A pin positioning welding device for LED light emitting diode production

Abstract

The present invention relates to the technical field of LED welding production, and in particular to a pin positioning welding device for LED light-emitting diode production. The device comprises a welding table, a support frame is provided on the welding table, a transverse guide seat is provided on the support frame, a transverse threaded screw is rotatably connected to the transverse guide seat, a transverse slider is slidably connected to the threaded screw, and a first pulley is fixedly connected to one end of the threaded screw, a first driving motor is also installed on the transverse guide seat, a second pulley is fixedly connected to the rotating shaft of the first driving motor, and the first pulley and the second pulley are connected by belt transmission. The device significantly improves the welding accuracy and success rate, realizes automatic control, improves production efficiency and consistency, reduces production costs, and ensures the stability of product quality.

Description

Technical Field

[0001] The invention relates to the technical field of LED welding production, in particular to a pin positioning welding device for LED light emitting diode production. Background Art

[0002] With the rapid development of LED lighting technology, higher requirements are placed on the production efficiency and product quality of LED light-emitting diodes. Traditional LED pin positioning welding devices have problems such as low efficiency, poor precision, and easy errors, which make it difficult to meet the needs of large-scale production. In order to solve these problems, many automated LED pin positioning welding devices have emerged in recent years, but most of these devices use solutions with complex mechanical structures and unintelligent control systems, resulting in high costs, difficult maintenance, and poor adaptability.

[0003] At present, the LED pin positioning welding devices commonly available in the market have the following shortcomings: the existing devices often use multi-stage transmission mechanisms, such as screws, slide rails, etc., which lead to complex device structures, large volumes, difficult to control processing accuracy, and prone to mechanical wear and failure. Most of the existing devices use simple control systems, such as PLC control, which lack the ability to monitor and intelligently control the welding process in real time, making it difficult to improve welding accuracy and efficiency. In order to overcome the shortcomings of the existing technology, there is an urgent need for a new type of LED pin positioning welding device with a simple structure, intelligent control, and strong adaptability to improve LED production efficiency and product quality, reduce production costs, and meet market demand. Summary of the invention

[0004] The invention overcomes the shortcomings of the prior art and provides a pin positioning welding device for producing LED light emitting diodes.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is:

[0006] The first aspect of the present invention discloses a pin positioning welding device for LED light emitting diode production, comprising a welding table, a support frame is arranged on the welding table, a transverse guide seat is arranged on the support frame, a transverse threaded screw is rotatably connected to the transverse guide seat, a transverse slider is slidably connected to the threaded screw, and a first pulley is fixedly connected to one end of the threaded screw, a first driving motor is also installed on the transverse guide seat, a second pulley is fixedly connected to the rotating shaft of the first driving motor, and the first pulley and the second pulley are connected by a belt transmission;

[0007] A vertical guide seat is fixedly mounted on the horizontal slider, a vertical threaded screw is rotatably connected to the vertical guide seat, a vertical slider is slidably connected to the vertical threaded screw, a second drive motor is also mounted on the vertical guide seat, and a rotating shaft of the second drive motor is fixedly connected to the vertical threaded screw;

[0008] A mounting plate is fixedly mounted on the vertical slider, a guide rail is mounted on the mounting plate, a guide block is slidably connected to the guide rail, a fine-tuning cylinder is also mounted on the mounting plate, and the telescopic end of the fine-tuning cylinder is fixedly connected to the guide block; a clamping column is also mounted on the guide block, an L-shaped rod is clamped on the clamping column, and a welding head is fixedly mounted on the L-shaped rod.

[0009] Furthermore, in a preferred embodiment of the present invention, the welding head is driven to move by the first driving motor and the second driving motor to achieve a coarse positioning function; and the welding head is driven to move by the fine-tuning cylinder to achieve a fine positioning function.

[0010] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a controller, and the controller is communicatively connected with the first drive motor, the second drive motor and the fine-tuning cylinder.

[0011] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a CCD camera.

[0012] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a processor, and the processor is communicatively connected to the CCD camera.

[0013] The second aspect of the present invention discloses a control method for a pin positioning welding device for LED light emitting diode production, which is applied to any of the above-mentioned pin positioning welding devices for LED light emitting diode production, and comprises the following steps:

[0014] Draw a preset position and posture model diagram of the welding head at each time stamp during the welding process, and build a position and posture diagram database according to each preset position and posture model diagram;

[0015] Acquire an actual position and posture image of the welding head at a preset welding time node, and evaluate the position and posture of the welding head according to the actual position and posture image and in combination with the position and posture graph database;

[0016] If the position and posture of the welding head is in a normal state, the welding equipment is not regulated; if the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image;

[0017] If the LED pin welding working state is a scrap state, the welding device is controlled to stop welding the LED pin in the current processing process, and the LED pin in the current processing process is scrapped;

[0018] If the LED pin welding working condition is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing.

