Full-automatic sorting method for impact performance detection samples

Abstract

The invention discloses a full-automatic sorting method for impact performance detection samples. The method comprises the steps that the samples are conveyed to a feeding station and then placed in a feeding disc according to the machining sequence; the control system sends sample information to the robot, the robot receives a centralized control instruction, and the clamping jaw moves to the designated position of the feeding disc to grab the sample and sends the sample to the sorting platform; samples qualified through sorting are put into a designated discharging box through the robot, the impact temperatures of the samples in the same discharging box are the same, the robot returns a sample sorting completion signal of the control system, and the control system issues a sorting task of the next sample. According to the method, the defects of traditional sample sorting are overcome, errors caused by visual identification are avoided, the accuracy of sample impact performance detection is ensured, and the overall efficiency of sample sorting is improved.

Description

Technical Field

[0001] This invention relates to the field of sample sorting technology, and in particular to a fully automated sorting method for samples used in impact performance testing. Background Technology

[0002] Traditional impact performance testing sample sorting mostly employs robots, vision recognition systems, and sample storage racks. The vision recognition system identifies sample markings, and the robot places the sample into a designated storage box on the sample storage rack, achieving automated sample sorting.

[0003] However, visual recognition is prone to errors in sample identification due to environmental factors, such as excessively high or low light intensity, dirt on the lens, or unclear sample number. These factors can cause errors in the visual recognition system, leading to abnormalities in the impact performance testing of the sample. Consequently, sample testing errors and misjudgments occur, and the efficiency of the testing operation is severely reduced. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a fully automatic sorting method for impact performance testing samples. This method overcomes the defects of traditional sample sorting, avoids errors caused by visual recognition, ensures the accuracy of impact performance testing of samples, and improves the overall efficiency of sample sorting.

[0005] To solve the above-mentioned technical problems, the fully automated sorting method for impact performance testing samples of the present invention includes the following steps: Step 1: The samples are transported to the loading station through the logistics system and automatically placed in the loading tray according to the processing sequence; Step 2: The control system sends the sample information to the robot through the communication protocol. The sample information includes the sample number, loading position, sample type, impact temperature and unloading position. The robot is preset with position information and sorting methods for different types of samples. The robot receives the centralized control command through network communication, moves the gripper to the designated position of the loading tray to grab the sample and send it to the sorting platform. Step 3: After sorting, qualified samples are placed into the feeding box designated by the control system by the robot. Samples in the same feeding box have the same impact temperature. The robot sends a signal back to the control system that the sample sorting is complete, and the control system issues the sorting task for the next sample.

[0006] Furthermore, the sample types in the sample information include plates, round bars, U-grooves, and V-grooves, and the robot is preset with sorting methods for plates, round bars, U-grooves, and V-grooves samples.

[0007] Furthermore, the communication protocol between the control system and the robot includes PLC-MC communication protocol, Modbus communication protocol, Tcp / IP-Socket communication protocol, WebSocket communication protocol, or HTTP communication protocol.

[0008] Furthermore, the sorting platform is equipped with size detection sensors and surface defect detection sensors. If a sample fails the size detection sensor and surface defect detection sensor, the robot will transfer the unqualified sample into the recycling box.

[0009] Because the fully automated sorting method for impact performance testing samples of this invention adopts the above-mentioned technical solution, the samples are transported to the loading station and placed in the loading tray according to the processing sequence. The control system sends sample information to the robot, which receives the centralized control command, moves its grippers to the designated position on the loading tray to grab the sample, and sends it to the sorting platform. Samples that pass the sorting are placed into designated unloading boxes by the robot. Samples in the same unloading box have the same impact temperature. The robot sends a signal back to the control system indicating that sample sorting is complete, and the control system issues the sorting task for the next sample. This method overcomes the shortcomings of traditional sample sorting, avoids errors caused by visual recognition, ensures the accuracy of impact performance testing, and improves the overall efficiency of sample sorting. Attached Figure Description

[0010] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments: Figure 1 This is a schematic diagram of the fully automated sorting method for impact performance testing samples according to the present invention. Detailed Implementation

[0011] Implementation, for example Figure 1 As shown, the fully automated sorting method for impact performance testing samples of the present invention includes the following steps: Step 1: The samples are transported to loading station 1 through the logistics system and automatically placed in loading tray 2 according to the processing sequence; Step 2: The control system 3 sends the sample information to the robot 4 through the communication protocol. The sample information includes the sample number, loading position, sample type, impact temperature and unloading position. The robot 4 is preset with position information and sorting methods for different types of samples. The robot 4 receives the centralized control command through network communication, moves the gripper to the designated position of the loading tray 2 to grab the sample and send it to the sorting platform 5. Step 3: After sorting, qualified samples are placed into the unloading box 6 designated by the control system 3 by the robot 4. The impact temperature of samples in the same unloading box 6 is the same. The robot 4 sends back a sample sorting completion signal to the control system 3, and the control system 3 issues the sorting task for the next sample.

