Nut positioning, mounting and control method for copper bar press riveter and related equipment

Abstract

This application relates to the fields of artificial intelligence-based equipment control and industrial manufacturing technology, and provides a nut positioning and installation control method and related equipment for a copper busbar riveting machine. By establishing a spatial reference through equipment self-inspection and zeroing, the system enables automatic matching of task parameters between fixture in-situ detection and part number retrieval, preventing mixed material production. A first-vision station pre-inspects empty fixtures, preventing damage from collisions between the material handling mechanism and residual hard objects. A second-vision station acquires global images and extracts multi-dimensional feature parameters. Difference and coupling analyses are performed on these multi-dimensional feature parameters, and a defect degree is generated by fusion calculation combined with neighborhood influence factors. This degree is then compared with multi-level thresholds and classified into different levels before differentiated handling is implemented. This achieves hierarchical control, automatically compensating for minor anomalies and intercepting severe anomalies. While improving production efficiency and eliminating human safety hazards, it effectively prevents defective nuts from entering the riveting process, thus improving the efficiency and reliability of the industrial production process.

Description

Technical Field

[0001] This application relates to the fields of artificial intelligence-based equipment control and industrial manufacturing technology, and more specifically, to a nut positioning and installation control method and related equipment for a copper busbar riveting machine. Background Technology

[0002] Copper busbars are key conductive components widely used in power systems, such as busbar trunking and switchgear. During their processing, nuts need to be crimped and fixed to specific positions on the copper busbars for subsequent threaded connections. Currently, some solutions in the industry use a vibratory feeder combined with a mechanical screening mechanism to automatically feed the nuts. However, the mechanical screening in this solution can only make a preliminary judgment on the orientation of the nuts based on their shape, and cannot detect surface defects or positional deviations after placement. Furthermore, there is a lack of unified status monitoring and interlocking mechanisms between different process stages.

[0003] In practical applications, the above solution lacks visual inspection capabilities, making it impossible to detect and intercept surface defects such as nuts, omissions, and misalignments in a timely manner. Defective products continue to flow into the riveting process, resulting in the scrapping of copper busbars. At the same time, each link operates independently without interlocking, and the subsequent process continues to execute even if any link malfunctions, resulting in low industrial production efficiency and reliability. Summary of the Invention

[0004] This application provides a nut positioning and installation control method and related equipment for a copper busbar riveting machine, which can at least partially solve the problem of low industrial production efficiency and reliability.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of this application, a nut positioning and installation control method for a copper busbar riveting machine is provided, comprising: when the working air pressure of the copper busbar riveting machine is detected to be normal, controlling each motion axis to perform a return-to-origin operation, so that each motion axis returns to a preset reference position; after detecting that the fixture is in place, obtaining the product part number, retrieving the process parameter set corresponding to the product part number from the memory, the process parameter set including the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension; after determining that the fixture is in a clean state through a preset first visual station, the picking mechanism sequentially picks up nuts from the picking position, and places the nuts sequentially on the corresponding station of the fixture according to the target coordinates in the process parameter set, until the number of placed nuts reaches the total number of nuts; After the material placement is completed, a global image of the carrier plate is acquired at a preset second vision station. The global image is preprocessed to segment the contour information of the nut, and multi-dimensional feature parameters of the nut are extracted from the contour information. The multi-dimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the area ratio of the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. Difference analysis and coupling analysis are performed on the relative deviation ratio, area ratio, and contour deviation value of the nut, and the defect degree is obtained by combining the neighborhood influence factor between adjacent nuts. The defect degree of the nut is compared with a preset multi-level threshold. According to the comparison result, the nut is divided into different abnormal levels, and the corresponding handling strategy is executed according to the abnormal level.

[0007] In this application, based on the aforementioned scheme, controlling each motion axis to perform a return-to-origin operation, so that each motion axis returns to a preset reference position, includes: first controlling the Z-axis to return to the origin, and then controlling the X-axis module and Y-axis module to return to the origin simultaneously; wherein, the X-axis and Y-axis are horizontal motion axes used to drive the picking head and unloading head to move horizontally to each picking position and unloading position; the Z-axis is a vertical motion axis; controlling the fixture translation axis to return to the origin, and then each axis waits in the standby position; wherein, the fixture translation axis is a horizontal motion axis independent of the X-axis, Y-axis, and Z-axis, used to drive the fixture to perform horizontal transport and transfer between the unloading position and the riveting position.

[0008] In this application, based on the aforementioned scheme, the material handling mechanism sequentially picks up nuts from the material handling position and places them sequentially on the corresponding workstations of the fixture according to the target coordinates in the process parameter set, until the number of nuts placed reaches the total number of nuts. This includes: the X-axis module and the Y-axis module moving to the first material handling position of the material handling position, the first Z-axis cylinder pressing down to perform the material handling action, and the cylinder resetting after the material handling is completed; subsequently, the X-axis module and the Y-axis module sequentially move to the second, third, and fourth material handling positions, and the Z-axis cylinders corresponding to each material handling position sequentially perform the material handling action. After the material handling is completed, the module resets. Once all materials are picked up, the X-axis module and Y-axis module simultaneously move to the first material placement position. The first Z-axis cylinder presses down to perform the material placement action and then resets. Subsequently, the X-axis module and Y-axis module move sequentially to the second, third, and fourth material placement positions. The Z-axis cylinders corresponding to each material placement position sequentially perform the material placement action and then reset. After completing one material handling cycle, the X-axis module and Y-axis module return to the material handling position and repeat the material handling control stage and the material placement control stage until the number of nuts placed on the fixture reaches the total number of nuts.

[0009] In this application, based on the aforementioned scheme, the step of preprocessing the global image to segment the nut's contour information and extracting the nut's multidimensional feature parameters from the contour information includes: registering the global image according to the target coordinates of each feeding station; performing binarization processing on the registered global image; extracting the nut's outer contour and inner hole contour through connected component analysis as contour information; and calculating the nut's multidimensional feature parameters based on the contour information.

[0010] In this application, based on the aforementioned scheme, the calculation of the multidimensional feature parameters of the nut based on the contour information includes: extracting the actual position of the nut based on the outer contour of the nut, and calculating the relative deviation ratio according to the degree of deviation between the actual position and the target position; delineating a projection area based on the outer contour of the nut, identifying defect areas within the projection area, and calculating the area ratio value according to the proportion of the defect area to the projection area; and calculating the contour deviation value based on the distances from multiple sampling points on the outer contour of the nut to the actual centroid of the nut, according to the degree of dispersion between the distances.

[0011] In this application, based on the aforementioned scheme, the step of performing difference analysis and coupling analysis on the relative deviation ratio, area ratio, and contour deviation value of the nuts, and combining this with the neighborhood influence factor between adjacent nuts to calculate the defect degree, includes: converting the relative deviation ratio, area ratio, and contour deviation value of each nut into normalized features through nonlinear mapping; calculating the basic deviation metric value of each nut based on the difference between the normalized features and a preset reference vector; constructing a second-order interaction matrix based on the normalized features of the nuts, and calculating the difference metric value between the second-order interaction matrix and the reference interaction matrix; using the minimum value in the normalized features as the higher-order coupling excitation value; fusing the basic deviation metric value, the difference metric value, and the higher-order coupling excitation value to calculate the individual defect degree of the nut; obtaining the spatial distance between the nut and its adjacent nuts, and calculating the neighborhood influence factor based on the individual defect degree of the adjacent nuts and the spatial distance; and fusing the individual defect degree of the nut with the corresponding neighborhood influence factor to obtain the defect degree of the nut.

[0012] In this application, based on the aforementioned scheme, the defect degree of the nut is compared with a preset multi-level threshold, and the nuts are classified into different abnormal levels according to the comparison results. A corresponding handling strategy is then executed according to the abnormal level, including: when the defect degree of all nuts is less than or equal to the first threshold, it is determined to be at a normal level, and the process proceeds normally to the alternating double fixture and riveting operation; when the defect degree of a nut is greater than the first threshold and less than or equal to the second threshold, and the relative deviation ratio of the nut is the only deviation type exceeding the allowable range among all dimensional deviations, it is determined to be at a slight abnormal level, and the position compensation of the nut is calculated. Before riveting, the material handling mechanism is used to perform position compensation. After compensation, the defect degree calculation and level judgment are re-executed. When the defect degree of a nut is greater than the second threshold and less than or equal to the third threshold, or the area ratio value is greater than the preset severe defect threshold, it is judged as a moderate abnormality level. The abnormal nut number and detailed feature parameters of each dimension are displayed on the touch screen, and the operator waits for manual confirmation before selecting to release or reject it. When the defect degree of a nut is greater than the third threshold, or the contour deviation value is greater than the preset severe contour deviation threshold, it is judged as a severe abnormality level, an alarm signal is issued and all subsequent processes are locked.

