at different positions can be detected. This is of great significance for some parts with high precision requirements, and it can also avoid observing the depth of only one side, resulting in omission of the observation of the entire part.

[0041] The visual measurement sensor performs multi-angle inspection on multiple areas and sends the inspection results to the data analysis system. The data analysis system can puzzle multiple areas according to the preset track. After each surface of the parts is inspected and sent to the data analysis system, the data analysis system can simulate and form a complete three-dimensional point cloud data.

[0042] Usually, when inspecting parts with high precision requirements, it is necessary to perform repeated measurements many times, and compare the average of multiple measurements with the standard 3D digital model dimensions to reduce the possibility of errors.

[0043] It should be noted that the visual measurement sensor used is a 1-inch 12.8×9.6-mm visual measurement sensor manufactured by The Image Source, with the following specific parameters: optical camera tube diameter 25.400 mm, diagonal 16.000 mm, width 12.800 mm, height 9.600 mm, conversion coefficient 2.704;

[0044] Among them, the circulation unit also includes transmission belt A, transmission belt B, transmission belt C and a transfer robot, among which, transmission belt A is set up corresponding to the position of the clamping robot, and a pickup point of the clamping robot is set on transmission belt A, transmission belt B and transmission belt C are both used to transport the parts that have been inspected, the transfer robot is set up corresponding to the positions of transmission belt B and transmission belt C, and a defective product frame for storing faulty products is also set next to the transfer robot, transmission belt A and transmission belt B are used to distinguish different types of parts, the transfer robot places qualified parts on transmission belt A or transmission belt B as required, and for parts that fail the inspection, the transfer robot will place them in the defective product frame, which is convenient for subsequent staff to recycle, and at the same time, a mark is set in the defective product frame, and there is a corresponding mark on the inspection report of the parts placed in the defective product frame, which is convenient for staff to distinguish;

[0045] It should be noted that the calibration unit can also adjust the safe measurement distance and detection speed between the detection robot and the clamping robot according to the standard 3D digital model size of the parts to be tested, and adjust according to different types of parts. For some areas that do not have complex structures after the parts are separated, such as the plane area, which is a whole plane without special structures, the detection speed can be accelerated for such areas, and for some areas with fine structures, the detection speed can be slowed down for fine detection;

[0046] The online detection method for automobile parts based on the fully automatic control platform also includes the following steps:

[0047] S1: Receive the standard 3D digital model dimensions of the parts to be tested and import them into the data analysis system;

[0048] S2: The clamping robot clamps the parts to be tested and adjusts the running trajectory of the parts to be tested according to the standard 3D digital model size, as well as the safe measurement distance and detection speed between the parts and the visual measurement sensor;

[0049] S3: The visual measurement sensor performs multi-angle visual imaging 3D measurement on the parts to be measured, and obtains the 3D point cloud data of the parts to be measured. The specific operation is to magnify the parts and then transmit the magnified image to the computer through the CCD system, and then generate a complete engineering drawing through the computer software PC-DMIS. The software automatically completes edge extraction, focusing, matching, measurement synthesis, and image synthesis through focusing, point selection, function switching, manual correction, and lighting matching;

[0050] S4: Repeat the measurement steps in step S3 multiple times, and calculate the average of the multiple three-dimensional point cloud data measurements;

[0051] Among them, for parts with higher precision requirements, six repeated tests are generally adopted by default, and the average value is taken through six measurements to reduce the randomness of the test results;

[0052] S4: Compare the average of multiple 3D point cloud data measurements with the standard 3D digital model dimensions originally received, determine the error value, and compare it with the standard 3D digital model dimensions for component production, so as to more intuitively determine the accuracy of the component;

[0053] S5: If the error value exceeds the set range, the component is a defective product, and the transfer robot is controlled to discard the component into the defective product box; if the error value is within the set range, the component is a qualified product, and the transfer robot is controlled to place the component on the transmission belt B and the transmission belt C;