[0012] Preferably, the sample types in the sample information include plates, round bars, U-grooves, and V-grooves, and the robot is preset with sorting methods for plates, round bars, U-grooves, and V-grooves samples.

[0013] Preferably, the communication protocol between the control system 3 and the robot 4 includes PLC-MC communication protocol, Modbus communication protocol, Tcp / IP-Socket communication protocol, WebSocket communication protocol, or HTTP communication protocol.

[0014] Preferably, the sorting platform 5 is equipped with a size detection sensor 51 and a surface defect detection sensor 52. If the sample fails the size detection sensor 51 and the surface defect detection sensor 52, the robot will transfer the unqualified sample into the recycling box 7.

[0015] This method sends sample information to the robot through the control system, eliminating the need for a visual recognition system. The robot sorts samples according to a pre-programmed procedure, avoiding sample sorting errors caused by visual recognition. Through the coordinated action of the robot and the control system, it can identify and grasp samples of different types and impact temperatures, ensuring the accuracy and efficiency of the feeding process.

[0016] This method, based on different sample types such as plate impact, round bar impact, U-groove, and V-groove, employs a pre-set sorting method on the robot. Sample information is transmitted to the robot via the control system. The distribution of sample information and the transmission of sorting completion signals can both be completed within 1 second, compared to at least 3 seconds required by a visual recognition system to identify sample information, thus greatly improving the overall efficiency of sample sorting.

[0017] The control system supports dynamic configuration of business processes and steps, dynamic management of business equipment, and multiple communication protocols. It automatically creates sorting processes and automatic loop processes based on configuration templates, automatically processes various logical business operations, supports real-time monitoring of process execution, and allows manual intervention in case of anomalies. Sorting rules are generated based on sample type and impact temperature configuration. Sorting information includes sample type, processing dimensions, sample number, and marking number, and can be manually modified according to actual on-site conditions. The control system database is equipped with a data management system for the entire production process, used for basic production management, configuration management, personnel organization, role and permission management, entrustment message management, production performance management, and process log management. This achieves fully automated control of sample sorting, effectively improving production efficiency, reducing labor intensity, and ensuring sample testing quality.

Claims

1. A fully automated sorting method for impact performance testing specimens, characterized in that... Includes the following steps: Step 1: The samples are transported to the loading station through the logistics system and automatically placed in the loading tray according to the processing sequence; Step 2: The control system sends the sample information to the robot through the communication protocol. The sample information includes the sample number, loading position, sample type, impact temperature and unloading position. The robot is preset with position information and sorting methods for different types of samples. The robot receives the centralized control command through network communication, moves the gripper to the designated position of the loading tray to grab the sample and send it to the sorting platform. Step 3: After sorting, qualified samples are placed into the feeding box designated by the control system by the robot. Samples in the same feeding box have the same impact temperature. The robot sends a signal back to the control system that the sample sorting is complete, and the control system issues the sorting task for the next sample.

2. The fully automated sorting method for impact performance testing samples according to claim 1, characterized in that: The sample types mentioned in the sample information include plates, round bars, U-grooves, and V-grooves. The robot is pre-set to sort the samples of plates, round bars, U-grooves, and V-grooves.

3. The fully automated sorting method for impact performance testing specimens according to claim 1 or 2, characterized in that: The communication protocol between the control system and the robot includes PLC-MC communication protocol, Modbus communication protocol, Tcp / IP-Socket communication protocol, WebSocket communication protocol, or HTTP communication protocol.

4. The fully automated sorting method for impact performance testing specimens according to claim 1, characterized in that: The sorting platform is equipped with size detection sensors and surface defect detection sensors. If a sample fails the size detection sensors and surface defect detection sensors, the robot will transfer the unqualified sample into the recycling box.

Images