[0019] Furthermore, in a preferred embodiment of the present invention, a preset position and posture model diagram of the welding head at each time stamp during the welding process is drawn, and a position and posture diagram database is constructed according to each preset position and posture model diagram, specifically:

[0020] Obtaining a preset welding scheme for the LED pins, and obtaining a preset welding path for welding the LED pins according to the preset welding scheme;

[0021] Discretize the preset welding path, obtain the preset welding position node of the welding head at each time stamp, and obtain the coordinates of the preset welding position node of the welding head at each time stamp;

[0022] Acquire the size parameter information of the welding head, and draw the preset position posture model diagram of the welding head at each time stamp according to the size parameter information and the coordinates of each preset welding position node;

[0023] Constructing a graph database, dividing the graph database into a plurality of storage node spaces based on each timestamp, and assigning a corresponding time sequence label to each storage node space based on the time sequence information of each timestamp;

[0024] The preset position and posture model graphs of the welding head at each time stamp are divided and stored in corresponding storage node spaces in the graph database to generate a position and posture graph database.

[0025] Furthermore, in a preferred embodiment of the present invention, an actual position and posture image of the welding head is obtained at a preset welding time node, and the position and posture of the welding head is evaluated according to the actual position and posture image and in combination with the position and posture diagram database, specifically:

[0026] During the actual operation of the welding device, an actual position and posture image of the welding head is obtained at a preset welding time node, and an actual position and posture model diagram of the welding head at the preset welding time node is constructed according to the actual position and posture image;

[0027] and obtaining a timing tag of the preset welding time node, importing the timing tag of the preset welding time node into the position posture graph database, and obtaining a storage node space matching the timing tag of the preset welding time node;

[0028] Extracting a corresponding preset position posture model graph from the storage node space matching the timing label of the preset welding time node, and defining it as a preset position posture model graph corresponding to the welding head at the preset welding time node;

[0029] Introducing an ICP algorithm, and calculating the degree of overlap between the actual position and posture model diagram at a preset welding time node and the preset position and posture model diagram based on the ICP algorithm;

[0030] If the overlap degree is greater than a preset threshold, the position and posture of the welding head at the preset welding time node is marked as a normal state; if the overlap degree is not greater than the preset threshold, the position and posture of the welding head at the preset welding time node is marked as a drift state.

[0031] Furthermore, in a preferred embodiment of the present invention, if the position and posture of the welding head is in a drift state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image, specifically:

[0032] Obtaining a detection record book of LED pins, and obtaining scrap feature images corresponding to various scrapped LED pins according to the detection record book;

[0033] Construct a knowledge graph, and import the scrap feature images corresponding to various scrapped LED pins into the knowledge graph;

[0034] If the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the real-time working condition image is imported into the knowledge base;

[0035] Calculating the cosine similarity between the real-time working condition image and each waste characteristic image; and comparing the cosine similarity between the real-time working condition image and each waste characteristic image with a preset similarity threshold value;

[0036] If the cosine similarity between the real-time working condition image and each waste feature image is not greater than the preset similarity threshold, the LED pin welding working condition state is marked as a normal state;

[0037] If the cosine similarity between the real-time working condition image and a certain waste characteristic image is greater than a preset similarity threshold, the LED pin welding working condition state is marked as a waste state.

[0038] Furthermore, in a preferred embodiment of the present invention, if the LED pin welding working state is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing, specifically:

[0039] If the LED pin welding working condition is normal, the actual position posture model diagram and the preset position posture model diagram at the preset welding time node are obtained;

[0040] Rendering the actual position posture model diagram at the preset welding time node as a pure black model, and rendering the preset position posture model diagram at the preset welding time node as a pure white model;

[0041] Constructing a virtual pairing space based on the preset position and posture model graph, importing the actual position and posture model graph at the preset welding time node into the virtual pairing space for pairing processing, and outputting the position and posture model graph after pairing;

[0042] Obtaining the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram in the paired position posture model diagram respectively, and calculating the offset of the welding head according to the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram;

[0043] The model part that only exists in pure black or pure white in the position and posture model diagram after pairing is retained, and the model part that exists in both pure black and pure white in the position and posture model diagram after pairing is removed; after the processing is completed, a position deviation area model diagram of the welding head is obtained; and the offset direction of the welding head is determined according to the position deviation area model diagram;

[0044] After the position and posture of the welding head are corrected based on the offset amount and offset direction of the welding head, the welding device is controlled to continue welding the LED pins in the current processing.

[0045] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: the device adopts advanced position posture evaluation and correction technology to ensure that the welding head can accurately align with the preset position at each welding node, greatly improves the welding accuracy, and reduces the defective rate caused by inaccurate positioning. By acquiring the actual position posture image of the welding head in real time and comparing it with the preset position posture model, the system can quickly judge the state of the welding process and adjust the welding parameters accordingly, effectively preventing the position drift in the welding process and ensuring the consistency of welding quality. For the abnormal state of the welding condition, the system can automatically identify and mark it, and quickly locate the problem through matching analysis with the knowledge graph, reducing the complexity and time cost of manual troubleshooting and improving production efficiency. By calculating the overlap degree between the actual and preset position postures, and evaluating the cosine similarity, the system can accurately judge the welding condition of the LED pin, automatically mark the waste, avoid the generation of unqualified products, and improve the controllability of the production process and product quality. It can optimize the welding parameters, improve the performance and efficiency of the welding device for a long time, adapt to the welding requirements of different models of LEDs, and enhance the flexibility and adaptability of the production system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0047] Figure 1 It is a first overall structural schematic diagram of the device;

