Automatic component detection device based on annular conveying circulation loop and application method
By combining a circular conveyor loop with dynamic visual recognition and robotic arm grasping, an automatic component inspection device has been developed, solving the problems of low efficiency and high false detection rate of existing equipment in the detection of multiple batches and small quantities, and achieving efficient and accurate component inspection.
Patent Information
- Application Number
- CN202510976995.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-15
- Publication Date
- 2026-03-03
AI Technical Summary
Existing component testing equipment suffers from problems such as low identification efficiency, high false detection rate, inability to adapt to high-speed conveyor lines, and inability to achieve high-efficiency testing of components with many batches and small batches when faced with testing tasks with many batches and small batches. In addition, it has poor compatibility and is difficult to meet the testing needs of multiple batches and small batches of components.
An automatic component inspection device based on a circular conveying loop is adopted, which combines a dynamic vision recognition module, a robotic arm dynamic grasping module, and a testing module. It utilizes deep learning target detection algorithms and dynamic path planning algorithms to achieve efficient identification and testing of components.
It improves detection efficiency, reduces false detection rate, enhances automation level, and enables high-precision detection of different types of devices, making it suitable for detection scenarios with many batches and small quantities.
Smart Images
Figure CN121589048A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automated testing technology for electronic components, specifically to an automated testing device and application method for electronic components based on a circular conveying loop. Background Technology
[0002] Most domestic electronic component testing and inspection institutions face the challenge of handling numerous batches of small quantities. When developing or purchasing automated component testing equipment, they can only meet the needs of automated testing and sorting of large quantities of components. Other components, which are more varied but smaller in quantity, still require manual testing, consuming significant manpower. Furthermore, traditional electronic component testing methods often employ static image recognition, which suffers from poor compatibility, high false positive rates, and inability to adapt to high-speed conveyor lines. Simultaneously, most existing automated testing equipment uses linear conveyor systems, making it difficult to achieve automatic connections between different processes and automatic transfer of components under test.
[0003] To address the aforementioned issues, existing technology provides an intelligent multi-dimensional visual inspection device for small electronic components, including a feeding device, a discharging device, a picking device, a feeding conveyor, and a visual inspection device. This device is used to automatically inspect small electronic components, thereby reducing the probability of false detections and missed detections and improving inspection reliability.
[0004] However, this equipment has limitations in its application scope and compatibility. It is suitable for the automatic inspection of large batches of components but cannot meet the testing needs of multiple batches and small quantities. Therefore, developing a high-efficiency inspection device suitable for components with many batches and small quantities is a problem that needs to be solved. Summary of the Invention
[0005] This application provides an automatic component detection device and application method based on a circular conveyor loop, which solves the problems of low identification efficiency, high false detection rate, inability to adapt to high-speed conveyor lines, and inability to achieve high-efficiency detection of components with many batches and small quantities in traditional component detection.
[0006] To achieve the above objectives, this application adopts the following technical solution:
[0007] In a first aspect, this application provides an automatic component testing device based on a circular conveying loop. The device includes: a workbench, with a circular conveying loop module, a dynamic vision recognition module, a robotic arm dynamic grasping module, and a testing module arranged above the workbench, and a control module arranged below the workbench. The dynamic vision recognition module and the robotic arm dynamic grasping module are placed in the middle area above the workbench, the circular conveying loop module and the testing module are respectively located on both sides above the workbench, and the four-axis robotic arm of the robotic arm dynamic grasping module covers the entire area of the circular conveying loop module and the testing module.
[0008] A circular conveyor loop module is used to carry and transport the component under test (SUT).
[0009] The dynamic visual recognition module is used to identify the components under test and to locate the components under test using a deep learning object detection algorithm, thereby determining the coordinate information of the components under test.
[0010] The robotic arm dynamic grasping module is used to calculate the optimal grasping path based on coordinate information using a dynamic path planning algorithm, and to use a four-axis robotic arm to grasp the component under test and place it in the test module.
[0011] The test module is used to test the electrical parameters of the component under test;
[0012] The control module is connected to the circular conveyor loop module, the dynamic vision recognition module, the robotic arm dynamic grasping module, and the testing module to perform integrated control of the device.