[0013] According to one aspect of this application, a nut positioning and installation control device for a copper busbar riveting machine is provided, comprising: The initialization module is used to control each motion axis to perform a return-to-origin operation when the working air pressure of the copper busbar riveting machine is normal, so that each motion axis returns to the preset reference position. The acquisition module is used to acquire the product part number after detecting that the fixture is in place, and retrieve the process parameter set corresponding to the product part number from the memory. The process parameter set includes the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension. The placement module is used to determine that the fixture is in a clean state through a preset first visual station. Then, the material picking mechanism picks up nuts from the picking position in sequence and places them on the corresponding positions of the fixture according to the target coordinates in the process parameter set until the number of nuts placed reaches the total number of nuts. The detection module is used to acquire a global image of the carrier plate after the material is placed at a preset second vision station, preprocess the global image to segment the contour information of the nut, and extract the multi-dimensional feature parameters of the nut from the contour information. The multi-dimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the ratio of the area of ​​the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. The calculation module is used to perform difference analysis and coupling analysis on the relative deviation ratio, area ratio value and contour deviation value of the nuts, and to perform fusion calculation by combining the neighborhood influence factors between adjacent nuts to obtain the defect degree; The execution module is used to compare the defect level of the nut with a preset multi-level threshold, classify the nut into different abnormal levels according to the comparison results, and execute the corresponding handling strategy according to the abnormal level.

[0014] According to one aspect of this application, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the nut positioning and installation control method for a copper busbar riveting machine as described in the above embodiments.

[0015] According to one aspect of this application, a computer device is provided, comprising: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the nut positioning and installation control method for a copper busbar riveting machine as described in the above embodiments.

[0016] According to one aspect of this application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the nut positioning and installation control method for a copper busbar riveting machine provided in the various alternative implementations described above.

[0017] The main differences and technical effects of the technical solution of this application compared with the prior art are as follows: This technical solution establishes a spatial benchmark through equipment self-inspection and zeroing to ensure accurate positioning of each motion axis; it achieves automatic matching of task parameters through fixture in-situ detection and part number retrieval to prevent mixed material production; it pre-inspects empty fixtures at the first vision station to prevent damage from collisions between the material handling mechanism and residual hard objects; it acquires global images and extracts multi-dimensional feature parameters through the second vision station, performs difference and coupling analysis on the multi-dimensional feature parameters, and combines them with neighborhood influence factors to generate a defect degree, achieving a comprehensive quantitative assessment of omissions, deviations, and defects; by comparing the defect degree with multi-level thresholds and classifying abnormal levels, it performs differentiated handling to achieve hierarchical control of automatic compensation for minor abnormalities and immediate interception of serious abnormalities. While improving production efficiency and eliminating human safety hazards, it effectively prevents defective nuts from flowing into the riveting process, improving the efficiency and reliability of the industrial production process.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0020] Figure 1 The flowchart illustrating a nut positioning and installation control method for a copper busbar riveting machine in one embodiment of this application is shown schematically.

[0021] Figure 2 The illustration shows a schematic diagram of the copper busbar before the nut is attached in one embodiment of this application.

[0022] Figure 3 The diagram illustrates a copper busbar pressing a nut in one embodiment of this application.

[0023] Figure 4 The illustration shows a schematic diagram of a nut positioning and installation control device for a copper busbar riveting machine in one embodiment of this application.

[0024] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the computer device of the present application is shown. Detailed Implementation

[0025] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0026] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0027] It should be noted that the data acquisition or information collection in this embodiment is performed after authorization by the user or the object of collection, and its process and purpose strictly follow the relevant regulations.

[0028] The block diagrams shown in the attached figures are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more hardware modules composed of smart chips, smart integrated circuits, or application-specific integrated circuits (ASICs), or in different network and / or processor devices and / or microcontroller devices.

[0029] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0030] The implementation details of the technical solution of this application are described below: Figure 1A flowchart illustrating a nut positioning and installation control method for a copper busbar riveting machine according to an embodiment of this application is shown. The copper busbar riveting machine of this application mainly consists of a material handling mechanism, a material feeding mechanism, a fixture translation axis, a dual-vision station, and a riveting mechanism. The material handling and feeding mechanisms share the same X / Y axis module, and are each equipped with an independent Z-axis cylinder. The X-axis and Y-axis modules drive the material handling head and the material feeding head to move as a whole. The fixture translation axis operates independently, responsible for the reciprocating transport of the fixture between the feeding station, the vision station, and the riveting station. Its working principle is as follows: After the equipment is zeroed and the part number parameters are loaded, the material handling mechanism picks up the nut from the material handling position and places it into the corresponding fixture station; after the material is full, it undergoes a full inspection at the second vision station. Qualified products are sent to the riveting station by the translation axis, where the nut is riveted and fixed to the predetermined position on the copper busbar.

[0031] Reference Figure 1 As shown, the nut positioning and installation control method for the copper busbar riveting machine includes at least steps S110 to S160, which are described in detail below: S110, when the working air pressure of the copper busbar riveting machine is normal, controls each motion axis to perform a return-to-origin operation, so that each motion axis returns to the preset reference position.

[0032] In this embodiment, after the equipment is powered on, it first reads the value of the air pressure sensor to determine whether the working air pressure has reached a preset threshold, such as 0.5 to 0.7 MPa. If the air pressure is abnormal, the touchscreen displays an alarm message and prevents the equipment from starting, to prevent the pneumatic components from failing to operate properly under low pressure. If the air pressure is normal, the operator clicks the one-click homing button on the main screen of the touchscreen to perform the homing operation. After all homing operations are completed, each axis waits in the standby position.

[0033] In one embodiment of this application, controlling each motion axis to perform a return-to-origin operation, so that each motion axis returns to a preset reference position, includes: First, control the Z-axis to return to the origin, then control the X-axis module and Y-axis module to return to the origin simultaneously; among them, the X-axis and Y-axis are horizontal motion axes, used to drive the picking head and discharging head to move horizontally to each picking position and discharging position; the Z-axis is the vertical motion axis; The control fixture translation axis returns to its origin, after which all axes wait in the standby position. The fixture translation axis is a horizontal motion axis independent of the X, Y, and Z axes, used to drive the fixture for horizontal transport and transfer between the unloading and riveting positions. The X-axis and Y-axis modules drive the pick-and-place head assembly, while the fixture translation axis drives the slide that carries the fixture. These two components are spatially located at different levels and do not interfere with each other.

[0034] In one embodiment of this application, when controlling each motion axis to perform a homing operation, a homing command is first sent to the servo driver of the Z-axis, causing the Z-axis to move vertically upwards until the homing sensor is triggered, completing the vertical position reference calibration. Subsequently, homing commands are sent to the servo drivers of the X-axis and Y-axis modules, causing them to move synchronously in two mutually orthogonal directions in the horizontal plane to their respective homing sensor trigger positions, completing the horizontal position reference calibration. Finally, a homing command is sent to the servo driver of the fixture translation axis, causing it to move horizontally to its homing sensor trigger position, completing the independent position reference calibration of the fixture's transport direction. If, during the homing process of any of the above axes, the axis fails to trigger the homing sensor within a preset time window, an alarm signal is issued and the homing operation is terminated.

[0035] After all motion axes have returned to their origin, the servo drivers of each axis send back a confirmation signal. Once the confirmation signals from the Z-axis, X-axis, Y-axis, and fixture translation axis have been received, it is determined that all motion axes have returned to their preset reference positions. The current coordinates of each axis are then zeroed, and the origin return completion status information is displayed on the touchscreen. Each axis remains in standby position awaiting subsequent instructions. Specifically, the X-axis and Y-axis are horizontal motion axes used to drive the pick-up and unload heads to move horizontally to their respective pick-up and unload positions; the Z-axis is a vertical motion axis used to drive the pick-up and unload heads to move vertically up and down to perform pick-up and unload actions; the fixture translation axis is a horizontal motion axis independent of the X-axis, Y-axis, and Z-axis, used to drive the fixture to perform horizontal transport and transfer between the unload position and the riveting position.

[0036] The above process ensures that the pneumatic components operate under rated working pressure through air pressure detection, and eliminates the cumulative positional errors of each axis caused by mechanical backlash, encoder drift, or unexpected power outages during long-term operation by returning each motion axis to its origin in sequence. This establishes a unified spatial coordinate reference for subsequent material handling, unloading, and visual inspection, ensuring that the material handling head can accurately align with the material handling position, the unloading head can accurately align with the target coordinates of each workstation, and the computer vision system can perform image registration and deviation calculation based on a unified coordinate system.

[0037] S120: After detecting that the fixture is in place, obtain the product part number and retrieve the process parameter set corresponding to the product part number from the memory. The process parameter set includes the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension.

[0038] In this embodiment, after the equipment returns to its origin, it checks whether the fixtures are within the sensing area. Upon first startup, both fixtures must be manually placed next to the riveting machine. Simultaneously, it checks whether the coordinate parameters for the nut pick-up and nut placement positions are set correctly. The operator checks the current part number selection on the touchscreen to ensure it is correct, and selects the corresponding part number after confirmation. Based on the selected part number, the corresponding process parameter set is retrieved from the memory. The touchscreen displays the currently selected part number and the corresponding number of nuts. The operator must confirm that everything is correct before proceeding to the next step.