[0054] According to the relevant fixation and product safety performance considerations, the measurement error of the length, width, height and angle of the parts needs to be less than ±0.03mm, which can meet the accuracy requirements of automotive parts size detection;

[0055] S6: In step S5, the data completed by the inspection is synthesized and converted through the AQDEF platform to generate the inspection report of the component and upload it to the system for recording;

[0056] S7: In step S6, qualified and unqualified parts are classified and filed. Qualified parts will generate qualified reports for easy traceability. Unqualified parts will be summarized to facilitate observation and improvement by staff. At the same time, manual sampling will be carried out on the parts that have been inspected.

[0057] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any ordinary technician in the industry can smoothly implement the present invention as described above. However, any equivalent changes, modifications and evolutions made by technicians familiar with the profession without departing from the scope of the technical solution of the present invention using the technical content disclosed above are all equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications and evolutions made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. An online detection system for automobile parts based on a fully automatic control platform, characterized in that: include: A measuring unit, which includes a visual measuring sensor, a searchlight, and a laser point visual aid for quickly locking the measuring area; A circulation unit, which is used to drive the transportation of the parts to be tested during the testing process. The circulation unit includes a clamping robot for adjusting the position of the parts to be tested and a detection robot for fixing the visual measuring instrument; An information acquisition unit, which is used to receive the standard 3D digital model dimensions of the component to be tested; A calibration unit, which is used to calibrate the running tracks of the gripping robot and the detection robot according to the standard 3D digital model size of the component to be tested received by the information acquisition unit; The data analysis system is used to connect with each unit and process, analyze, compare and evaluate the large amount of data obtained during the measurement process, and generate measurement reports and error analysis reports.

2. The online detection system for automobile parts based on a fully automatic control platform according to claim 1 is characterized in that: The circulation unit also includes a transmission belt A, a transmission belt B, a transmission belt C and a transfer robot, wherein the transmission belt A is set up corresponding to the position of the clamping robot, and a pickup point for the clamping robot is set on the transmission belt A, and the transmission belt B and the transmission belt C are both used to transport the inspected parts, and the transfer robot is set up corresponding to the positions of the transmission belts B and C, and a defective product frame for storing faulty products is also set next to the transfer robot.

3. The online detection system for automobile parts based on a fully automatic control platform according to claim 2 is characterized in that: The calibration unit can also adjust the safe measurement distance and detection speed between the detection robot and the clamping robot according to the standard 3D digital model size of the component to be tested.

4. The online detection system for automobile parts based on a fully automatic control platform according to any one of claims 1 to 3, characterized in that: The following detection methods are also included: S1: Receive the standard 3D digital model dimensions of the parts to be tested and import them into the data analysis system; S2: The clamping robot clamps the parts to be tested and adjusts the running trajectory of the parts to be tested according to the standard 3D digital model size, as well as the safe measurement distance and detection speed between the parts and the visual measurement sensor; S3: The visual measurement sensor performs multi-angle visual imaging 3D measurement on the parts to be measured, and obtains the 3D point cloud data of the parts to be measured; S4: Repeat the measurement steps in step S3 multiple times, and calculate the average of the multiple three-dimensional point cloud data measurements; S4: Compare the average value of multiple 3D point cloud data measurements with the standard 3D digital model size originally received to determine the error value; S5: If the error value exceeds the set range, the component is a defective product, and the transfer robot is controlled to discard the component into the defective product box; if the error value is within the set range, the component is a qualified product, and the transfer robot is controlled to place the component on the transmission belt B and the transmission belt C; S6: In step S5, the data completed by the inspection is synthesized and converted through the AQDEF platform to generate the inspection report of the component and upload it to the system for recording; S7: In step S6, qualified and unqualified parts are classified and filed. Qualified parts will generate a qualified report for easy traceability, and unqualified parts will be summarized.