[0013] One possible design, the first aspect of the device further includes, the annular conveying loop module including a standard tray, a barcode scanner, an encoder, a tray carrier and a guide rail, the standard tray being mounted on the tray carrier, the tray carrier being mounted on the guide rail, and the barcode scanner and encoder being mounted on the side of the guide rail;
[0014] Standard trays are used to hold components under test.
[0015] A barcode scanner is used to scan the barcode on a standard material tray, thus binding the material tray barcode to the information of the component under test.
[0016] Encoders are used to monitor the speed and position of a standard tray in real time.
[0017] A tray carrier is used to carry a standard tray, allowing the standard tray to move at a certain speed.
[0018] Guide rails are used to form a circular conveying loop, allowing the tray carrier to move on the circular conveying loop.
[0019] One possible design, the device of the first aspect further includes a dynamic visual recognition module, used to identify the component under test and to locate the component under test using a deep learning object detection algorithm, determining the coordinate information of the component under test, including:
[0020] The dynamic visual recognition module includes a following vision module, which is used to capture multiple frames of images of the component under test, identify the component under test based on the multiple frames of images, and locate the component under test using a deep learning object detection algorithm based on the multiple frames of images to determine the coordinate information of the component under test.
[0021] One possible design, the first aspect of the device further includes, the dynamic visual recognition module further includes a polar vision module and a bar light source, the bar light source is close to the annular conveying circulation loop module, and the polar vision module is positioned above the bar light source;
[0022] The polarity vision module is used to perform polarity detection and secondary positioning on the component under test placed in the test module, and to determine the polarity information and orientation information of the component under test.
[0023] A bar light source is used to illuminate the component under test.
[0024] One possible design scheme, the first aspect of the device also includes a polar vision module, which is also used to identify abnormal postures of the component under test placed on the test module. If the component under test has an abnormal posture, an alarm message will be generated for the control module. The abnormal posture is a posture that deviates significantly from the position, angle and direction when it is normally placed for detection.
[0025] One possible design, the first aspect of the device further includes a test module comprising a flipping mechanism, a test fixture, a test instrument and a partitioned tray, wherein the flipping mechanism is disposed on one side of the test fixture, the partitioned tray is disposed on the other side of the test fixture, and the test instrument is connected to the test fixture;
[0026] A flipping mechanism is used to flip the component under test from the reverse side based on the front and back information;
[0027] Test fixtures are used to correctly place the components under test (DUTs) based on polarity information.
[0028] Testing instruments are used to test the relevant parameters of the components under test and store the parameter data;
[0029] The partitioned tray is used to sort and place qualified and unqualified test components based on parameter data.
[0030] One possible design, the first aspect of the device further includes a flipping mechanism comprising a positioning seat, a Y-axis drive arm, an X-axis drive arm, a vacuum nozzle, and a rotating arm, wherein the Y-axis drive arm and the X-axis drive arm are disposed above the positioning seat, the vacuum nozzle is disposed to the side of the positioning seat, and the rotating arm is disposed above the side of the vacuum nozzle.
[0031] The positioning base is used to reposition the component under test placed on the test fixture;
[0032] The Y-axis drive arm is used to correct the Y-axis pose of the component under test based on repositioning, so that the vacuum nozzle can pick up the component under test with the reverse side facing up.
[0033] The X-axis drive arm is used to correct the X-direction pose of the component under test based on repositioning, so that the vacuum nozzle can pick up the component under test with the reverse side facing up.
[0034] Vacuum nozzles are used to pick up components that are facing upwards;
[0035] The rotating arm is used to flip the component under test that is attached to the vacuum nozzle.
[0036] One possible design scheme, the device of the first aspect, also includes a control module including a flow control server, an algorithm server, and a robotic arm controller;
[0037] The flow control server is used to coordinate the control of the circular conveyor loop module, the dynamic vision recognition module, the robotic arm dynamic grasping module, and the testing module.
[0038] Algorithm server, used to execute deep learning object detection algorithms and dynamic path planning algorithms;
[0039] The robotic arm controller is used in the robotic arm dynamic grasping module to grasp the components to be tested.
[0040] Secondly, an application method for an automatic component testing device based on a circular conveying loop includes the following steps:
[0041] Step 1: The component under test is conveyed to the area that the dynamic vision recognition module can recognize through the circular conveyor loop module;
[0042] Step 2: The dynamic visual recognition module identifies the component under test and uses a deep learning target detection algorithm to locate the component under test and determine its coordinate information.
