Full-automatic fatigue test system and method

Abstract

The invention discloses a full-automatic fatigue testing system and method. The system comprises a fatigue testing machine, an industrial robot, a machine vision unit, an intelligent clamp unit and a central control unit. Samples are recognized and positioned through machine vision, automatic feeding and discharging are carried out through the industrial robot, the samples are automatically locked through the intelligent clamp unit, and the central control unit carries out unified scheduling and associates data. The full-process unmanned operation of the fatigue test from clamping, centering, testing to data management is achieved, the problems that a traditional method is low in efficiency, large in error and high in labor cost are solved, and the method is particularly suitable for large-scale and high-throughput material fatigue performance testing scenes.

Description

Technical Field

[0001] This invention relates to the field of material mechanical property testing technology, specifically to a fully automated fatigue testing system and method. Background Technology

[0002] Fatigue testing is a crucial method for evaluating the durability of materials, components, and structures under cyclic loading, and is widely used in aerospace, automotive, and additive manufacturing fields. Traditional fatigue testing processes heavily rely on manual operation, including specimen identification, clamping and alignment, testing machine parameter settings, process monitoring, and data recording. This approach has several drawbacks: low efficiency: testing a single specimen can take hours or even days, but preparation work such as clamping and alignment still requires manual intervention, resulting in overall low efficiency; high labor costs: long hours of operator monitoring are required, especially during large-scale material screening (such as testing multiple sets of specimens under different additive manufacturing process parameters), leading to enormous labor costs; significant human error: manual clamping makes it difficult to guarantee alignment accuracy each time, and the introduced eccentric loads significantly affect the accuracy and reliability of test results; cumbersome data management: the correspondence between test data and specimen information is prone to errors due to manual recording, leading to difficulties in data traceability.

[0003] Currently, although some testing machines have achieved single-machine automation, how to achieve unmanned operation of the entire process from sample queue management, automatic loading and unloading, intelligent clamping to automatic data association is still a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0004] To achieve the above objectives, the present invention aims to provide a fully automated fatigue testing system, comprising: Fatigue testing machine, used to test the mechanical properties of specimens; Industrial robot units are used to perform sample gripping, handling, and placement operations; The machine vision unit is used to identify the ID information of the sample, position the sample to guide the industrial robot unit, and perform centering checks on the clamped sample. An intelligent clamping unit, installed on the fatigue testing machine, is used to receive and automatically lock the sample placed by the industrial robot unit; The central control unit is connected to the fatigue testing machine, industrial robot unit, machine vision unit and intelligent fixture unit. It is used to manage the sample testing queue, schedule the collaborative work of each unit, and automatically bind and store the test data with the sample ID information.

[0005] Preferably, the industrial robot unit is a six-axis industrial robot, and its end effector is an adaptive gripper with integrated force / torque sensors.

[0006] Preferably, the force / torque sensor is used to monitor the force in real time during the gripping and placement of the sample, and the central control unit adaptively adjusts the robot's actions based on the force data to prevent sample damage or improper placement.

[0007] Preferably, the machine vision unit includes: The first vision subsystem, located in the sample storage area, is used to identify the sample's ID information and determine its initial position coordinates on the sample stage. The second vision subsystem is set in the clamping area of ​​the fatigue testing machine to acquire images after the specimen is clamped, in order to calculate the deviation between the specimen axis and the loading axis of the testing machine and complete the alignment check.

[0008] Preferably, the central control unit is configured to: when the deviation detected by the second vision subsystem exceeds a preset threshold, control the industrial robot unit to re-grab and adjust the sample position, or issue an alignment failure alarm.

[0009] Preferably, the intelligent clamping unit is a pneumatic, hydraulic, or servo motor driven quick-locking mechanism, which has a self-centering V-shaped jaw or an adaptive floating module, and can automatically compensate for minor positional deviations of the sample during the locking process.

[0010] Preferably, the central control unit includes: The queue management module is used to edit, store, and sequentially call task queues containing sample IDs and their corresponding test parameters; The collaborative scheduling module is used to automatically trigger the industrial robot unit to execute the sample replacement process after the fatigue testing machine completes the current test; The data management module is used to automatically create a database and uniquely bind the test data collected from the fatigue testing machine with the sample ID read from the machine vision unit.

[0011] Preferably, the central control unit also integrates a digital twin module, which constructs a virtual model consistent with the physical system for real-time mapping of the physical system's operating status, process simulation prediction, and visual monitoring.