[0039] In this embodiment, the process parameter set includes: the total number of nuts N, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension.

[0040] Specifically, the total number of nuts represents the total number of nuts required for the single product corresponding to the current product part number, and is used to control the number of times the material pick-and-place cycle is executed.

[0041] Specifically, the target coordinates of each feeding station represent the theoretical position value of each nut on the fixture relative to the equipment coordinate system, which is used to guide the feeding mechanism to accurately place the nut to the predetermined position.

[0042] Specifically, the judgment threshold for each inspection item represents the upper limit of the permissible value of each quality indicator in visual inspection, such as the upper limit of positional deviation, defect area, and contour deviation, which is used to determine whether the nut is qualified.

[0043] Specifically, the detection weight coefficients for each dimension represent the contribution weights assigned to each dimension of position deviation, defect area, and contour deviation when calculating the overall defect degree of the nut, and are used to reflect the importance of different quality indicators to the final judgment result.

[0044] The above process prevents the equipment from starting erroneously when the fixture is not placed correctly by checking the fixture in place, thus avoiding the material handling mechanism from running empty or colliding. By selecting the part number, the corresponding set of process parameters is retrieved from the database, so that the same equipment can be compatible with the production needs of different product models without the need for manual input of parameters one by one. At the same time, it ensures that the target coordinates, judgment thresholds and weight coefficients of each material handling station match the current product, preventing incorrect material placement or mismatch of detection standards due to parameter confusion.

[0045] S130: After determining that the fixture is in a clean state through the preset first visual station, the material picking mechanism picks up nuts from the picking position in sequence and places the nuts in the corresponding positions of the fixture according to the target coordinates in the process parameter set until the number of nuts placed reaches the total number of nuts.

[0046] In this embodiment, the clean state refers to the first vision station detecting, through template matching method, that there are no residual nuts or foreign objects on the surface of the fixture; the non-clean state refers to the detection of residual nuts or foreign objects on the surface of the fixture. At this time, the vision judgment is NG, triggering an alarm and locking the process. Manual cleaning is required before it can continue.

[0047] In this embodiment, the first vision station is set at the nut placement station. After the fixture is moved to the nut placement station by the fixture translation axis, the first vision station takes pictures of the empty fixture for inspection.

[0048] In one embodiment of this application, the material handling mechanism performs material handling and placement operations. First, the X-axis module and Y-axis module drive the material handling head to the material handling position. The Z-axis cylinders corresponding to each material handling position press down sequentially to perform the material handling action, gripping the nut from the direct vibration outlet through the gripper or the internal support type material handling head. After each material handling is completed, the proximity sensor confirms that the nut has been successfully gripped, and the material handling cylinder resets. After all materials are handled, the X-axis module and Y-axis module drive the material handling head to the material handling position. The Z-axis cylinders corresponding to each material handling position press down sequentially to perform the material handling action, placing the nut on the corresponding work position of the fixture. The proximity sensor at the carrier plate placement position confirms that the nut is in place. After completing one material handling and placement cycle, the X-axis module and Y-axis module return to the material handling position and repeat the above material handling and placement actions until the number of nuts placed on the fixture reaches the total number of nuts.

[0049] In actual operation, the first step is to check the fixture's position and conduct a preliminary visual inspection of the empty fixture. The operator places the fixture plate onto the lower die of the hydraulic press. After the equipment senses the fixture, the operator presses the double switch button. The fixture's translation axis moves into the riveting machine, where the lifting mechanism lifts the fixture and moves it to the nut placement position.

[0050] The empty fixture before the nut is installed at the first vision station (e.g.) Figure 2 As shown, a photo inspection is performed to determine whether there are residual nuts or foreign objects on the surface of the fixture based on template matching. If there are residual objects, the visual photo is judged as NG, the touch screen alarm is triggered: there are nuts on the empty fixture plate, please check, and the subsequent material handling process is locked; after manually removing the nuts or foreign objects, the start button is pressed to re-perform the visual pre-inspection. After confirming that there are no residual nuts or foreign objects, the next step is continued.

[0051] Optionally, the equipment is equipped with two fixtures, each assigned a number (Jig 1 and Fixture 2). When Fixture 1 is in the waiting area awaiting riveting and Fixture 2 is idle, the fixture translation axis first moves Fixture 2 from the lower die of the riveting machine to the nut placement station to begin material placement. Then, Fixture 1 is moved from the waiting area to the riveting station for riveting. After riveting is completed, the operator removes the finished fixture, which becomes idle and can be reintroduced into the cycle. Through the above scheduling logic, the two fixtures form a production line-like alternating operation between the material placement station and the riveting station. While one fixture is placing material at the nut placement station, the other fixture is riveting at the riveting station, achieving continuous and uninterrupted alternating operation of the equipment.

[0052] In one embodiment of this application, the material handling mechanism sequentially picks up nuts from the material handling position and places them sequentially on the corresponding workstations of the fixture according to the target coordinates in the process parameter set, until the number of nuts placed reaches the total number of nuts, including: The X-axis and Y-axis modules move to the first picking position of the picking station, and the first Z-axis cylinder presses down to perform the picking action. After picking up the material, the cylinder resets. Subsequently, the X-axis and Y-axis modules move to the second, third, and fourth picking positions in sequence. The Z-axis cylinders corresponding to each picking position perform the picking action in sequence and then reset. Here, Z-axis refers to the servo-driven Z-axis main motion axis; Z-axis cylinder refers to the pneumatic actuator installed on the Z-axis module.

[0053] It should be noted that the configuration of 4 picking heads and 4 discharging heads in this embodiment is merely an example. The 4 picking heads are arranged at equal intervals along the X-axis, with the spacing between adjacent picking heads being the same as the spacing between each picking position at the direct vibration outlet. Similarly, the 4 discharging heads are arranged at equal intervals along the X-axis, with the spacing between adjacent discharging heads being the same as the spacing between each discharging position on the fixture. The picking head group and the discharging head group are staggered along the Y-axis to avoid interference when operating simultaneously. A single picking and discharging cycle can complete the picking and discharging of 4 nuts. The total number of nuts N is determined by the product part number. The control system compares the number of nuts already placed with N to determine whether to continue the picking and discharging cycle until the number of nuts already placed reaches N.

[0054] After all materials are picked up, the X-axis module and the Y-axis module move simultaneously to the first material feeding position. The first Z-axis cylinder presses down to perform the material feeding action and then resets. Subsequently, the X-axis module and the Y-axis module move sequentially to the second, third, and fourth material feeding positions. The Z-axis cylinders corresponding to each material feeding position perform the material feeding action sequentially and then reset.

[0055] After completing one material handling cycle, the X-axis module and Y-axis module return to the material handling position to repeat the material handling control stage and the material handling control stage until the number of nuts placed on the fixture reaches the total number of nuts.

[0056] After the empty fixture passes inspection, the X-axis and Y-axis modules move to the first nut-picking position. Once the through-beam optical fiber at this position confirms that the nut is in place, the first cylinder on the corresponding Z-axis presses down to drive the gripper to perform the picking action. After picking, the proximity sensor confirms that the nut has been successfully picked up, and the cylinder returns to its origin. This process is repeated, with the X-axis and Y-axis modules moving sequentially to the second, third, and fourth picking positions. The corresponding Z-axis cylinder at each picking position performs the picking action sequentially and then returns to its origin. If the through-beam optical fiber at any picking position fails to detect the nut being in place within a timeout period, or if the proximity sensor fails to report successful picking within a timeout period, an interlock is triggered and an alarm is activated.

[0057] After all materials are picked up, the X-axis and Y-axis modules simultaneously move to the first feeding position of the first row of feeding stations. The first Z-axis cylinder presses down to perform the feeding action. After the proximity sensor at the carrier plate placement position confirms that the nut has been successfully placed, the first cylinder resets. Subsequently, the X-axis and Y-axis modules move sequentially to the second, third, and fourth feeding positions, and the corresponding Z-axis cylinders at each feeding position sequentially perform the feeding action and then reset. After completing one picking and feeding cycle, the X-axis and Y-axis modules return to the picking position and repeat the picking and feeding actions until the number of nuts placed on the fixture reaches the preset total number of nuts N (e.g., ...). Figure 3 (As shown).

[0058] The above process involves pre-inspecting the empty fixture at the first vision station to intercept any residual nuts or foreign objects on the fixture before the material handling operation begins. This prevents the gripper from deforming or being damaged when the material handling mechanism presses down on the hard object. It also avoids positional interference between the newly placed nuts and the residual objects. The material handling mechanism then sequentially picks up the nuts from the picking position and places them precisely according to the target coordinates. This transforms the discrete operation of manual placement into an automated continuous operation, eliminating uncertainties such as fatigue and negligence caused by manual operation. It fundamentally avoids the inherent defects of manual operation, such as missed placement, incorrect placement, and misplacement.