[0043] Step 3: Based on the coordinate information, the robotic arm dynamic grasping module uses a dynamic path planning algorithm to calculate the optimal grasping path and uses a four-axis robotic arm to grasp the component under test and place it in the test module.
[0044] Step four: The dynamic visual recognition module performs polarity detection and secondary positioning on the component under test on the test module to determine the polarity and orientation information of the component under test.
[0045] Step 5: Based on polarity and positive / negative information, the test module tests the component under test;
[0046] The modules in steps one through five are integrated and controlled by the control module.
[0047] One possible design approach, the second aspect of which also includes testing the component under test based on polarity and positive / negative information, including:
[0048] Based on the positive and negative information, the flipping mechanism in the test module flips the component under test that is facing up;
[0049] Based on polarity information, the component under test is correctly placed in the test fixture;
[0050] The testing instruments in the testing module test the relevant parameters of the component under test that is correctly placed in the testing fixture, and store the parameter data;
[0051] Based on the parameter data, the partitioned trays in the test module sort and place qualified and unqualified test components.
[0052] In this embodiment, the automatic component testing device based on a circular conveyor loop effectively connects various processes of component testing through a circular conveyor loop module, a dynamic vision recognition module, a robotic arm dynamic grasping module, a testing module, and a control module. The device has a compact layout and occupies little space, allowing testers to simply pour the components into a standard tray, and the equipment will automatically perform subsequent operations. This device is suitable for component testing scenarios with many batches and small quantities, and can perform dynamic testing on small batches of components of different models.
[0053] Compared with existing equipment, it has the following advantages: (1) Improved compatibility: Multiple test stations can be arranged in the same equipment at the same time to meet the simultaneous testing of different types of devices; (2) Improved detection efficiency: Through the collaborative work of dynamic vision recognition system and robotic arm dynamic grasping system, high-speed and high-precision detection of components is realized; (3) Reduced false detection rate: The deep learning target detection algorithm is adopted to improve the accuracy and stability of component identification; (4) Enhanced automation level: Through the design of the ring conveyor loop, the automatic connection between each process and the automatic transmission of the device under test are realized, which improves the overall automation level.
[0054] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description
[0055] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0056] Figure 1 A schematic diagram of the structure of an automatic component testing device based on a circular conveying loop provided in an embodiment of this application;
[0057] Figure 2This is a schematic diagram of the structure of the annular conveying loop module provided in the embodiments of this application;
[0058] Figure 3 This is a schematic diagram of the structure of the dynamic visual recognition module provided in the embodiments of this application;
[0059] Figure 4 This is a schematic diagram of the structure of the robotic arm dynamic grasping module provided in the embodiments of this application;
[0060] Figure 5 This is a schematic diagram of the structure of the test module provided in an embodiment of this application;
[0061] Figure 6 This is a schematic diagram of the structure of the control module provided in an embodiment of this application;
[0062] Figure 7 This is a schematic diagram of the structure of the flipping mechanism provided in the embodiments of this application;
[0063] Figure 8 A flowchart of the deep learning object detection algorithm provided in the embodiments of this application;
[0064] Figure 9 A flowchart of the dynamic path planning algorithm provided in the embodiments of this application;
[0065] Figure 10 A flowchart illustrating the application method of the automatic component testing device based on a circular conveying loop provided in this application embodiment;
[0066] Explanation of reference numerals in the attached diagram: 1-Circular conveyor loop module, 2-Dynamic vision recognition module, 3-Dynamic gripping module of robotic arm, 4-Testing module, 5-Control module, 11-Standard tray, 12-Barcode scanner, 13-Encoder, 14-Pattern carrier, 15-Guide rail, 21-Following vision module, 22-Polar vision module, 23-Bar light source, 31-Four-axis robotic arm, 41-Tilting mechanism, 42-Test fixture, 43-Test instrument, 44-Divided tray, 51-Flow control server, 52-Algorithm server, 53-Robot controller, 411-Positioning seat, 412-Y-axis drive arm, 413-X-axis drive arm, 414-Vacuum nozzle, 415-Rotating arm. Detailed Implementation
[0067] To make the objectives, technical solutions, and advantages of the embodiments in this specification clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. The components of the embodiments of this specification described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.