[0012] A fully automated fatigue testing method includes the following steps: S1: The machine vision unit identifies the test sample on the test stage and obtains its ID information and spatial coordinates; S2: The central control unit plans the motion path of the industrial robot unit based on the spatial coordinates and controls it to grasp the target sample; S3: The industrial robot unit transports the sample and places it into the intelligent fixture unit of the fatigue testing machine; S4: The intelligent clamping unit automatically locks the sample; S5: The machine vision unit acquires and processes images of the clamped sample and calculates its centering deviation. S6: If the centering deviation is within the allowable range, the central control unit sends a command to the fatigue testing machine to start the test; if the centering deviation exceeds the limit, an adjustment or alarm procedure is executed. S7: During the test, the central control unit collects test data in real time and binds and stores the data with the sample ID obtained in step S1; S8: After the current test is completed, the central control unit controls the industrial robot unit to remove the tested sample and return to step S1 to grab the next sample, until all samples in the queue have been tested.

[0013] In step S3, the industrial robot unit uses the force sensing function at the end effector to place the sample into the fixture in a compliant control manner, ensuring stable placement posture.

[0014] This invention provides a fully automated fatigue testing system with the following improvements and advantages compared to the prior art: Fully automated process: It realizes full automation from sample identification to report generation, can run 24 hours a day, greatly improves efficiency, and is particularly suitable for large-scale sample testing.

[0015] High precision and high consistency: Machine vision guidance and force sensing control ensure the accuracy of gripping and clamping; intelligent fixtures guarantee the consistency of each clamping, eliminate human error, and improve data reliability.

[0016] Intelligent scheduling and management: The central software enables efficient scheduling and collaborative management of multiple devices and tasks, forming a complete integrated solution of "measurement-management-control".

[0017] Strong data traceability: Automated data binding ensures that each piece of data has a unique sample ID source, which facilitates data traceability and analysis. Attached Figure Description

[0018] Figure 1 This is a three-dimensional schematic diagram of the overall structure of the present invention; Figure 2 This is a top view of the overall structure of the present invention; Figure 3 This is a partial structural schematic diagram of the present invention; Figure 4 This is a three-dimensional structural diagram of the intelligent clamping unit of the present invention; Figure 5 This is a schematic diagram of the three-dimensional structure of the industrial robot unit of the present invention; Figure 6 This is a system framework diagram of the present invention.

[0019] In the diagram: 1. Fatigue testing machine; 2. Industrial robot unit; 201. Gripper; 3. Intelligent fixture unit; 4. First vision subsystem; 401. Storage area; 402. Sample stage; 403. Second vision subsystem; 5. V-jaw; 501. Base; 502. Cylinder; 6. Rotating end; 601. Locking port. Detailed Implementation

[0020] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention 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 the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" 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 invention based on the specific circumstances.

[0024] See Figure 1-6 Example: The fully automated fatigue testing system in this embodiment mainly includes: a fatigue testing machine 1, an industrial robot unit 2, a machine vision unit, an intelligent fixture unit 3, and a central control cabinet. The system is housed within a safety enclosure to ensure human and machine safety.

[0025] Fatigue testing machine 1 (core actuator) Selection and Configuration: This embodiment uses a 100kN servo hydraulic high-frequency fatigue testing machine 1, equipped with the intelligent fixture unit 3 of this invention. The testing machine controller is connected to the central control cabinet via Ethernet, and can receive start and stop commands from the central software, and upload full-cycle test data such as load, number of cycles, and strain in real time.

[0026] Industrial robot unit 2 (performing material handling) Selection and Configuration: Select a six-axis industrial robot with a load capacity greater than 10kg and a working radius of not less than 1.5m (brand optional, such as KUKA, FANUC, etc.). It communicates with the central control cabinet via the Profinet bus.

[0027] End effector: A three-finger adaptive pneumatic gripper 201 (such as the SCHUNK brand) is mounted at the end of the robot's wrist. The gripper 201 has a flexible, non-slip material embedded on its inner side to accommodate cylindrical or plate-shaped samples. Crucially, a six-dimensional force / torque sensor (such as an ATI Industrial Automation product) is integrated into the gripper 201. This sensor can detect the forces and torques acting on the sample in real time during gripping, handling, and placement.

[0028] Machine vision unit (the system's "eyes") Composition and configuration: The machine vision unit of this system consists of two high-resolution industrial cameras and their supporting light source and image processing software.

[0029] The first camera (identification and positioning camera, first vision subsystem 4) is fixedly installed above the sample stage 402. It is equipped with a ring LED light source to clearly illuminate multiple samples on the stage. Each sample has a Data Matrix QR code label. The camera's tasks are: 1) to identify and read the unique ID of each sample; 2) to accurately calculate the X, Y, Z coordinates and rotation angle of the center of each sample through a visual positioning algorithm, and to transform this coordinate system into the coordinate system of the industrial robot unit 2 to guide the industrial robot unit 2 to accurately grasp the sample.