[0048] Figure 2 is a second overall structural schematic diagram of the device;

[0049] Figure 3 is a third overall structural schematic diagram of the device;

[0050] Figure 4 for Figure 3 The enlarged structural diagram at AA in the middle;

[0051] The reference numerals in the accompanying drawings are explained as follows: 101, welding table; 102, transverse guide seat; 103, transverse threaded screw; 104, transverse slider; 105, first pulley; 106, first drive motor; 107, second pulley; 108, vertical guide seat; 109, vertical threaded screw; 201, vertical slider; 202, second drive motor; 203, mounting plate; 204, guide rail; 205, guide block; 206, fine-tuning cylinder; 207, clamping column; 208, welding head. DETAILED DESCRIPTION

[0052] In order to more clearly understand the above-mentioned purposes, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the structures related to the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other without conflict.

[0053] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of the present application. In addition, the terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the invention, unless otherwise specified, "multiple" means two or more.

[0054] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0055] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thoroughly understood.

[0056] like Figure 1 , 2 As shown, the first aspect of the present invention discloses a pin positioning welding device for LED light emitting diode production, comprising a welding table 101, a support frame is arranged on the welding table 101, a transverse guide seat 102 is arranged on the support frame, a transverse threaded screw 103 is rotatably connected to the transverse guide seat 102, a transverse slider 104 is slidably connected to the threaded screw, and a first pulley 105 is fixedly connected to one end of the threaded screw, a first drive motor 106 is also installed on the transverse guide seat 102, a second pulley 107 is fixedly connected to the rotating shaft of the first drive motor 106, and the first pulley 105 and the second pulley 107 are connected by a belt transmission;

[0057] like Figure 3 , 4As shown, a vertical guide seat 108 is fixedly mounted on the horizontal slider 104, a vertical threaded screw 109 is rotatably connected to the vertical guide seat 108, a vertical slider 201 is slidably connected to the vertical threaded screw 109, and a second drive motor 202 is also mounted on the vertical guide seat 108, and a rotating shaft of the second drive motor 202 is fixedly connected to the vertical threaded screw 109;

[0058] A mounting plate 203 is fixedly mounted on the vertical slider 201, a guide rail 204 is mounted on the mounting plate 203, a guide block 205 is slidably connected to the guide rail 204, a fine-tuning cylinder 206 is also mounted on the mounting plate 203, the telescopic end of the fine-tuning cylinder 206 is fixedly connected to the guide block 205; a clamping column 207 is also mounted on the guide block 205, an L-shaped rod is clamped on the clamping column 207, and a welding head 208 is fixedly mounted on the L-shaped rod.

[0059] Furthermore, in a preferred embodiment of the present invention, the welding head 208 is driven to move by the first driving motor 106 and the second driving motor 202 to achieve a coarse positioning function; and the welding head 208 is driven to move by the fine-tuning cylinder 206 to achieve a fine positioning function.

[0060] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a controller, and the controller is communicatively connected with the first drive motor 106 , the second drive motor 202 , and the fine-tuning cylinder 206 .

[0061] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a CCD camera.

[0062] Furthermore, in a preferred embodiment of the present invention, the welding device also includes a processor, and the processor is communicatively connected to the CCD camera.

[0063] It should be noted that the coordinates of each pre-set welding position of the LED light-emitting diode are obtained, and these coordinates are based on the production design drawing or the results of the previous processing steps. After receiving the coordinate information, the controller controls the first drive motor 106 and the second drive motor 202 to start working. The first drive motor 106 drives the horizontal threaded screw 103 to rotate, and the horizontal slider 104 slides along the horizontal guide seat 102 to achieve movement in the X-axis direction; the second drive motor 202 drives the vertical threaded screw 109 to rotate, and the vertical slider 201 slides along the vertical guide seat 108 to achieve movement in the Y-axis direction, and the belt transmission system is used to ensure the stability and accuracy of the movement. When the horizontal slider 104 and the vertical slider 201 move to the predetermined position, the welding head 208 is roughly located near the expected welding position of the LED light-emitting diode, and the rough positioning is completed. This process can effectively improve the welding work efficiency. On the basis of rough positioning, the controller starts the fine-tuning cylinder 206, and the fine-tuning cylinder 206 makes a slight adjustment to the welding head 208 through telescopic action to achieve a more accurate welding position, improve welding accuracy, and thus ensure welding quality. The positional relationship between the welding head 208 and the LED pin is monitored in real time by the CCD camera, and the fine-tuning cylinder 206 is adjusted according to the feedback information until the welding head 208 is completely aligned with the pin to complete the precise positioning. After the precise positioning is completed, the welding head 208 is accurately aligned with the LED pin and is ready for welding. The controller sends a command to start the welding process. The welding head 208 contacts the pin and applies heat, and the pin is melted and a solder joint is formed through a welding process (such as hot pressing, laser welding, etc.), completing the welding operation.

[0064] In addition, during or after welding, the CCD camera automatically performs quality inspections to assess whether the welding results meet the standards. The inspection content includes the size, shape, position, quality, etc. of the solder joints.