[0068] Therefore, the following detailed description of the embodiments of this specification provided in the accompanying drawings is not intended to limit the scope of the claimed specification, but merely to illustrate selected embodiments of this specification. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without inventive effort are within the scope of protection of this specification.
[0069] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
[0070] In the description of the embodiments in this specification, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings, or the orientation or positional relationships commonly used when the product is in use. These are merely for the convenience of describing this specification and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this specification. Furthermore, the terms "first," "second," and "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0071] Furthermore, the use of terms such as "horizontal," "vertical," and "sag" does not imply that the component must be absolutely horizontal or suspended, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.
[0072] In the description of the embodiments in this specification, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this specification according to the specific circumstances.
[0073] The following section will describe in detail the automatic component inspection device based on a circular conveying loop of this application, which aims to achieve high-efficiency inspection of components with many batches and small quantities.
[0074] Figure 1 This is a schematic diagram of the structure of an automatic component testing device based on a circular conveying loop provided in an embodiment of this application. Figure 1As shown, the automatic component testing device based on a circular conveying loop includes: a workbench, with a circular conveying loop module 1, a dynamic vision recognition module 2, a robotic arm dynamic gripping module 3, and a testing module 4 arranged above the workbench, and a control module 5 arranged below the workbench. The dynamic vision recognition module 2 and the robotic arm dynamic gripping module 3 are placed in the middle area above the workbench, the circular conveying loop module 1 and the testing module 4 are respectively located on both sides above the workbench, and the four-axis robotic arm of the robotic arm dynamic gripping module 3 covers the entire area of the circular conveying loop module 1 and the testing module 4.
[0075] The circular conveyor loop module 1 is used to carry and transport the component under test (SUT).
[0076] The dynamic visual recognition module 2 is used to identify the component under test and to locate the component under test using a deep learning target detection algorithm to determine the coordinate information of the component under test.
[0077] The robotic arm dynamic grasping module 3 is used to calculate the optimal grasping path based on coordinate information using a dynamic path planning algorithm, and to use a four-axis robotic arm 31 to grasp the component under test and place it in the test module 4.
[0078] Test module 4 is used to test the electrical parameters of the component under test;
[0079] The control module 5 is connected to the circular conveyor loop module 1, the dynamic vision recognition module 2, the robotic arm dynamic grasping module 3, and the testing module 4 to perform integrated control of the device.
[0080] like Figure 2 As shown, the above-mentioned circular conveying loop module 1 includes a standard tray 11, a barcode scanner 12, an encoder 13, a tray carrier 14, and a guide rail 15. The standard tray 11 is mounted on the tray carrier 14, the tray carrier 14 is mounted on the guide rail 15, and the barcode scanner 12 and the encoder 13 are mounted on the side of the guide rail 15.
[0081] Standard tray 11 is used to hold the component under test;
[0082] The barcode scanner 12 is used to scan the barcode on the standard tray 11, so that the tray barcode is bound to the information of the component under test;
[0083] Encoder 13 is used to monitor the movement speed and position of the standard tray 11 in real time;
[0084] The tray carrier 14 is used to carry the standard tray 11, so that the standard tray 11 moves at a certain speed;
[0085] The guide rail 15 is used to form a circular conveying circuit, so that the tray carrier 14 moves on the circular conveying circuit.
[0086] In addition, it should be noted that one side of the guide rail 15 is the loading area and the other side is the testing area. The components under test can be placed in the loading area in a cyclical manner, and the subsequent testing of the components under test can be carried out in the testing area. For specific testing methods, please refer to the following description, and no specific restrictions are made here.
[0087] like Figure 3 As shown, the dynamic visual recognition module 2 includes a following vision module 21, which is used to capture multiple frames of images of the component under test, identify the component under test based on the multiple frames of images, and locate the component under test using a deep learning object detection algorithm based on the multiple frames of images to determine the coordinate information of the component under test.
[0088] It should be noted that the above deep learning object detection algorithms can be used as a reference. Figure 8 I understand, so I won't go into details here.
[0089] In addition, the aforementioned follow vision module 21 includes a camera that captures multiple frames of images of the component under test.
[0090] In addition, the aforementioned polar vision module 22 is also used to identify abnormal postures of the components under test placed in the test module 4. If the components under test have abnormal postures, an alarm message will be generated for the control module 5. The abnormal posture is a posture that deviates significantly from the position, angle, and direction when the components are placed normally for testing.