[0059] S140: At the preset second vision station, a global image of the carrier plate after the material placement is completed is acquired. After preprocessing the global image, the contour information of the nut is segmented, and multi-dimensional feature parameters of the nut are extracted from the contour information. The multi-dimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the area ratio of the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. The relative deviation ratio, area ratio, and contour deviation value of the nut are subjected to difference analysis and coupling analysis, and combined with the neighborhood influence factor between adjacent nuts for fusion calculation to obtain the defect degree.

[0060] In one embodiment of this application, a second vision station is positioned above the fixture. After the X-axis and Y-axis modules have completed the placement of all nuts and returned to the standby position, the second vision station is triggered to acquire a global image of the fixture. The acquired global image is sequentially converted to grayscale and then subjected to Gaussian filtering for noise reduction to eliminate image noise and enhance contour features. Then, the global image is registered according to the target coordinates of each feeding station to correct the overall positioning deviation of the fixture. The registered image undergoes adaptive binarization to separate the nut area from the background area. Then, the outer contour and inner hole contour of each nut are extracted using connected component analysis as contour information. Based on the extracted contour information, multidimensional feature parameters for each nut are calculated. These multidimensional feature parameters include a relative deviation ratio, a surface defect area ratio, and a contour deviation value. Finally, the multidimensional feature parameters of each nut are substituted into a defect degree calculation model to obtain a defect degree characterizing the overall state of the nut. The defect degree is a comprehensive quantitative index used to characterize the overall state of the nut in terms of positional accuracy, surface quality, and contour integrity. The lower the value, the healthier the overall quality state of the nut.

[0061] It should be noted that in this embodiment, a first vision station and a second vision station are built based on computer vision technology to acquire corresponding images and detect the working status of industrial equipment through image recognition. The first vision station is located at the nut placement station. Before material handling, it photographs the empty fixture to detect residue, and the result serves as the material handling enable signal. Only after passing the inspection can material handling be performed. The second vision station is located above the fixture. After material placement is completed, it takes a global photograph, extracts information on the position of each nut in multiple dimensions, and calculates the defect degree, achieving a comprehensive quality judgment before riveting. Both stations prevent collisions at the source and intercept defects at the end, forming a dual protection mechanism.

[0062] In one embodiment of this application, the contour information of the nut is segmented after preprocessing the global image, and multidimensional feature parameters of the nut are extracted from the contour information, including: The global image is registered according to the target coordinates of each feeding station. The registered global image is then binarized. The outer contour and inner hole contour of the nut are extracted by connected component analysis as contour information. The multidimensional feature parameters of the nut are calculated based on the contour information.

[0063] Specifically, the multidimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the proportion of the surface defect area to the projected area of ​​the nut, and the contour deviation value of the outer contour relative to the standard circle. The relative deviation ratio quantifies the degree of deviation of the actual placement position of the nut from the target position; a larger value indicates a more severe positional deviation. The area proportion quantifies the proportion of the surface defect area to the overall projected area of ​​the nut; a larger value indicates a more severe surface defect. The contour deviation value quantifies the degree of deformation of the nut's outer contour relative to the standard circle; a larger value indicates a more severe contour deformation.

[0064] Specifically, in one embodiment of this application, the global image is first registered using an affine transformation based on the target coordinates of each feeding station to correct the image position deviation caused by the overall offset and rotation of the fixture; then, the registered global image is subjected to adaptive binarization processing, and the segmentation threshold is dynamically determined based on the local grayscale distribution of the image to separate the nut region from the background region, so that the nut appears as a foreground connected region; finally, connected component labeling is performed on the binarized image, all foreground pixels are traversed and the pixel set of each connected region is counted, and the connected regions belonging to the nut are filtered out according to the preset region range corresponding to the target coordinates of each station, and then the outer contour pixel set and inner hole contour pixel set of each connected region are extracted as the contour information of the corresponding nut.

[0065] Next, the actual position of the nut is extracted based on its outer contour, and the relative deviation ratio is calculated according to the degree of deviation between the actual position and the target position. Specifically, this is done by analyzing the nut in the binarized image. i The actual centroid coordinates are obtained by averaging the coordinates of all pixels in the connected region, representing the actual center position of the nut in the image. Calculate the actual centroid coordinates relative to the preset target coordinates of the workstation. The Euclidean distance is calculated, and the sum of the squares of the squares of the Euclidean distance divided by the preset position tolerance thresholds in the X and Y directions is taken to obtain the relative deviation ratio. for: in, These represent the preset position tolerance thresholds in the X and Y directions, respectively. The value of the position tolerance threshold is determined according to the requirements of the nut positioning accuracy in the copper busbar riveting process. The typical value range is 0.5mm to 2.0mm, and the specific value is determined by the nut position tolerance requirements marked in the product drawing.

[0066] This process involves defining the nut's projection area based on its outer contour, identifying defective areas within this projection area (such as scratches, rust, or dents), and then determining the area of ​​each defective region. The proportion of the projected area to the surface defect area is calculated to obtain the proportion of the projected area of ​​the nut. for: in, The area of ​​the projected region; This represents the standard deviation of pixel grayscale values ​​for defective areas in the same batch of nuts, used to reflect the severity of defects, such as scratch depth and degree of corrosion. This is the mean of the standard deviation of grayscale defects in nuts of the same batch. It is preset by the process personnel according to the process standard of this type of nut and stored in the control system. It represents the reference value of the standard deviation of grayscale defects in the defect area under normal process conditions. This is the sensitivity coefficient, with a value ranging from 0.3 to 1.0. The specific value is pre-calibrated by process engineers within the above-mentioned principle range based on actual process verification results and stored in the control system, for example, for high-reliability products (such as those used in high-voltage power equipment). Take the upper limit of the corresponding type range, and for ordinary products, take the median or lower limit. The area ratio value is used to indicate that, when the defect area ratio is the same, defects with drastic grayscale changes (such as deep scratches) have a greater impact on riveting quality than defects with gradual grayscale changes (such as slight stains).

[0067] Specifically, the contour deviation value is calculated based on the distances from multiple sampling points on the outer contour of the nut to the actual centroid of the nut, according to the degree of dispersion between each distance. More specifically, multiple sampling points are uniformly collected on the outer contour of the nut, and the distance from each sampling point to the actual centroid coordinates is calculated. Then, the sum of the absolute values ​​of the deviations between this distance and the average distance is calculated and divided by the product of the number of sampling points and the average distance to obtain the contour deviation value. This value reflects the roundness deviation of the nut's outer contour; a larger value indicates a more severe contour deformation, such as local dents caused by impacts.

[0068] S150 performs difference and coupling analysis on the relative deviation ratio, area ratio, and contour deviation of the nuts, and combines the neighborhood influence factors between adjacent nuts for fusion calculation to obtain the defect degree.

[0069] In this embodiment, the three-dimensional feature parameters of each nut are converted into normalized features through nonlinear mapping. The difference between each nut and a preset benchmark vector is calculated as the basic deviation metric. A second-order interaction matrix is ​​constructed and the difference between it and the benchmark interaction matrix is ​​calculated as the two-dimensional coupling metric. The minimum value among the normalized features is taken as the higher-order coupling excitation value. The three are fused to obtain the individual defect degree, so as to capture the multi-level coupling effects such as single-dimensional independent deviation, two-dimensional synergistic amplification, and three-dimensional joint deterioration. On this basis, the spatial distance between each nut and its adjacent nuts is obtained. The neighborhood influence factor is calculated based on the individual defect degree and spatial distance of the adjacent nuts. The individual defect degree and the neighborhood influence factor are fused to obtain the final defect degree. Thus, while evaluating the multi-dimensional comprehensive quality of a single nut, the risk of offset interference between adjacent nuts on the carrier plate is taken into consideration, realizing the complete quantification of each nut from independent quality assessment to group collaborative assessment.

[0070] In one embodiment of this application, difference analysis and coupling analysis are performed on the relative deviation ratio, area ratio, and contour deviation value of the nuts, and the defect degree is obtained by combining the neighborhood influence factors between adjacent nuts. The relative deviation ratio, area ratio, and profile deviation of each nut are converted into normalized features through nonlinear mapping. Based on the difference between the normalized features and the preset reference vector, calculate the basic deviation metric value of each nut; construct a second-order interaction matrix based on the normalized features of the nut, and calculate the difference metric value between the second-order interaction matrix and the reference interaction matrix; take the minimum value in the normalized features as the higher-order coupling excitation value. The individual defect degree of the nut is obtained by fusing the basic deviation metric, the difference metric, and the higher-order coupling excitation value. Obtain the spatial distance between the nut and its adjacent nuts, and calculate the neighborhood influence factor based on the individual defect degree of the adjacent nuts and the spatial distance; The defect degree of the nut is obtained by fusing the individual defect degree of the nut with the corresponding neighborhood influence factor.