[0065] The system records the data of each welding operation, including welding time, welding temperature, welding pressure, welding point quality evaluation, etc., to provide a basis for subsequent analysis and optimization. If welding quality problems or equipment failures are detected, the system will automatically trigger an alarm mechanism.

[0066] In summary, through the above control workflow, the pin positioning welding device for LED light-emitting diode production can achieve: through the double-layer positioning mechanism of coarse positioning and fine positioning, it is ensured that the welding head 208 can accurately align with the pin of the LED light-emitting diode, which significantly improves the welding accuracy and success rate; the automated control process reduces manual intervention, improves production efficiency and consistency, reduces production costs, and automated control reduces errors caused by human operation, ensuring the stability of product quality. By recording the data of each welding operation, it is convenient for quality control and production management, and helps to track problems and continuously improve.

[0067] The second aspect of the present invention discloses a control method for a pin positioning welding device for LED light emitting diode production, which is applied to any of the above-mentioned pin positioning welding devices for LED light emitting diode production, and comprises the following steps:

[0068] Draw a preset position and posture model diagram of the welding head at each time stamp during the welding process, and build a position and posture diagram database according to each preset position and posture model diagram;

[0069] Acquire an actual position and posture image of the welding head at a preset welding time node, and evaluate the position and posture of the welding head according to the actual position and posture image and in combination with the position and posture graph database;

[0070] If the position and posture of the welding head is in a normal state, the welding equipment is not regulated; if the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image;

[0071] If the LED pin welding working state is a scrap state, the welding device is controlled to stop welding the LED pin in the current processing process, and the LED pin in the current processing process is scrapped;

[0072] If the LED pin welding working condition is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing.

[0073] It should be noted that the preset position and posture model diagram of the welding head at each time point during the welding process is drawn by industrial three-dimensional software such as CAD and UG. This step is based on the precise planning of the position and posture of the welding head in the ideal state, which provides a basis for subsequent evaluation and adjustment. Then, the system builds a position and posture diagram database based on these preset position and posture model diagrams as a basis for evaluation and decision-making. Next, at the preset welding time node, the system obtains the actual position and posture image of the welding head. By comparing the actual position and posture image with the preset model in the database, the system can evaluate whether the position of the welding head deviates from the expected. If the welding head is in a normal state, that is, its position and posture meet the preset standard, the system will not perform any control processing to keep the current welding process undisturbed. However, if it is detected that the welding head is in a drifting state, that is, its position and posture deviate from the preset standard, the system will take further action: obtain real-time working condition images of the welding area to fully understand the current welding environment and conditions. By analyzing these real-time images, the system can evaluate the welding working condition of the LED pin. If the evaluation result shows that the welding condition is a waste state, that is, the welding quality of the LED pin cannot meet the standard, the system will immediately instruct the welding device to stop the current welding process to prevent unqualified products from flowing into the next process, and at the same time, the current LED pin will be scrapped to avoid the use of unqualified parts in subsequent processes and to avoid the continued welding of workpieces that are already waste, effectively saving processing costs. On the contrary, if the evaluation result shows that the welding condition of the LED pin is normal, that is, the welding quality meets the standard, the system will make necessary corrections to the position and posture of the welding head to ensure its stability and accuracy in the future welding process. After the correction, the system will continue to control the welding device to perform welding processing on the LED pin in the current processing process to ensure the continuity and efficiency of the entire production process. In summary, through precise preset, real-time monitoring and evaluation, and flexible response mechanism, the quality control level of the LED pin welding process is effectively improved, the scrap rate is reduced, and the production efficiency and product quality are improved.

[0074] Furthermore, in a preferred embodiment of the present invention, a preset position and posture model diagram of the welding head at each time stamp during the welding process is drawn, and a position and posture diagram database is constructed according to each preset position and posture model diagram, specifically:

[0075] Obtaining a preset welding scheme for the LED pins, and obtaining a preset welding path for welding the LED pins according to the preset welding scheme;

[0076] Discretize the preset welding path, obtain the preset welding position node of the welding head at each time stamp, and obtain the coordinates of the preset welding position node of the welding head at each time stamp;

[0077] Acquire the size parameter information of the welding head, and draw the preset position posture model diagram of the welding head at each time stamp according to the size parameter information and the coordinates of each preset welding position node;

[0078] Constructing a graph database, dividing the graph database into a plurality of storage node spaces based on each timestamp, and assigning a corresponding time sequence label to each storage node space based on the time sequence information of each timestamp;

[0079] The preset position and posture model graphs of the welding head at each time stamp are divided and stored in corresponding storage node spaces in the graph database to generate a position and posture graph database.