[0091] It should also be noted that the aforementioned dynamic visual recognition module 2 further includes a polarity vision module 22 and a bar light source 23. The bar light source 23 is located near the annular conveying loop module 1, and the polarity vision module 22 is positioned above the bar light source 23. Specifically, the polarity vision module 22 is used to perform polarity detection and secondary positioning on the component under test placed in the test module 4, determining the polarity and orientation information of the component under test; the bar light source 23 is used to illuminate the component under test.
[0092] like Figure 4 As shown, the robotic arm dynamic grasping module 3 is used to calculate the optimal grasping path based on coordinate information using a dynamic path planning algorithm, and uses a four-axis robotic arm 31 to grasp the component under test and place it in the test module 4.
[0093] It should be noted that the dynamic path planning algorithm described above predicts the motion trajectory of the device under test and feeds the coordinates back to the four-axis robotic arm 31. The specific flow of the dynamic path planning algorithm is as follows: Figure 9As shown, the motion trajectory of the component under test is fitted based on the target detection results to establish a spatiotemporal motion model of the component. Several time points in the future motion trajectory of the component under test are selected, and the speed at which the robot reaches those points is calculated in reverse. The following fixed point and following speed are updated in the global environment. To ensure the consistency of the following time, the input motion trajectory of the component under test must include not only spatial coordinates X, Y, and U, but also a selected time node t. The spatial coordinates of the component under test are output by the target detection algorithm, and the time node is the timestamp of the image frame acquisition. The trajectory of the component under test obtained from the image is fitted and calculated to obtain the spatiotemporal motion model of the component under test, which is then used to grasp the component under test.
[0094] like Figure 5 As shown, the test module 4 includes a flipping mechanism 41, a test fixture 42, a test instrument 43, and a partitioned tray 44. The flipping mechanism 41 is located on one side of the test fixture 42, and the partitioned tray 44 is located on the other side of the test fixture 42. The test instrument 43 is connected to the test fixture 42.
[0095] The flipping mechanism 41 is used to flip the component under test with the reverse side facing up based on the front and back information;
[0096] Test fixture 42 is used to correctly place the component under test in the test fixture 42 based on polarity information;
[0097] Test instrument 43 is used to test the relevant parameters of the component under test and store the parameter data;
[0098] The partitioned tray 44 is used to sort and place qualified and unqualified test components based on parameter data.
[0099] It should be noted that the flipping mechanism 41 needs to flip the component under test with the reverse side facing up based on the front and back information fed back by the polarity vision module 22; then, based on the polarity information, the component under test is correctly placed on the test fixture 42 and then the test is performed, and the partitioning action is executed. In addition, for the component under test that is placed face up, there is no need to flip it; it is only necessary to ensure that it is correctly placed on the test fixture 42.
[0100] Among them, such as Figure 7 As shown, the flipping mechanism 41 includes a positioning base 411, a Y-axis drive arm 412, an X-axis drive arm 413, a vacuum nozzle 414, and a rotating arm 415. The Y-axis drive arm 412 and the X-axis drive arm 413 are positioned above the positioning base 411, the vacuum nozzle 414 is positioned to the side of the positioning base 411, and the rotating arm 415 is positioned above the side of the vacuum nozzle 414.
[0101] Positioning seat 411 is used to reposition the component under test placed on the test fixture 42;
[0102] Y-axis drive arm 412 is used to correct the Y-direction pose of the component under test based on repositioning, so that the vacuum nozzle 414 can adsorb the component under test with the reverse side facing up.
[0103] X-axis drive arm 413 is used to correct the X-direction pose of the component under test based on repositioning, so that the vacuum nozzle 414 can adsorb the component under test with the reverse side facing up.
[0104] Vacuum nozzle 414 is used to pick up components under test with their reverse side facing up.
[0105] The rotating arm 415 is used to flip the component under test that is adsorbed on the vacuum nozzle 414.
[0106] like Figure 6 As shown, the control module 5 includes a flow control server 51, an algorithm server 52, and a robotic arm controller;
[0107] The flow control server 51 is used to coordinate the control of the circular conveyor loop module 1, the dynamic vision recognition module 2, the robotic arm dynamic grasping module 3, and the testing module 4.