[0030] The second camera (centering detection camera, second vision subsystem 403): fixedly mounted on the frame of the fatigue testing machine 1, with its lens facing the clamping area of ​​the intelligent fixture. It is equipped with a low-angle diffused light source to highlight the outline of the specimen. The camera's task is to capture images of the specimen after the robot places it into the fixture and initially positions it, but before the intelligent fixture unit 3 is fully locked, and to calculate the coaxiality deviation between the specimen axis and the loading axis of the testing machine through image algorithms.

[0031] Intelligent clamping unit 3 (enabling automatic clamping) Structure and working principle: The intelligent clamp in this embodiment is pneumatically driven.

[0032] Fixture body: includes a fixed base 501, which is connected to the actuating cylinder of the testing machine.

[0033] Clamping mechanism: The base 501 contains two symmetrically distributed V-shaped jaws 5. Each V-shaped jaw 5 is connected to the piston rod of a double-acting cylinder 502. The cylinder 502 is controlled by a central control cabinet via a solenoid valve. Among them, such as Figure 3 As shown, it also has two symmetrical rotating ends 6. The rotating ends 6 lock the two ends of the rod-shaped structure respectively through locking ports 601. The bending fatigue test is achieved by rotating the two rotating ends 6, which is a conventional prior art and will not be described in detail here.

[0034] Workflow: Industrial robot unit 2 places the sample between two open V-shaped jaws 5. The central software issues a command, the solenoid valve actuates, and the drive cylinder 502 pushes the two V-shaped jaws 5 to move synchronously towards each other until the sample is clamped and locked. The V-shaped jaw design has self-centering characteristics, which can automatically compensate for minor deviations in robot placement and ensure that the sample is clamped in the centered position.

[0035] Central control unit (the system's "brain") Hardware: The central control cabinet 5 contains an industrial computer (IPC), PLC controller, robot controller, motion control card, and various communication interfaces (Ethernet, Profinet, etc.). The IPC serves as the central command center.

[0036] Software: The IPC runs self-developed central scheduling and management software, whose core modules include: Queue Management Module: Operators can import a CSV file in advance, which contains the IDs of all test samples (corresponding to QR codes) and their respective test parameters (such as load amplitude, stress ratio, frequency, etc.). The software generates a test task queue in sequence.

[0037] The vision processing module calls library functions such as Halcon / OpenCV, the first vision subsystem 4, and the second vision subsystem 403 to realize QR code recognition, positioning, and centering calculation.

[0038] Robot path planning module: Based on the visual positioning results, automatically generate the optimal motion trajectory of industrial robot unit 2 from grabbing the sample in the test area -> moving to fatigue testing machine 1 -> placing the sample -> moving to the completed area, and inject compliant control commands fed back from the force sensor.

[0039] Cooperative scheduling module: This is the core of the control logic. It acts like a "symphony conductor," precisely controlling the timing of each device's actions: Fatigue testing machine 1 completes -> Industrial robot unit 2 removes the old sample -> Industrial robot unit 2 grabs the new sample -> Vision alignment inspection -> Intelligent fixture unit 3 locks -> Fatigue testing machine 1 starts.

[0040] Data Management Module: Automatically creates an SQL database. For each test sample, the software creates a data file named after the sample ID and writes all data streams transmitted in real-time from the fatigue testing machine 1 into this file, achieving seamless data binding. After all tests are completed, a comprehensive report containing all sample data and statistical charts can be generated with a single click.

[0041] Digital Twin Module (Visual Interface): The software interface displays a 3D virtual model that is completely identical to the physical system. The movement of the robot and testing machine in the model is synchronized with the real world, and the current task progress, equipment status, visual recognition results, alignment deviation data, etc. are displayed in real time, achieving transparent monitoring.

[0042] System workflow: Initialization: The operator places a batch of samples on the sample stage 402, imports the task queue into the software, and clicks start.

[0043] Identification and Grasping: The first vision subsystem 4 scans the sample stage 402, identifies the ID of sample number 1 and its coordinates, and sends the information to the central software. The software plans a path and controls the industrial robot unit 2 to move above sample number 1, with force sensors assisting it in grasping the sample in a compliant mode.

[0044] Handling and placement: Industrial robot unit 2 transports sample No. 1 to intelligent clamping unit 2 of fatigue testing machine 1 and gently places it into the open V-shaped jaws 5.

[0045] Alignment check and locking: The second vision subsystem 403 immediately takes a picture of the clamping status, and the software calculates the alignment deviation to be 0.05mm (less than the preset 0.1mm threshold), which is considered acceptable. The central software then triggers the solenoid valve, and the cylinder 502 drives the V-jaw 5 to lock the sample.