[0080] It should be noted that the ideal welding path is determined by obtaining the preset welding scheme of the LED pin. This preset welding scheme contains the ideal steps and sequence for welding the LED pin, providing a basis for subsequent precise control. The preset welding scheme is prepared in advance by relevant technical personnel. Next, the system discretizes the preset welding path and decomposes the entire welding process into a series of welding position nodes at specific time points. Each node contains the precise position and posture information of the welding head, including coordinate data. In this way, the system can record and track in detail the motion trajectory and posture changes of the welding head throughout the welding process. Then, the system uses the size parameter information of the welding head and the coordinate data of each preset welding position node to draw the preset position posture model diagram of the welding head at each time stamp. These model diagrams provide a visual representation of the expected position and posture of the welding head at different stages, which helps to understand the dynamic characteristics of the welding process. Next, a graph database is constructed (no data is stored at this time), and these position posture model diagrams are organized and stored according to timestamps. Each timestamp corresponds to a storage node space, which ensures the orderliness and traceability of the data. In addition, the system also assigns corresponding time series labels to each storage node space to facilitate quick search and identification of welding process data within a specific time period. Finally, the system stores the preset position and posture model diagram of the welding head at each timestamp in the corresponding storage node space, and generates a position and posture diagram database. This database contains not only static information of the welding process (such as expected position and posture), but also dynamic information (such as time series and correlation), providing rich data resources for subsequent analysis, monitoring and optimization. Through this series of steps, the system can achieve refined management and control of the welding process, effectively improve welding quality and production efficiency, and reduce human errors and scrap rates.

[0081] Furthermore, in a preferred embodiment of the present invention, an actual position and posture image of the welding head is obtained at a preset welding time node, and the position and posture of the welding head is evaluated according to the actual position and posture image and in combination with the position and posture diagram database, specifically:

[0082] During the actual operation of the welding device, an actual position and posture image of the welding head is obtained at a preset welding time node, and an actual position and posture model diagram of the welding head at the preset welding time node is constructed according to the actual position and posture image;

[0083] and obtaining a timing tag of the preset welding time node, importing the timing tag of the preset welding time node into the position posture graph database, and obtaining a storage node space matching the timing tag of the preset welding time node;

[0084] Extracting a corresponding preset position posture model graph from the storage node space matching the timing label of the preset welding time node, and defining it as a preset position posture model graph corresponding to the welding head at the preset welding time node;

[0085] Introducing an ICP algorithm, and calculating the degree of overlap between the actual position and posture model diagram at a preset welding time node and the preset position and posture model diagram based on the ICP algorithm;

[0086] If the overlap degree is greater than a preset threshold, the position and posture of the welding head at the preset welding time node is marked as a normal state; if the overlap degree is not greater than the preset threshold, the position and posture of the welding head at the preset welding time node is marked as a drift state.

[0087] It should be noted that, first, the actual position and posture images of the welding head are captured at the preset welding time node, and then, the actual position and posture model graph is constructed based on these images, which is a digital representation of the real position and posture of the welding head at a specific moment. Next, the system will obtain the time series label related to the current time node and match it with the label in the position and posture graph database. In this way, the system can locate the data storage space corresponding to the current time node, and extract the preset position and posture model graph from this space, that is, the ideal position and posture model that the welding head should have at this time node. In order to evaluate the degree of match between the actual position and posture and the preset position and posture, the ICP (Iterative Closest Point Matching) algorithm is introduced. The ICP algorithm calculates the degree of overlap between the two models by iteratively matching two point sets and minimizing the distance between them. If the calculated overlap exceeds the preset threshold, it means that the position and posture of the welding head at this time node are highly consistent with the preset target, so it is marked as "normal state". On the contrary, if the overlap is lower than the threshold, it means that the position and posture of the welding head have deviated and is marked as "drift state". The method can monitor the welding process in real time, and promptly detect and correct the position and posture deviation of the welding head, thereby ensuring the welding quality and improving the production efficiency and consistency of product quality.

[0088] Furthermore, in a preferred embodiment of the present invention, if the position and posture of the welding head is in a drift state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image, specifically:

[0089] Obtaining a detection record book of LED pins, and obtaining scrap feature images corresponding to various scrapped LED pins according to the detection record book;

[0090] Construct a knowledge graph, and import the scrap feature images corresponding to various scrapped LED pins into the knowledge graph;

[0091] If the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the real-time working condition image is imported into the knowledge base;

[0092] Calculating the cosine similarity between the real-time working condition image and each waste characteristic image; and comparing the cosine similarity between the real-time working condition image and each waste characteristic image with a preset similarity threshold value;

[0093] If the cosine similarity between the real-time working condition image and each waste feature image is not greater than the preset similarity threshold, the LED pin welding working condition state is marked as a normal state;

[0094] If the cosine similarity between the real-time working condition image and a certain waste characteristic image is greater than a preset similarity threshold, the LED pin welding working condition state is marked as a waste state.

[0095] The LED pin inspection record book is a document or electronic database used to record and manage the inspection results of the LED pins during the production process.