[0108] Algorithm server 52 is used to execute deep learning object detection algorithms and dynamic path planning algorithms;
[0109] The robotic arm controller 53 is used for the robotic arm in the dynamic gripping module 3 to grip the component to be tested, and can also be used for gripping the rotating arm 415 in the flipping mechanism 41.
[0110] Furthermore, the aforementioned flow control server 51, algorithm server 52, and robotic arm controller can also be integrated into one or two or other numbers of servers, depending on the actual situation. The deployment of the flow control server 51, algorithm server 52, and robotic arm controller on separate servers in this application is merely an example and no specific restrictions are imposed here.
[0111] In summary, this automatic component inspection device based on a circular conveyor loop effectively connects the various processes of component inspection through a circular conveyor loop module, a dynamic vision recognition module, a robotic arm dynamic grasping module, a testing module, and a control module. Its compact layout and small footprint allow testers to simply pour the components into a standard tray, and the equipment automatically performs subsequent operations. This device is suitable for component inspection scenarios with many batches and small quantities, and can perform dynamic testing on small batches of different models of components.
[0112] The above combination Figures 1-9This application provides a detailed description of the automatic component testing device based on a circular conveying loop provided in the embodiments of this application. The specific application method of this automatic component testing device based on a circular conveying loop is described below.
[0113] like Figure 10 As shown, the application method of this automatic component testing device based on a circular conveying loop includes the following steps:
[0114] Step 1: The component under test is conveyed to the identifiable area of the dynamic vision recognition module 2 through the circular conveyor loop module 1;
[0115] Step 2: The dynamic visual recognition module 2 identifies the component under test and uses a deep learning target detection algorithm to locate the component under test and determine its coordinate information.
[0116] Step 3: Based on the coordinate information, the robotic arm dynamic grasping module 3 uses a dynamic path planning algorithm to calculate the optimal grasping path, and uses the four-axis robotic arm 31 to grasp the component to be tested and place it in the test module 4.
[0117] Step 4: The dynamic visual recognition module 2 performs polarity detection and secondary positioning on the component under test on the test module 4 to determine the polarity and orientation information of the component under test.
[0118] Step 5: Based on polarity and positive / negative information, test module 4 tests the component under test;
[0119] The modules in steps one through five are integrated and controlled by control module 5.
[0120] It should be noted that in step five, based on polarity and positive / negative information, test module 4 tests the component under test, including:
[0121] Based on the positive and negative information, the flipping mechanism 41 in the test module 4 flips the component under test with the reverse side facing up.
[0122] Based on polarity information, the component under test is correctly placed in the test fixture 42;
[0123] The test instrument 43 in test module 4 tests the relevant parameters of the component under test that is correctly placed in test fixture 42, and stores the parameter data;
[0124] Based on the parameter data, the partitioned tray 44 in the test module 4 sorts and places qualified and unqualified test components.
[0125] Furthermore, the specific implementation of the above application method is basically similar to that of the device implementation, so the description is relatively simple. For relevant details, please refer to the description of the device implementation.
[0126] The following describes the application method of the device of this application, taking a solid tantalum electrolytic capacitor as an example. The capacitor to be tested is placed in the standard tray 11 and moves with the circular conveyor belt at a certain speed. The specific implementation process is as follows:
[0127] Step 1: Component loading and information binding
[0128] 500 tantalum capacitors to be tested are randomly placed into a standard tray 11, which then enters the scanning station at a speed of 100 mm / s via a circular conveyor belt. A barcode scanner 12 scans the barcode on the tray at a speed of 200 ms per tray, automatically binding the batch number "TAN-2025-001" with the process parameters (test voltage 16V, capacitance range 22μF±20%) in the MES system.
[0129] Step 2: Dynamic Visual Recognition
[0130] When the tray enters the visual recognition area:
[0131] The vision module 21 captures capacitance images at a frame rate of 1500fps and completes localization within 12ms using an improved YOLOv8 algorithm, outputting coordinate data (X: 325.4mm, Y: 78.2mm, θ: 15°).
[0132] After receiving the command, the four-axis robotic arm 31(31) calculates the optimal grasping path within 80ms based on the dynamic path planning algorithm. The end effector grasps the capacitors in both front and back shapes with a repeatability of ±0.05mm.
[0133] Step 3: Four-axis robotic arm 31 collaboratively grasps and flips.