[0071] In one embodiment of this application, when calculating the defect degree of the nut, the multidimensional characteristic parameters of the nut are first normalized. The relative deviation ratio, area ratio, and contour deviation value of the nut are converted into normalized features through tanh (hyperbolic tangent function) nonlinear mapping, which constitutes the normalized features of each nut.

[0072] The preset benchmark vector is calculated, which consists of the characteristic mean values ​​of qualified samples of this model in three dimensions: relative deviation ratio, area ratio, and contour deviation value. Specifically, where represents the characteristic mean values ​​of qualified samples in the same batch in the three dimensions. The benchmark interaction matrix is ​​calculated by the outer product of this preset benchmark vector, representing the coupled benchmark value when all dimensions are in the benchmark state.

[0073] Then, based on the difference between each normalized feature and the preset reference vector, the basic deviation metric value of each nut is calculated to reflect the independent cumulative effect of deviation in each dimension. The larger the value, the more serious the deviation of each dimension from the reference.

[0074] Subsequently, to capture the interactive coupling relationship between the deviations in each dimension, a second-order interaction matrix was constructed based on the normalized characteristics of each nut. The second-order interaction matrix is ​​obtained by multiplying the normalized feature by its own transpose. When two dimensions simultaneously deviate, their combined deterioration effect on product quality is greater than the sum of their individual contributions, i.e., a coupling amplification effect exists. In the actual nut riveting process, positional deviation changes the contact direction, contour deviation changes the stress distribution, and defect area changes the effective load-bearing cross section. These three factors are coupled through contact mechanics, and the combined deterioration effect is equal to the superposition of the product terms of the deviations in each dimension. The second-order interaction matrix is ​​used to capture the coupling amplification effect when any two dimensions simultaneously deviate. When positional deviation and defect area, positional deviation and contour deformation, or defect area and contour deformation coexist pairwise, the interaction between any two dimensions is independent of the third dimension, and their combined deterioration effect is equal to the superposition of the corresponding two-dimensional deviation products. When there is no deviation in any dimension, the two-dimensional product term is automatically zero.

[0075] Next, the outer product of the preset reference vectors is calculated, which serves as the reference interaction matrix. This represents the coupling value when all dimensions are in the baseline state. Next, the second-order interaction matrix and the baseline interaction matrix are calculated. Difference measure between This reflects the combined amplification effect when any two-dimensional deviations exist simultaneously. The larger the norm square value (difference measure) of the difference in the second-order interaction matrix, the more significant the cooperative deviation of the current nut between each pair of dimensions, and the more severe the quality degradation.

[0076] Simultaneously, the minimum value among the three normalized eigenvalues ​​is taken as the higher-order coupling excitation value to capture the synergistic deterioration effect when deviations exist simultaneously in all three dimensions. When deviations exist simultaneously in the three dimensions of positional deviation, defect area, and contour deformation, they couple with each other through stress field and contact state to form a synergistic deterioration effect. Its strength is limited by the minimum normalized eigenvalue among the three, reflecting the physical constraint that the weakest link determines the ternary synergistic strength. When any dimension has no deviation, that is, the normalized eigenvalue of that dimension is 0, the synergistic coupling chain breaks at that link, the higher-order coupling excitation value is 0, and the synergistic effect is not activated.

[0077] The aforementioned second-order interactions and higher-order couplings are calculated independently, and are ultimately integrated into the defect degree calculation formula, jointly reflecting the complete multi-dimensional deviation deterioration effect from pairwise coupling to ternary synergy.

[0078] Based on this, the basic deviation metric, difference metric, and higher-order coupling excitation value of each nut are fused and calculated to obtain the nut. i Individual defect degree for: in, This represents the difference vector between the normalized features of each nut and the preset reference vector, reflecting the direction and magnitude of deviation of each dimension relative to the reference. Its square norm (basic deviation measure) is used to quantify the independent cumulative effect of deviations in each dimension.

[0079] in, This represents the preset second-order interaction influence coefficient, which characterizes the contribution weight of the two-dimensional deviation coupling effect to the defect degree. It is determined by statistical regression analysis of historical defect samples, and its value ranges from 0.3 to 0.8, reflecting the sensitivity of the process to multidimensional coupled defects. Let be the second-order interaction matrix of the current nut. Interaction matrix with the benchmark The norm square of the difference between the two dimensions is used to quantify the joint amplification effect when any two dimensional deviations exist simultaneously.

[0080] Wherein, k represents the preset high-order coupling sensitivity coefficient, which characterizes the exponential amplification intensity of the synergistic effect of deviations in three dimensions and above on the degree of defect. It is obtained by fitting the quality loss data under the scenario of coexistence of multi-dimensional defects, and the value ranges from 0.5 to 2.0, reflecting the tolerance of the process to multi-dimensional coupling. This represents the sum of the products of the eigenvalues ​​of any three dimensions in the normalized features of nut i, used to capture the synergistic deterioration effect when there are deviations in three or more dimensions simultaneously.

[0081] in, This represents the preset adaptive scaling factor, which is used to adaptively adjust the defect level according to the overall deviation level. The value range is determined by the process engineers based on actual production data. Normalized characteristics of nut i The L1 norm is used to adaptively scale the individual defect degree according to the overall deviation level.

[0082] In the above formula for calculating individual defect degree, the basic deviation metric reflects the independent cumulative effect of deviations in each dimension, the difference metric reflects the norm square of the difference between the second-order interaction matrix and the benchmark interaction matrix, and the higher-order coupling excitation value is the minimum of the three normalized eigenvalues. These three correspond to first-order independent terms, second-order pairwise coupling terms, and third-order ternary synergistic terms, respectively. They are combined additively during fusion to form a multi-level deviation metric system from low to high order. In this embodiment, the calculated individual defect degree integrates single-dimensional deviation information, second-order interactive coupling information, and higher-order synergistic coupling information. When multiple deviations exist simultaneously, the individual defect degree exhibits superlinear growth, reflecting the actual engineering law that the synergistic effect of defects is far greater than the independent superposition.

[0083] It should be noted that the above defect rate calculation is performed on an industrial computer. For a single inspection involving no more than 100 nuts, the calculation time for the entire process is no more than 500 milliseconds, which can meet the production line cycle time requirements.

[0084] Furthermore, the spatial distance between the nut and its adjacent nuts is obtained, and the neighborhood influence factor is calculated based on the individual defect degree of the adjacent nuts and the spatial distance. The closer the distance and the higher the defect rate of the neighboring nuts, the greater the impact on this nut. This is used to quantify the mutual interference risk between adjacent nuts on the carrier plate. Offset nuts may generate lateral extrusion force or material flow interference to adjacent nuts.

[0085] Specifically, the defect levels of adjacent nuts are weighted and summed using the reciprocal of the square of the spatial distance as the weight to obtain a neighborhood influence factor. This factor is used to quantify the mutual interference risk between adjacent nuts on the carrier plate. The closer the distance and the higher the defect level of the neighboring nuts, the greater the impact on the current nut. When the defect levels of adjacent nuts are generally high, the defect level of the current nut is appropriately amplified to reflect the uneven riveting force caused by the cumulative offset in a local area of ​​the download plate in a closely packed scenario. When all adjacent nuts are normal, this factor tends to zero.

[0086] Finally, the individual defect degree of the nut is fused with the corresponding neighborhood influence factor to obtain the defect degree of the nut. for: in, This represents the individual defect rate calculated above. This represents the neighborhood coupling coefficient, which characterizes the weight of neighborhood influence in the defect degree calculation; the default value is 0.3. This represents the neighborhood influence factor. Through the above process, it can be analyzed that if the defect degree of the surrounding nuts is generally high, the defect degree of this nut is slightly amplified, which may cause abnormal stress on this nut due to the offset of adjacent nuts; if the defect degree of the surrounding nuts is low, the defect degree of this nut is hardly affected.

[0087] In this embodiment, the calculated defect degree reflects both the overall quality status of the nut itself across multiple dimensions and the potential interference from adjacent nuts. The smaller the value, the healthier the overall condition of the nut. The defect degree is used as the quantitative basis for subsequent anomaly classification and diagnosis. The lower the defect degree, the closer it is to normal release; the higher the defect degree, the more it triggers the corresponding level of anomaly handling strategy, thereby achieving a complete quantitative judgment of each nut from independent quality assessment to group collaborative assessment.

[0088] The above process involves acquiring a global image of the carrier plate through a second vision station and extracting multi-dimensional feature parameters for each nut. A single inspection can simultaneously determine the presence or absence of a nut (missing nut detection), appearance quality (surface defect detection), and installation accuracy (positional misalignment and contour deformation detection). Compared to mechanical screening, which can only determine orientation, this process achieves a comprehensive quantitative assessment of nut quality. By using image recognition-based computer vision technology to calculate the defect degree, the inspection results from multiple dimensions are integrated into a comprehensive index, providing a continuous and quantifiable decision-making basis for subsequent graded handling.