[0096] It should be noted that, first, a knowledge graph is established to store the scrap feature images of various scrapped LED pins. These scrap feature images contain various abnormal conditions that lead to the scrapping of LED pins, such as size deviation, welding defects, etc. By constructing such a knowledge graph, the system can effectively classify and summarize abnormal conditions. When it is detected that the position and posture of the welding head is in a drift state, that is, the welding head fails to weld accurately according to the preset path, the system will obtain the real-time working condition image of the welding area. The real-time working condition image is imported into the knowledge graph and compared with the stored scrap feature image. By calculating the cosine similarity between the real-time working condition image and each scrap feature image, the similarity between the two in the feature space can be measured. Cosine similarity is a measurement method for measuring the cosine value of the angle between vectors, which is suitable for comparing the similarity of high-dimensional data such as images. The cosine similarity between the real-time working condition image and all scrap feature images is compared and compared with the preset similarity threshold. If the cosine similarity between all real-time working condition images and scrap feature images is less than or equal to the preset threshold, it means that the current welding condition does not show obvious abnormal characteristics, so the LED pin welding condition status is marked as "normal state". However, if the cosine similarity between a real-time working condition image and a scrap feature image is greater than the preset threshold, this indicates that the current welding condition has a high similarity with the known scrap features, which may mean that there are potential welding problems or defects, so the LED pin welding condition status is marked as "scrap state". Through this method, the system can evaluate the welding condition status of the LED pin in real time and automatically, and promptly discover and prevent possible quality problems.

[0097] Furthermore, in a preferred embodiment of the present invention, if the LED pin welding working state is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing, specifically:

[0098] If the LED pin welding working condition is normal, the actual position posture model diagram and the preset position posture model diagram at the preset welding time node are obtained;

[0099] Rendering the actual position posture model diagram at the preset welding time node as a pure black model, and rendering the preset position posture model diagram at the preset welding time node as a pure white model;

[0100] Constructing a virtual pairing space based on the preset position and posture model graph, importing the actual position and posture model graph at the preset welding time node into the virtual pairing space for pairing processing, and outputting the position and posture model graph after pairing;

[0101] Obtaining the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram in the paired position posture model diagram respectively, and calculating the offset of the welding head according to the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram;

[0102] The model part that only exists in pure black or pure white in the position and posture model diagram after pairing is retained, and the model part that exists in both pure black and pure white in the position and posture model diagram after pairing is removed; after the processing is completed, a position deviation area model diagram of the welding head is obtained; and the offset direction of the welding head is determined according to the position deviation area model diagram;

[0103] After the position and posture of the welding head are corrected based on the offset amount and offset direction of the welding head, the welding device is controlled to continue welding the LED pins in the current processing.

[0104] It should be noted that, first, when the welding working condition of the LED pin is evaluated as normal, the actual position posture model diagram and the preset position posture model diagram of the preset welding time node are obtained. The actual position posture model diagram reflects the real position and posture of the current welding head at the time node, while the preset position posture model diagram is the position and posture that the welding head should reach under ideal conditions. Then, the actual position posture model diagram is rendered as pure black, and the preset position posture model diagram is rendered as pure white to form a sharp contrast. The purpose of this is to make it easier to identify the difference area between the actual position and the preset position. Then, the system constructs a virtual pairing space based on the preset position posture model diagram, and imports the actual position posture model diagram into this space for pairing processing. After pairing processing, a paired position posture model diagram that integrates the actual position and preset position information is obtained. In the paired position and posture model diagram, the system obtains the position coordinates of the welding contact points of the welding head in the actual position and posture model diagram and the preset position and posture model diagram respectively, and calculates the posture offset of the welding head relative to the preset position based on these coordinates. Subsequently, the system will filter out the model parts with only pure black or pure white in the paired position and posture model diagram, which represent the areas where the actual position is completely mismatched or completely matched with the preset position. The model parts with both pure black and pure white are eliminated because they represent unclear areas of position and posture. After processing, the position deviation area model diagram of the welding head is obtained, and the direction and range that need to be adjusted are further clarified. Finally, the offset direction and offset of the welding head are determined according to the position deviation area model diagram, and the system corrects the position and posture of the welding head. The corrected position and posture of the welding head will be closer to the preset ideal state, thereby improving the welding quality. After the correction processing is completed, the system controls the welding device to continue welding the LED pins in the current processing process. Through this series of steps, the system can monitor and adjust the position and posture of the welding head in real time while ensuring the normal welding conditions, effectively improving the welding accuracy and product quality.

[0105] In summary, this device adopts advanced position and posture evaluation and correction technology to ensure that the welding head can accurately align with the preset position at each welding node, greatly improve the welding accuracy, and reduce the defective rate caused by inaccurate positioning. By obtaining the actual position and posture image of the welding head in real time and comparing it with the preset position and posture model, the system can quickly determine the state of the welding process and adjust the welding parameters accordingly, effectively preventing the position drift during the welding process and ensuring the consistency of welding quality. For abnormal conditions of welding conditions, the system can automatically identify and mark them, and quickly locate the problem through matching analysis with the knowledge graph, reducing the complexity and time cost of manual troubleshooting and improving production efficiency. By calculating the degree of overlap between the actual and preset position and posture, and evaluating the cosine similarity, the system can accurately determine the welding condition of the LED pin, automatically mark the waste, avoid the production of unqualified products, and improve the controllability of the production process and product quality. It can optimize welding parameters, improve the performance and efficiency of welding devices in the long term, adapt to the welding needs of different types of LEDs, and enhance the flexibility and adaptability of the production system. In general, the pin positioning welding device and control method for LED light-emitting diode production not only greatly improves production efficiency and product quality, but also optimizes the production process and reduces operating costs, providing strong technical support for the high-quality development of the LED industry.