[0134] The four-axis robotic arm 31 transfers the capacitor to the flipping mechanism 41. The X-axis drive arm 413 and the Y-axis drive arm 412 correct the pose of the device under test. For devices facing upwards, the polarity vision module 22 identifies the capacitor polarity mark, and then the four-axis robotic arm 31 picks it up and places it in the test fixture 42. For devices facing downwards, the rotating arm 415 flips them to face upwards. After the polarity vision module 22 identifies the capacitor polarity mark, the four-axis robotic arm 31 picks the device up from the vacuum nozzle 414 and places it in the test fixture 42.
[0135] Step 4: Capacitance Testing (To be implemented step by step)
[0136] First, the test instrument 43 was triggered to apply a 16V DC voltage to test the leakage current (standard value ≤3.5μA), with measured data of 2.1μA / 2.8μA / 3.2μA; second, the capacitance value (22μF±20%) was measured, with measured data of 20.7μF / 23.5μF / 18.9μF; finally, a withstand voltage test was performed (1.5 times the rated voltage for 5 seconds).
[0137] Test data is uploaded in real time, and the system automatically determines that capacitor #6 (18.9μF) is out of tolerance.
[0138] Step 5: Automated sorting and data closed loop
[0139] Control module 5 sorts and places qualified and unqualified test components according to the test results:
[0140] Qualified products: The robotic arm places the capacitors on the green tray, and they are then manually transferred to the packaging station;
[0141] Non-conforming product: Transfer capacitor #6 to the red tray and trigger the MES system to generate a non-conforming product confirmation form;
[0142] The entire process took 4 minutes and 15 seconds to complete the inspection of 500 pieces, which is 962% more efficient than traditional manual inspection (which takes 45 minutes) and reduced the false detection rate from 1.8% to 0.12%.
[0143] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of this application as described above, which are not provided in the details for the sake of brevity.
[0144] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. An automatic component testing device based on a circular conveying loop, characterized in that, The device includes: a workbench, above which are arranged a ring conveyor circulation loop module, a dynamic vision recognition module, a robotic arm dynamic grasping module, and a testing module; below which is a control module; the dynamic vision recognition module and the robotic arm dynamic grasping module are placed in the middle area above the workbench; the ring conveyor circulation loop module and the testing module are respectively located on both sides above the workbench; the four-axis robotic arm of the robotic arm dynamic grasping module covers the entire area of the ring conveyor circulation loop module and the testing module. The circular conveying loop module is used to carry and transport the component under test. The dynamic visual recognition module is used to identify the component under test and to locate the component under test using a deep learning target detection algorithm to determine the coordinate information of the component under test. The robotic arm dynamic grasping module is used to calculate the optimal grasping path based on the coordinate information using a dynamic path planning algorithm, and to use a four-axis robotic arm to grasp the component under test and place it in the test module. The test module is used to test the electrical parameters of the component under test; The control module is connected to the circular conveying loop module, the dynamic vision recognition module, the robotic arm dynamic grasping module, and the testing module to perform integrated control of the device.
2. The automatic component testing device based on a circular conveying loop according to claim 1, characterized in that, The circular conveying loop module includes a standard tray, a barcode scanner, an encoder, a tray carrier, and a guide rail. The standard tray is mounted on the tray carrier, the tray carrier is mounted on the guide rail, and the barcode scanner and the encoder are mounted on the side of the guide rail. The standard tray is used to hold the component under test; The barcode scanner is used to scan the barcode on the standard tray, so that the tray barcode is bound to the information of the component under test; The encoder is used to monitor the movement speed and position of the standard tray in real time; The tray carrier is used to carry the standard tray, so that the standard tray moves at a certain speed; The guide rail is used to form a circular conveying circuit, so that the tray carrier can move on the circular conveying circuit.
3. The automatic component testing device based on a circular conveying loop according to claim 1, characterized in that, The dynamic visual recognition module is used to identify the component under test and to locate the component under test using a deep learning object detection algorithm, determining the coordinate information of the component under test, including: The dynamic visual recognition module includes a following vision module, which is used to capture multiple frames of images of the component under test, identify the component under test based on the multiple frames of images, and locate the component under test using a deep learning object detection algorithm based on the multiple frames of images to determine the coordinate information of the component under test.