[0089] S160, compare the defect level of the nut with the preset multi-level threshold, classify the nut into different abnormal levels according to the comparison result, and execute the corresponding handling strategy according to the abnormal level.

[0090] In this embodiment, the defect level of each nut is compared with a preset first threshold, a second threshold, and a third threshold. Based on the comparison results, each nut is classified into a normal level, a slightly abnormal level, a moderately abnormal level, or a severely abnormal level. For the normal level, the process proceeds normally to the riveting process. For the slightly abnormal level, the position compensation amount is calculated and fine-tuned before riveting. After compensation, the defect level calculation and level determination are re-executed. For the moderately abnormal level, the abnormal nut's number and characteristic parameter details are displayed on the touch screen, and the operator is required to manually confirm before releasing or rejecting it. For the severely abnormal level, an alarm signal is issued and all subsequent processes are locked, thereby implementing corresponding differentiated handling strategies according to different abnormal levels.

[0091] In one embodiment of this application, the defect level of the nut is compared with a preset multi-level threshold, and the nut is classified into different abnormality levels according to the comparison result. A corresponding handling strategy is then executed according to the abnormality level, including: When the defect rate of all nuts is less than or equal to the first threshold, it is judged as normal and the process proceeds normally to the alternation of double fixtures and riveting operation. When the defect degree of a nut is greater than the first threshold and less than or equal to the second threshold, and the relative deviation ratio of the nut is the only deviation type that exceeds the allowable range among all dimensions of deviation, it is judged as a minor abnormality level. The position compensation amount of the nut is calculated, and the position compensation is performed by the fine-tuning material picking mechanism before riveting. After the compensation is completed, the defect degree calculation and level judgment are re-executed. When the defect degree of a nut is greater than the second threshold and less than or equal to the third threshold, or the area ratio value is greater than the preset defect severity threshold, it is judged as a moderate abnormality level. The abnormal nut number and detailed feature parameters of each dimension are displayed on the touch screen, and the operator waits for manual confirmation before choosing to release or reject it. When the defect level of a nut exceeds the third threshold, or the contour deviation value exceeds the preset severe contour deviation threshold, it is judged as a severe abnormality level, an alarm signal is issued, and all subsequent processes are locked.

[0092] In one embodiment of this application, when the defect degree of all nuts is less than or equal to the first threshold, it indicates that the deviation of all nuts in each dimension is within an acceptable range, there is no single or coupled abnormality, and it is judged to be at the normal level. The process proceeds normally to the subsequent double fixture alternation and riveting operation.

[0093] In one embodiment of this application, when the defect degree of a nut is greater than a first threshold and less than or equal to a second threshold, and the relative deviation ratio of the nut is the only deviation type exceeding the allowable range among all dimensional deviations, it indicates that the nut only has a slight deviation in positional accuracy, while the quality indicators of other dimensions are normal, and it is judged to be at the minor abnormality level. At this time, the position compensation amount is calculated based on the difference between the actual coordinates and the target coordinates of the nut, and the position compensation of the nut station is performed by the fine-tuning material handling mechanism before riveting. After the compensation is completed, the defect degree calculation and level judgment are re-executed to confirm whether the compensation is effective.

[0094] Specifically, for positional deviations classified as minor anomalies, the jig's translation axis is driven to a preset fine-tuning station. The X-axis and Y-axis modules then move the unloading head above the nut's position. A Z-axis cylinder drives the unloading head downwards, applying lateral thrust to perform in-situ fine-tuning and correction of the nut without clamping it. This lateral thrust is controlled by a servo motor outputting torque corresponding to the position compensation amount. The thrust direction is from the nut's actual position to the target position, and the magnitude of the thrust is proportional to the positional deviation, with the proportionality coefficient calibrated experimentally.

[0095] During the fine-tuning process, the feeding head remains in contact with the nut but does not clamp it. The contact force does not exceed the static friction generated by the nut's own weight to avoid interference with adjacent placed nuts. If there are multiple nuts with positional deviations on the same fixture, the above-mentioned in-situ fine-tuning is performed sequentially in descending order of deviation. After completion, the global image acquisition and defect determination at the second vision station are re-executed. By utilizing lateral thrust to achieve nut fine-tuning based on the existing equipment structure, interference with adjacent nuts caused by re-feeding and unloading is avoided, ensuring that the compensation process does not damage other placed nuts.

[0096] In one embodiment of this application, when the defect degree of a nut is greater than a second threshold and less than or equal to a third threshold, or when the area ratio is greater than a preset defect severity threshold, it indicates that the nut has a relatively obvious quality problem or the severity of surface defects exceeds the tolerance range, and is judged as a moderate abnormality level. The abnormal nut's number and detailed characteristic parameters of each dimension are displayed on the touch screen. The operator manually confirms the information displayed and chooses to release or reject the nut. When releasing the nut, the riveting speed of the station where the nut is located will be reduced in the subsequent riveting process to reduce the impact force.

[0097] In one embodiment of this application, when the defect level of a nut exceeds a third threshold, or the contour deviation value exceeds a preset severe contour deviation threshold, it indicates that the nut has a serious quality defect or contour deformation that cannot guarantee the riveting quality, and is judged as a severe abnormality. An alarm signal is immediately issued, all subsequent processes are locked, the fixture is prohibited from entering the riveting process, and abnormality details are displayed on the touch screen to guide the operator in troubleshooting and handling.

[0098] The above process, by comparing the defect level with multi-level thresholds and classifying them into different abnormal levels, breaks away from the limitations of binary judgment in traditional schemes and achieves refined hierarchical management of abnormalities. Minor abnormalities are compensated and corrected without stopping the machine, moderate abnormalities prompt manual assistance in decision-making to balance quality and capacity, and severe abnormalities are immediately stopped to prevent defective products from flowing out. Thus, while maximizing the effective operating time of the equipment, the multi-level protection mechanism prevents defective nuts from flowing into the riveting process.

[0099] To verify the effectiveness of the defect degree calculation model of this application compared with the traditional linear weighting method, the applicant conducted comparative experiments on the same batch of mixed samples containing normal nuts, nuts with surface defects, misaligned nuts, and deformed nuts, using both the defect degree model of this application and the traditional linear weighting method. The experimental sample consisted of 200 nuts, of which, after manual calibration, were: 120 normal nuts, 25 nuts with surface scratches, 15 rusted nuts, 20 misaligned nuts, and 20 deformed nuts. The traditional linear weighting method used the same four-dimensional feature parameters as this application and calculated a comprehensive score by summing the results with equal weights. The judgment threshold was set when the comprehensive score exceeded a preset upper limit, indicating a failure.

[0100] The results of the comparative experiment are shown in Table 1: Table 1 Comparison of Experimental Results Experimental results show that, compared with the traditional linear weighting method, the defect degree model of this application improves the detection rate of defective nuts by approximately 23.75% and reduces the false alarm rate of normal nuts by approximately 12.5%, especially in the collaborative detection of multi-dimensional defects by approximately 41%. This is because the traditional linear weighting method can only reflect the independent cumulative effect of deviations in each dimension, and cannot capture the collaborative amplification effect when multiple dimensions of deviations coexist, leading to the missed detection of some minor multi-dimensional anomalies. The defect degree model of this application captures the collaborative deterioration effect between multi-dimensional deviations through a second-order interaction matrix, significantly enhancing the detection capability of multi-dimensional defects.

[0101] This technical solution establishes a spatial benchmark through equipment self-inspection and zeroing to ensure accurate positioning of each motion axis; it achieves automatic matching of task parameters through fixture in-situ detection and part number retrieval to prevent mixed material production; it pre-inspects empty fixtures at the first vision station to prevent damage from collisions between the material handling mechanism and residual hard objects; it acquires global images and extracts multi-dimensional feature parameters through the second vision station, performs difference and coupling analysis on the multi-dimensional feature parameters, and combines them with neighborhood influence factors to generate a defect degree, achieving a comprehensive quantitative assessment of omissions, deviations, and defects; by comparing the defect degree with multi-level thresholds and classifying abnormal levels, it performs differentiated handling to achieve hierarchical control of automatic compensation for minor abnormalities and immediate interception of serious abnormalities. While improving production efficiency and eliminating human safety hazards, it effectively prevents defective nuts from flowing into the riveting process, improving the efficiency and reliability of the industrial production process.

[0102] The following describes an embodiment of the nut positioning and installation control device for a copper busbar riveting machine according to this application, which can be used to execute the nut positioning and installation control method for a copper busbar riveting machine described in the above embodiments of this application. It is understood that the nut positioning and installation control device for a copper busbar riveting machine can be a computer program (including program code) running on a computer device. For example, the nut positioning and installation control device for a copper busbar riveting machine can install industrial application software or industrial control management software to achieve computer vision detection of industrial big data generated during the production process through an industrial cloud platform. The nut positioning and installation control device for a copper busbar riveting machine can be used to execute the corresponding steps in the method provided in the embodiments of this application. For details not disclosed in the embodiments of the nut positioning and installation control device for a copper busbar riveting machine of this application, please refer to the embodiments of the nut positioning and installation control method for a copper busbar riveting machine described above in this application.