[0106] In addition, the control method may further include the following steps:

[0107] Obtaining a work log of the welding device, and obtaining a paralysis period when various operation paralysis failures occur during the operation of the welding device according to the work log;

[0108] Obtaining historical characteristic parameters corresponding to the welding device during the paralysis period, which are defined as paralysis characteristic parameters; and obtaining historical characteristic parameters corresponding to the welding device in a preset time period before various operation paralysis failures occur, which are defined as pre-paralysis characteristic parameters;

[0109] A Bayesian network model is introduced, the characteristic parameters before paralysis are used as the first independent node and the characteristic parameters during paralysis are used as the second independent node; a network topology diagram is generated according to the first independent node and the second independent node;

[0110] Obtaining an adjacency matrix between each first independent node and each second independent node according to the network topology structure diagram, importing the adjacency matrix into the Bayesian network model for structural learning, and outputting a Bayesian network prediction model after model parameters meet preset requirements;

[0111] During the actual working process of the welding equipment, actual characteristic parameters of the welding equipment within a preset time period are obtained, and the actual characteristic parameters of the welding equipment within the preset time period are imported into the Bayesian network prediction model for prediction, so as to obtain the paralysis probability value of the welding equipment at the current time node;

[0112] If the paralysis probability value is greater than a preset probability threshold, the welding equipment is controlled to stop production and an early warning message is generated;

[0113] The characteristic parameters include but are not limited to noise frequency, motor speed, current and voltage fluctuation amplitude.

[0114] It should be noted that, first, the work log of the welding device during operation is obtained to identify the specific period (i.e., paralysis period) during the operation paralysis fault. At the same time, the historical characteristic parameters (pre-paralysis characteristic parameters) within a certain time range before these paralysis periods, as well as the specific characteristic parameters in the paralysis period (paralysis characteristic parameters) are collected. Using the collected data, the Bayesian network model is introduced. Here, the pre-paralysis characteristic parameters are regarded as the first independent node, and the paralysis characteristic parameters are regarded as the second independent node. By analyzing the relationship between these two types of characteristic parameters, a network topology structure diagram is constructed to form a graphical model representing the correlation between different characteristic parameters. By analyzing the network topology structure diagram, the adjacency matrix between each first independent node and the second independent node is obtained. The matrix is ​​input into the Bayesian network model for structural learning, and the model parameters are continuously adjusted until the preset learning accuracy or stability requirements are met. Finally, a Bayesian network prediction model that can accurately predict the occurrence of faults is output.

[0115] During the actual operation of the welding equipment, the system will collect the actual characteristic parameters within the preset time period in real time. These actual parameters are input into the trained Bayesian network prediction model to predict the probability value of equipment failure (paralysis probability value) at the current moment. If the calculated paralysis probability value exceeds the preset threshold, the system will immediately control the welding equipment to stop production and generate corresponding early warning information. This helps to timely discover and deal with potential faults and avoid greater losses when the equipment is paralyzed. By analyzing the correlation between historical data and characteristic parameters, the accuracy of equipment failure prediction is improved. Predicting possible faults in advance allows maintenance work to be carried out before the fault actually occurs, reducing the time and cost of production interruption. Real-time collection of equipment status information and rapid response to fault warnings improve the stability and efficiency of the production system.

[0116] The above is based on the ideal embodiment of the present invention, and its description is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