[0046] Test execution and data binding: The central software sends a start command to fatigue testing machine 1 and inputs the test parameters for specimen 1. Fatigue testing machine 1 begins operation. Simultaneously, the software creates the file "Specimen 1.csv" and begins recording all input test data.

[0047] Cycle and Replacement: After the test of sample 1 is completed, fatigue testing machine 1 stops and notifies the central software. The software controls industrial robot unit 2 to remove the tested sample and place it in the "completed" area, and then immediately begins to execute the task of sample 2 in the queue.

[0048] Report generation: After the entire batch of samples has been tested, the software automatically generates a PDF report that summarizes the fatigue life (SN curve), fracture location and other data of all samples.

[0049] The foregoing description enables those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A fully automated fatigue testing system, characterized in that, include: Fatigue testing machine (1) is used to test the mechanical properties of specimens; Industrial robot unit (2) is used to perform sample gripping, handling and placement operations; The machine vision unit is used to identify the ID information of the sample, position the sample to guide the industrial robot unit (2), and perform a centering check on the clamped sample. The intelligent clamping unit (3) is installed on the fatigue testing machine (1) to receive and automatically lock the sample placed by the industrial robot unit (2); The central control unit is connected to the fatigue testing machine (1), industrial robot unit (2), machine vision unit and intelligent fixture unit (3) for managing the sample testing queue, scheduling the collaborative work of each unit, and automatically binding and storing the test data and sample ID information.

2. The system according to claim 1, characterized in that, The industrial robot unit (2) is a six-axis industrial robot, and its end effector is an adaptive gripper (201) with integrated force / torque sensors.

3. The system according to claim 2, characterized in that, The force / torque sensor is used to monitor the force in real time during the gripping and placement of the sample. The central control unit adaptively adjusts the robot's movements based on the force data to prevent sample damage or improper placement.

4. The system according to claim 1, characterized in that, The machine vision unit includes: The first vision subsystem (4) is set in the sample storage area (401) to identify the ID information of the sample and determine its initial position coordinates on the sample stage (402). The second vision subsystem (403) is set in the clamping area of ​​the fatigue testing machine (1) to acquire images after the specimen is clamped, so as to calculate the deviation between the specimen axis and the loading axis of the testing machine and complete the alignment check.

5. The system according to claim 4, characterized in that, The central control unit is configured to: when the deviation detected by the second vision subsystem (403) exceeds a preset threshold, control the industrial robot unit (2) to re-grab and adjust the sample position, or issue an alignment failure alarm.

6. The system according to claim 1, characterized in that, The intelligent clamping unit (3) is a fast locking mechanism driven by pneumatic, hydraulic or servo motor. It has a self-centering V-shaped jaw (5) or an adaptive floating module, which can automatically compensate for the small positional deviation of the sample during the locking process.

7. The system according to claim 1, characterized in that, The central control unit includes: The queue management module is used to edit, store, and sequentially call task queues containing sample IDs and their corresponding test parameters; The collaborative scheduling module is used to automatically trigger the industrial robot unit (2) to perform the sample replacement process after the fatigue testing machine (1) completes the current test; The data management module is used to automatically create a database and uniquely bind the test data collected from the fatigue testing machine (1) with the sample ID read from the machine vision unit.

8. The system according to claim 1, characterized in that, The central control unit also integrates a digital twin module, which constructs a virtual model consistent with the physical system, used to map the operating status of the physical system in real time, perform process simulation prediction, and visual monitoring.

9. A fully automated fatigue testing method, applied to the system described in any one of claims 1-8, characterized in that, Includes the following steps: S1: Identify the test sample on the test stage (402) using the machine vision unit and obtain its ID information and spatial coordinates; S2: The central control unit plans the motion path of the industrial robot unit (2) according to the spatial coordinates and controls it to grasp the target sample; S3: The industrial robot unit (2) transports the sample and places it into the intelligent fixture unit (3) of the fatigue testing machine (1); S4: Intelligent clamping unit (3) automatically locks the sample; S5: The machine vision unit acquires and processes images of the clamped sample and calculates its centering deviation. S6: If the centering deviation is within the allowable range, the central control unit sends a command to the fatigue testing machine (1) to start the test; if the centering deviation exceeds the limit, an adjustment or alarm procedure is executed. S7: During the test, the central control unit collects test data in real time and binds and stores the data with the sample ID obtained in step S1; S8: After the current test is completed, the central control unit controls the industrial robot unit (2) to remove the tested sample and return to step S1 to grab the next sample until all samples in the queue have been tested.

10. The method according to claim 9, characterized in that, In step S3, the industrial robot unit (2) uses the force sensing function at the end of the device to place the sample into the fixture in a compliant control manner to ensure stable placement posture.

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