[0103] Figure 4 A schematic diagram of a nut positioning and installation control device for a copper busbar riveting machine according to an embodiment of this application is shown. The nut positioning and installation control device for the copper busbar riveting machine in this embodiment can be equipped with nut positioning and installation control system software for the copper busbar riveting machine, industrial real-time control software, or manufacturing execution system (MES) software for realizing the above-mentioned nut positioning and installation industrial control functions, so as to realize the manufacturing process management of nut positioning and installation of the copper busbar riveting machine.

[0104] Reference Figure 4 As shown, a nut positioning and installation control device for a copper busbar riveting machine according to an embodiment of this application includes: The initialization module 310 is used to control each motion axis to perform a return-to-origin operation when the working air pressure of the copper busbar riveting machine is normal, so that each motion axis returns to the preset reference position. The acquisition module 320 is used to acquire the product part number after detecting that the fixture is in place, and retrieve the process parameter set corresponding to the product part number from the memory. The process parameter set includes the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension. The placement module 330 is used to determine that the fixture is in a clean state through a preset first visual station. Then, the material picking mechanism picks up nuts from the picking position in sequence and places them in the corresponding positions of the fixture according to the target coordinates in the process parameter set until the number of nuts placed reaches the total number of nuts. The detection module 340 is used to acquire a global image of the carrier plate after the material is placed at a preset second vision station, preprocess the global image to segment the contour information of the nut, and extract the multi-dimensional feature parameters of the nut from the contour information. The multi-dimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the ratio of the area of ​​the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. The calculation module 350 is used to perform difference analysis and coupling analysis on the relative deviation ratio, area ratio value and contour deviation value of the nuts, and to perform fusion calculation by combining the neighborhood influence factors between adjacent nuts to obtain the defect degree. The execution module 360 ​​is used to compare the defect level of the nut with the preset multi-level threshold, classify the nut into different abnormal levels according to the comparison result, and execute the corresponding handling strategy according to the abnormal level.

[0105] In this application, based on the aforementioned scheme, controlling each motion axis to perform a return-to-origin operation, so that each motion axis returns to a preset reference position, includes: first controlling the Z-axis to return to the origin, and then controlling the X-axis module and Y-axis module to return to the origin simultaneously; wherein, the X-axis and Y-axis are horizontal motion axes used to drive the picking head and unloading head to move horizontally to each picking position and unloading position; the Z-axis is a vertical motion axis; controlling the fixture translation axis to return to the origin, and then each axis waits in the standby position; wherein, the fixture translation axis is a horizontal motion axis independent of the X-axis, Y-axis, and Z-axis, used to drive the fixture to perform horizontal transport and transfer between the unloading position and the riveting position.

[0106] In this application, based on the aforementioned scheme, the material handling mechanism sequentially picks up nuts from the material handling position and places them sequentially on the corresponding workstations of the fixture according to the target coordinates in the process parameter set, until the number of nuts placed reaches the total number of nuts. This includes: the X-axis module and the Y-axis module moving to the first material handling position of the material handling position, the first Z-axis cylinder pressing down to perform the material handling action, and the cylinder resetting after the material handling is completed; subsequently, the X-axis module and the Y-axis module sequentially move to the second, third, and fourth material handling positions, and the Z-axis cylinders corresponding to each material handling position sequentially perform the material handling action. After the material handling is completed, the module resets. Once all materials are picked up, the X-axis module and Y-axis module simultaneously move to the first material placement position. The first Z-axis cylinder presses down to perform the material placement action and then resets. Subsequently, the X-axis module and Y-axis module move sequentially to the second, third, and fourth material placement positions. The Z-axis cylinders corresponding to each material placement position sequentially perform the material placement action and then reset. After completing one material handling cycle, the X-axis module and Y-axis module return to the material handling position and repeat the material handling control stage and the material placement control stage until the number of nuts placed on the fixture reaches the total number of nuts.

[0107] In this application, based on the aforementioned scheme, the step of preprocessing the global image to segment the nut's contour information and extracting the nut's multidimensional feature parameters from the contour information includes: registering the global image according to the target coordinates of each feeding station; performing binarization processing on the registered global image; extracting the nut's outer contour and inner hole contour through connected component analysis as contour information; and calculating the nut's multidimensional feature parameters based on the contour information.

[0108] In this application, based on the aforementioned scheme, the calculation of the multidimensional feature parameters of the nut based on the contour information includes: extracting the actual position of the nut based on the outer contour of the nut, and calculating the relative deviation ratio according to the degree of deviation between the actual position and the target position; delineating a projection area based on the outer contour of the nut, identifying defect areas within the projection area, and calculating the area ratio value according to the proportion of the defect area to the projection area; and calculating the contour deviation value based on the distances from multiple sampling points on the outer contour of the nut to the actual centroid of the nut, according to the degree of dispersion between the distances.

[0109] In this application, based on the aforementioned scheme, the step of performing difference analysis and coupling analysis on the relative deviation ratio, area ratio, and contour deviation value of the nuts, and combining this with the neighborhood influence factor between adjacent nuts to calculate the defect degree, includes: converting the relative deviation ratio, area ratio, and contour deviation value of each nut into normalized features through nonlinear mapping; calculating the basic deviation metric value of each nut based on the difference between the normalized features and a preset reference vector; constructing a second-order interaction matrix based on the normalized features of the nuts, and calculating the difference metric value between the second-order interaction matrix and the reference interaction matrix; using the minimum value in the normalized features as the higher-order coupling excitation value; fusing the basic deviation metric value, the difference metric value, and the higher-order coupling excitation value to calculate the individual defect degree of the nut; obtaining the spatial distance between the nut and its adjacent nuts, and calculating the neighborhood influence factor based on the individual defect degree of the adjacent nuts and the spatial distance; and fusing the individual defect degree of the nut with the corresponding neighborhood influence factor to obtain the defect degree of the nut.

[0110] In this application, based on the aforementioned scheme, the defect degree of the nut is compared with a preset multi-level threshold, and the nuts are classified into different abnormal levels according to the comparison results. A corresponding handling strategy is then executed according to the abnormal level, including: when the defect degree of all nuts is less than or equal to the first threshold, it is determined to be at a normal level, and the process proceeds normally to the alternating double fixture and riveting operation; when the defect degree of a nut is greater than the first threshold and less than or equal to the second threshold, and the relative deviation ratio of the nut is the only deviation type exceeding the allowable range among all dimensional deviations, it is determined to be at a slight abnormal level, and the position compensation of the nut is calculated. Before riveting, the material handling mechanism is used to perform position compensation. After compensation, the defect degree calculation and level judgment are re-executed. When the defect degree of a nut is greater than the second threshold and less than or equal to the third threshold, or the area ratio value is greater than the preset severe defect threshold, it is judged as a moderate abnormality level. The abnormal nut number and detailed feature parameters of each dimension are displayed on the touch screen, and the operator waits for manual confirmation before selecting to release or reject it. When the defect degree of a nut is greater than the third threshold, or the contour deviation value is greater than the preset severe contour deviation threshold, it is judged as a severe abnormality level, an alarm signal is issued and all subsequent processes are locked.

[0111] This technical solution establishes a spatial benchmark through equipment self-inspection and zeroing to ensure accurate positioning of each motion axis; it achieves automatic matching of task parameters through fixture in-situ detection and part number retrieval to prevent mixed material production; it pre-inspects empty fixtures at the first vision station to prevent damage from collisions between the material handling mechanism and residual hard objects; it acquires global images and extracts multi-dimensional feature parameters through the second vision station, performs difference and coupling analysis on the multi-dimensional feature parameters, and combines them with neighborhood influence factors to generate a defect degree, achieving a comprehensive quantitative assessment of omissions, deviations, and defects; by comparing the defect degree with multi-level thresholds and classifying abnormal levels, it performs differentiated handling to achieve hierarchical control of automatic compensation for minor abnormalities and immediate interception of serious abnormalities. While improving production efficiency and eliminating human safety hazards, it effectively prevents defective nuts from flowing into the riveting process, improving the efficiency and reliability of the industrial production process.

[0112] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the computer device of the present application is shown.

[0113] It should be noted that the computer system of the computer device in this embodiment is only an example and should not impose any limitations on the function and scope of use of the embodiments of this application.

[0114] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on a program stored in a read-only memory 402 or a program loaded from a storage section 408 into a random access memory 403, such as executing the nut positioning and installation control method for a copper busbar riveting machine described in the above embodiment. The random access memory 403 also stores various programs and data required for system operation, thereby realizing big data storage and big data management. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0115] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0116] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

[0117] It should be noted that the computer-readable storage medium shown in the embodiments of this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable storage medium other than a computer-readable storage medium, which can transmit, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The units involved in the embodiments of the application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not, in some cases, constitute a limitation on the units themselves.