Claims

1. A control method for a pin positioning welding device for LED light emitting diode production, characterized in that: The pin positioning welding device comprises a welding table, a support frame is arranged on the welding table, a transverse guide seat is arranged on the support frame, a transverse threaded screw is rotatably connected to the transverse guide seat, a transverse slider is slidably connected to the threaded screw, and a first pulley is fixedly connected to one end of the threaded screw, a first driving motor is also installed on the transverse guide seat, a second pulley is fixedly connected to the rotating shaft of the first driving motor, and the first pulley and the second pulley are connected through a belt transmission; A vertical guide seat is fixedly mounted on the horizontal slider, a vertical threaded screw is rotatably connected to the vertical guide seat, a vertical slider is slidably connected to the vertical threaded screw, a second drive motor is also mounted on the vertical guide seat, and a rotating shaft of the second drive motor is fixedly connected to the vertical threaded screw; A mounting plate is fixedly mounted on the vertical slider, a guide rail is mounted on the mounting plate, a guide block is slidably connected to the guide rail, a fine-tuning cylinder is also mounted on the mounting plate, and the telescopic end of the fine-tuning cylinder is fixedly connected to the guide block; a clamping column is also mounted on the guide block, an L-shaped rod is clamped on the clamping column, and a welding head is fixedly mounted on the L-shaped rod; The control method comprises the following steps: Draw a preset position and posture model diagram of the welding head at each time stamp during the welding process, and build a position and posture diagram database according to each preset position and posture model diagram; Acquire an actual position and posture image of the welding head at a preset welding time node, and evaluate the position and posture of the welding head according to the actual position and posture image and in combination with the position and posture graph database; If the position and posture of the welding head is in a normal state, the welding equipment is not regulated; if the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image; If the LED pin welding working condition is a scrap state, the welding device is controlled to stop welding the LED pin in the current processing process, and the LED pin in the current processing process is scrapped; If the LED pin welding working condition is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing; Among them, the actual position and posture image of the welding head is obtained at the preset welding time node, and the position and posture of the welding head is evaluated according to the actual position and posture image and combined with the position and posture map database, specifically: During the actual operation of the welding device, an actual position and posture image of the welding head is obtained at a preset welding time node, and an actual position and posture model diagram of the welding head at the preset welding time node is constructed according to the actual position and posture image; and obtaining a timing tag of the preset welding time node, importing the timing tag of the preset welding time node into the position posture graph database, and obtaining a storage node space matching the timing tag of the preset welding time node; Extracting a corresponding preset position posture model graph from the storage node space matching the timing label of the preset welding time node, and defining it as a preset position posture model graph corresponding to the welding head at the preset welding time node; Introducing an ICP algorithm, and calculating the degree of overlap between the actual position and posture model diagram at a preset welding time node and the preset position and posture model diagram based on the ICP algorithm; If the overlap degree is greater than a preset threshold, the position and posture of the welding head at the preset welding time node is marked as a normal state; if the overlap degree is not greater than the preset threshold, the position and posture of the welding head at the preset welding time node is marked as a drift state; If the welding head position and posture is in a drift state, a real-time working condition image of the welding area is obtained, and the welding working condition of the LED pin is evaluated according to the real-time working condition image, specifically: Obtaining a detection record book of LED pins, and obtaining scrap feature images corresponding to various scrapped LED pins according to the detection record book; Construct a knowledge graph, and import the scrap feature images corresponding to various scrapped LED pins into the knowledge graph; If the position and posture of the welding head is in a drifting state, a real-time working condition image of the welding area is obtained, and the real-time working condition image is imported into the knowledge base; Calculating the cosine similarity between the real-time working condition image and each waste characteristic image; and comparing the cosine similarity between the real-time working condition image and each waste characteristic image with a preset similarity threshold value; If the cosine similarity between the real-time working condition image and each waste feature image is not greater than the preset similarity threshold, the LED pin welding working condition state is marked as a normal state; If the cosine similarity between the real-time working condition image and a certain waste characteristic image is greater than a preset similarity threshold, the LED pin welding working condition state is marked as a waste state; If the LED pin welding working condition is normal, the position and posture of the welding head are corrected and then the welding device is controlled to continue welding the LED pin in the current processing, specifically: If the LED pin welding working condition is normal, the actual position posture model diagram and the preset position posture model diagram at the preset welding time node are obtained; Rendering the actual position posture model diagram at the preset welding time node as a pure black model, and rendering the preset position posture model diagram at the preset welding time node as a pure white model; Constructing a virtual pairing space based on the preset position and posture model graph, importing the actual position and posture model graph at the preset welding time node into the virtual pairing space for pairing processing, and outputting the position and posture model graph after pairing; Obtaining the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram in the paired position posture model diagram respectively, and calculating the offset of the welding head according to the position coordinates of the welding contact points of the welding head in the actual position posture model diagram and the preset position posture model diagram; The model part that only exists in pure black or pure white in the position and posture model diagram after pairing is retained, and the model part that exists in both pure black and pure white in the position and posture model diagram after pairing is removed; after the processing is completed, a position deviation area model diagram of the welding head is obtained; and the offset direction of the welding head is determined according to the position deviation area model diagram; After the position and posture of the welding head are corrected based on the offset amount and offset direction of the welding head, the welding device is controlled to continue welding the LED pins in the current processing.

2. The control method of a pin positioning welding device for LED light emitting diode production according to claim 1, characterized in that: The welding head is driven to move by the first driving motor and the second driving motor to realize the rough positioning function; the welding head is driven to move by the fine adjustment cylinder to realize the fine positioning function.

3. The control method of a pin positioning welding device for LED light emitting diode production according to claim 1, characterized in that: The welding device also includes a controller, which is communicatively connected with the first drive motor, the second drive motor and the fine-tuning cylinder.

4. The control method of a pin positioning welding device for LED light emitting diode production according to claim 1, characterized in that: The welding device also includes a CCD camera.

5. The control method of a pin positioning welding device for LED light emitting diode production according to claim 4, characterized in that: The welding device also includes a processor, and the processor is communicatively connected with the CCD camera.

6. The control method of a pin positioning welding device for LED light emitting diode production according to claim 1, characterized in that: Draw the preset position and posture model diagram of the welding head at each time stamp during the welding process, and build a position and posture diagram database based on each preset position and posture model diagram, specifically: Obtaining a preset welding scheme for the LED pins, and obtaining a preset welding path for welding the LED pins according to the preset welding scheme; Discretize the preset welding path, obtain the preset welding position node of the welding head at each time stamp, and obtain the coordinates of the preset welding position node of the welding head at each time stamp; Acquire the size parameter information of the welding head, and draw the preset position posture model diagram of the welding head at each time stamp according to the size parameter information and the coordinates of each preset welding position node; Constructing a graph database, dividing the graph database into a plurality of storage node spaces based on each timestamp, and assigning a corresponding time sequence label to each storage node space based on the time sequence information of each timestamp; The preset position and posture model graphs of the welding head at each time stamp are divided and stored in corresponding storage node spaces in the graph database to generate a position and posture graph database.

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