4. The automatic component testing device based on a circular conveying loop according to claim 3, characterized in that, The dynamic visual recognition module also includes a polar vision module and a bar light source. The bar light source is close to the annular conveying circulation loop module, and the polar vision module is positioned above the bar light source. The polarity vision module is used to perform polarity detection and secondary positioning on the component under test placed in the test module, and to determine the polarity information and orientation information of the component under test. The strip light source is used to illuminate the component under test.
5. The automatic component testing device based on a circular conveying loop according to claim 4, characterized in that, The polar vision module is also used to identify abnormal postures of the components under test placed in the test module. If the components under test have abnormal postures, an alarm message will be generated for the control module. The abnormal posture is a posture that deviates significantly from the position, angle, and direction when the components are placed normally for testing.
6. The automatic component testing device based on a circular conveying loop according to claim 4, characterized in that, The testing module includes a flipping mechanism, a testing fixture, a testing instrument, and a partitioned tray. The flipping mechanism is located on one side of the testing fixture, the partitioned tray is located on the other side of the testing fixture, and the testing instrument is connected to the testing fixture. The flipping mechanism is used to flip the component under test with the reverse side facing up based on the positive and negative information. The test fixture is used to correctly place the component under test in the test fixture based on the polarity information; The testing instrument is used to test the relevant parameters of the component under test and store the parameter data. The partitioned tray is used to sort and place qualified and unqualified test components based on the parameter data.
7. The automatic component testing device based on a circular conveying loop according to claim 6, characterized in that, The flipping mechanism includes a positioning base, a Y-axis drive arm, an X-axis drive arm, a vacuum nozzle, and a rotating arm. The Y-axis drive arm and the X-axis drive arm are positioned above the positioning base, the vacuum nozzle is positioned to the side of the positioning base, and the rotating arm is positioned above the side of the vacuum nozzle. The positioning seat is used to reposition the component under test placed on the test fixture; The Y-axis drive arm is used to correct the Y-direction pose of the component under test based on the repositioning, so that the vacuum nozzle adsorbs the component under test with the reverse side facing up. The X-axis drive arm is used to correct the X-direction pose of the component under test based on the repositioning, so that the vacuum nozzle adsorbs the component under test with the reverse side facing up. The vacuum nozzle is used to adsorb the component to be tested with its reverse side facing upwards; The rotating arm is used to flip the component under test that is adsorbed on the vacuum nozzle.
8. The automatic component testing device based on a circular conveying loop according to claim 1, characterized in that, The control module includes a flow control server, an algorithm server, and a robotic arm controller; The flow control server is used to coordinate the control of the circular conveying loop module, the dynamic vision recognition module, the robotic arm dynamic grasping module, and the testing module. The algorithm server is used to execute the deep learning object detection algorithm and the dynamic path planning algorithm; The robotic arm controller is used for the robotic arm in the robotic arm dynamic grasping module to grasp the component under test.
9. An application method for an automatic component testing device based on a circular conveying loop, applied to the automatic component testing device based on a circular conveying loop as described in any one of claims 1-8, characterized in that, The application method includes the following steps: Step 1: The component under test is conveyed to the area that the dynamic vision recognition module can recognize through the circular conveyor loop module; Step 2: The dynamic visual recognition module identifies the component under test and uses a deep learning target detection algorithm to locate the component under test and determine its coordinate information. Step 3: Based on the coordinate information, the robotic arm dynamic grasping module uses a dynamic path planning algorithm to calculate the optimal grasping path, and uses a four-axis robotic arm to grasp the component under test and place it in the test module. Step four: The dynamic visual recognition module performs polarity detection and secondary positioning on the component under test on the test module to determine the polarity information and orientation information of the component under test. Step 5: Based on the polarity information and the positive / negative information, the test module tests the component under test; The modules in steps one through five are integrated and controlled by a control module.
10. The application method of the automatic component testing device based on a circular conveying loop according to claim 9, characterized in that, Based on the polarity information and the positive / negative information, the testing module tests the component under test, including: Based on the positive and negative information, the flipping mechanism in the test module flips the component under test with the reverse side facing up. Based on the polarity information, the component under test is correctly placed in the test fixture; The testing instruments in the testing module test the relevant parameters of the component under test that is correctly placed in the testing fixture, and store the parameter data. Based on the parameter data, the partitioned trays in the test module sort and place qualified and unqualified test components.