[0120] One aspect of this application provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described above.

[0121] On the other hand, this application also provides a computer-readable storage medium, which may be included in the computer device described in the above embodiments; or it may exist independently and not assembled into the computer device. The computer-readable storage medium carries one or more programs, which, when executed by the computer device, cause the computer device to implement the nut positioning and installation control method for a copper busbar riveting machine described in the above embodiments.

[0122] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0123] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0124] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0125] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A nut positioning and installation control method for a copper bar press riveter, characterized by, include: When the working air pressure of the copper busbar riveting machine is normal, control each motion axis to perform a return-to-origin operation, so that each motion axis returns to the preset reference position. After the fixture is detected to be in place, the product part number is obtained, and the process parameter set corresponding to the product part number is retrieved from the memory. The process parameter set includes the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension. After determining that the fixture is in a clean state by the preset first visual station, the material picking mechanism picks up nuts from the picking position in sequence and places them on the corresponding station of the fixture in sequence according to the target coordinates of the process parameter set until the number of nuts placed reaches the total number of nuts. After the material is placed, a global image of the carrier plate is acquired at the preset second vision station. The outline information of the nut is segmented after the global image is preprocessed, and the multi-dimensional feature parameters of the nut are extracted from the outline information. The multidimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the ratio of the area of ​​the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. The relative deviation ratio, area ratio, and contour deviation of the nuts are analyzed for difference and coupling, and the defect degree is obtained by combining the neighborhood influence factors between adjacent nuts. The defect level of the nut is compared with a preset multi-level threshold. Based on the comparison result, the nut is divided into different abnormal levels, and the corresponding handling strategy is executed according to the abnormal level.

2. The nut positioning and installation control method for a copper busbar riveting machine according to claim 1, characterized in that, Control each motion axis to perform a homing operation, returning each motion axis to a preset reference position, including: First, control the Z-axis to return to the origin, then control the X-axis module and Y-axis module to return to the origin simultaneously; among them, the X-axis module and Y-axis module are horizontal motion axes, used to drive the picking head and discharging head to move horizontally to each picking position and discharging position; the Z-axis is the vertical motion axis; The control fixture translation axis returns to the origin, and then each axis waits in the standby position; among them, the fixture translation axis is a horizontal motion axis independent of the X-axis, Y-axis and Z-axis, used to drive the fixture to perform horizontal transport and transfer between the unloading position and the riveting position.

3. The nut positioning and installation control method for a copper busbar riveting machine according to claim 2, characterized in that, The material handling mechanism sequentially picks up nuts from the material handling position and places them sequentially on the corresponding workstations of the fixture according to the target coordinates in the process parameter set, until the number of nuts placed reaches the total number of nuts, including: The X-axis module and Y-axis module move to the first picking position of the picking station, and the first Z-axis cylinder presses down to perform the picking action. After the picking is completed, the cylinder resets. Then the X-axis module and Y-axis module move to the second, third and fourth picking positions in sequence. The Z-axis cylinders corresponding to each picking position perform the picking action in sequence and then reset. After all materials are picked up, the X-axis module and the Y-axis module move simultaneously to the first material feeding position. The first Z-axis cylinder presses down to perform the material feeding action and then resets. Subsequently, the X-axis module and the Y-axis module move sequentially to the second, third, and fourth material feeding positions. The Z-axis cylinders corresponding to each material feeding position perform the material feeding action sequentially and then reset. After completing one material handling cycle, the X-axis module and Y-axis module return to the material handling position to repeat the material handling control stage and the material handling control stage until the number of nuts placed on the fixture reaches the total number of nuts.

4. The nut positioning and installation control method for a copper busbar riveting machine according to claim 1, characterized in that, After preprocessing the global image, the contour information of the nut is segmented, and multidimensional feature parameters of the nut are extracted from the contour information, including: The global image is registered according to the target coordinates of each feeding station. The registered global image is then binarized. The outer contour and inner hole contour of the nut are extracted by connected component analysis as contour information. The multidimensional feature parameters of the nut are calculated based on the contour information.

5. The nut positioning and installation control method for a copper busbar riveting machine according to claim 4, characterized in that, The multidimensional feature parameters of the nut are calculated based on the contour information, including: The actual position of the nut is extracted based on its outer contour, and the relative deviation ratio is calculated based on the degree of deviation between the actual position and the target position. The projection area is defined based on the outer contour of the nut, the defect area within the projection area is identified, and the area ratio value is calculated based on the proportion of the defect area to the projection area. Based on the distances from multiple sampling points on the outer contour of the nut to the actual centroid of the nut, the contour deviation value is calculated according to the degree of dispersion between the distances.

6. The nut positioning and installation control method for a copper busbar riveting machine according to claim 1, characterized in that, The relative deviation ratio, area ratio, and contour deviation values ​​of the nuts are analyzed for difference and coupling, and the defect degree is obtained by combining the neighborhood influence factors between adjacent nuts. The relative deviation ratio, area ratio, and contour deviation value of each nut are converted into normalized features through nonlinear mapping. Based on the difference between the normalized features and the preset reference vector, calculate the basic deviation metric value of each nut; construct a second-order interaction matrix based on the normalized features of the nut, and calculate the difference metric value between the second-order interaction matrix and the reference interaction matrix; take the minimum value in the normalized features as the higher-order coupling excitation value. The individual defect degree of the nut is obtained by fusing the basic deviation metric, the difference metric, and the higher-order coupling excitation value. Obtain the spatial distance between the nut and its adjacent nuts, and calculate the neighborhood influence factor based on the individual defect degree of the adjacent nuts and the spatial distance; The defect degree of the nut is obtained by fusing the individual defect degree of the nut with the corresponding neighborhood influence factor.

7. The nut positioning and installation control method for a copper busbar riveting machine according to claim 1, characterized in that, The defect level of the nut is compared with a preset multi-level threshold. Based on the comparison result, the nut is classified into different abnormality levels, and a corresponding handling strategy is executed according to the abnormality level, including: When the defect rate of all nuts is less than or equal to the first threshold, it is judged as normal and the process proceeds normally to the alternation of double fixtures and riveting operation. When the defect degree of a nut is greater than the first threshold and less than or equal to the second threshold, and the relative deviation ratio of the nut is the only deviation type that exceeds the allowable range among all dimensions of deviation, it is judged as a minor abnormality level. The position compensation amount of the nut is calculated, and the position compensation is performed by the fine-tuning material picking mechanism before riveting. After the compensation is completed, the defect degree calculation and level judgment are re-executed. When the defect degree of a nut is greater than the second threshold and less than or equal to the third threshold, or the area ratio value is greater than the preset defect severity threshold, it is judged as a moderate abnormality level. The abnormal nut number and detailed feature parameters of each dimension are displayed on the touch screen, and the operator waits for manual confirmation before choosing to release or reject it. When the defect level of a nut exceeds the third threshold, or the contour deviation value exceeds the preset severe contour deviation threshold, it is judged as a severe abnormality level, an alarm signal is issued, and all subsequent processes are locked.

8. A nut positioning and installation control device for a copper busbar pressing and riveting machine, characterized in that, include: The initialization module is used to control each motion axis to perform a return-to-origin operation when the working air pressure of the copper busbar riveting machine is normal, so that each motion axis returns to the preset reference position. The acquisition module is used to acquire the product part number after detecting that the fixture is in place, and retrieve the process parameter set corresponding to the product part number from the memory. The process parameter set includes the total number of nuts, the target coordinates of each feeding station, the judgment threshold of each detection item, and the detection weight coefficient of each dimension. The placement module is used to determine that the fixture is in a clean state through a preset first visual station. Then, the material picking mechanism picks up nuts from the picking position in sequence and places them on the corresponding positions of the fixture according to the target coordinates in the process parameter set until the number of nuts placed reaches the total number of nuts. The detection module is used to acquire a global image of the carrier plate after the material is placed at a preset second vision station, preprocess the global image to segment the contour information of the nut, and extract the multi-dimensional feature parameters of the nut from the contour information. The multidimensional feature parameters include: the relative deviation ratio of the actual centroid coordinates to the target coordinates, the ratio of the area of ​​the surface defect region to the area of ​​the nut projection, and the contour deviation value of the outer contour relative to the standard circle. The calculation module is used to perform difference analysis and coupling analysis on the relative deviation ratio, area ratio value and contour deviation value of the nuts, and to perform fusion calculation by combining the neighborhood influence factors between adjacent nuts to obtain the defect degree; The execution module is used to compare the defect level of the nut with a preset multi-level threshold, classify the nut into different abnormal levels according to the comparison results, and execute the corresponding handling strategy according to the abnormal level.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the nut positioning and installation control method for a copper busbar riveting machine as described in any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the nut positioning and installation control method for a copper busbar riveting machine as described in any one of claims 1 to 7.

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