Fuse precision welding method and device

Abstract

The invention relates to the technical field of fuse production, and particularly discloses a fuse precision welding method and equipment, which are characterized in that welding parameters are adaptively set, laser-micro resistance hybrid welding is performed, and closed-loop control of real-time quality detection is performed. The defects that in the prior art, due to the fact that welding parameters are fixed, the technology adaptability is poor, welding heat damage is remarkable, and manual reinspection is relied on are effectively overcome, the effects of parameter self-adaptive adjustment, heat damage control and real-time quality closed-loop detection can be achieved in the welding process of the fuse and the terminal electrode, and the welding quality of the fuse and the terminal electrode is improved. And therefore, the production requirements of high-precision fuses can be met.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of fuse production, in particular to a fuse precision welding method and equipment. BACKGROUND

[0002] As a core component of circuit safety protection in the new energy field, the welding quality of the fuse and the end electrode of the fuse determines the on-off performance, overload protection threshold and service life of the fuse. The fuses in such application scenarios need to adapt to different specifications (the fuse material covers silver alloy and copper, the thickness range is 0.03-5 mm, and the diameter is 5-50 mm), and high requirements are put forward for the microstructure integrity and welding consistency of the fuse.

[0003] In the current fuse welding technology, although automatic equipment has partially replaced manual work, there are still three major defects in the production of high-precision fuses, which seriously restrict the production efficiency and product quality.

[0004] 1. Poor adaptability of welding parameters: The core parameters such as temperature, time and current of the existing automatic welding equipment are mostly fixed settings, and cannot be dynamically adjusted according to the fuse specifications. For example, for thin silver alloy fuses (thickness <0.1 mm), fixed high temperature and long time welding is adopted, which easily leads to excessive melting of the fuse or even penetration. For thick copper fuses (thickness >2 mm), fixed low temperature and short time welding is adopted, which easily leads to the problem of incomplete welding. Both cases will cause the on-off failure of the fuse, and cannot meet the safety protection requirements of new energy equipment.

[0005] 2. Significant thermal damage of laser welding: Most automatic equipment relies on single laser welding process, and the laser single-point energy is highly concentrated (especially for conventional lasers with wavelength 1064 nm), which causes the local temperature of the fuse to rise sharply, and the depth of the heat affected zone is generally more than 100 μm. Such excessive heat input will damage the microcrystalline structure of the fuse, cause the mechanical strength of the fuse to decrease, the melting threshold to drift, and even cause the oxidation layer on the surface of the fuse to intensify (such as Ag2O and CuO), further affecting the electrical performance stability of the fuse.

[0006] 3. Lack of real-time quality detection and reliance on manual reinspection: The existing technology cannot complete quality determination simultaneously during the welding process, and needs to perform reinspection operations such as appearance observation and resistance testing after welding. Manual reinspection not only has low efficiency (the time consumed for single batch detection is 3-5 times the welding time), but also is difficult to identify hidden defects such as "internal microcracks of the fuse" and "invisible virtual connection of the welding point", resulting in a defective product detection rate of more than 10%. At the same time, the unqualified products found through reinspection need to be reassembled and reworked, which greatly increases the production cycle and cost, and cannot adapt to large-scale production requirements.

[0007] To address the aforementioned shortcomings, existing technologies have not yet proposed an effective solution. There is an urgent need for a novel precision welding control method for fuses that can achieve "adaptive parameter adjustment, thermal damage control, and real-time quality closed-loop" in order to break through the production bottleneck of high-precision fuses.

[0008] The information disclosed in this background section is included only to enhance the understanding of the context of this disclosure, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0009] One objective of this invention is to provide a precision welding method and equipment for fuses, which can achieve adaptive parameter adjustment, thermal damage control, and real-time closed-loop quality detection during the welding process of fuses and end electrodes, thereby meeting the production requirements of high-precision fuses.

[0010] To achieve the above objectives, in one aspect, the present invention provides a method for precision welding of fused wires, comprising:

[0011] S1: Adaptive setting of welding parameters: Obtain the fuse wire specifications and end electrode parameters of the fuse to be welded, and automatically set the laser preheating parameters and resistance welding parameters based on the preset "fuse wire-end electrode specifications-welding parameters" mapping model; the laser preheating parameters include preheating temperature and preheating time, and the resistance welding parameters include welding current, welding time, and welding pressure;

[0012] S2: Laser-micro-resistance composite welding: After aligning the end electrode with the molten wire, start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire and eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1.

[0013] S3: Real-time Quality Inspection: During the welding process, a dual-band collaborative imaging system executes a "visible light and infrared fusion" inspection process, simultaneously acquiring visible light images of the fuse and end electrodes, and infrared images of the welding area. After registration and feature extraction, positioning deviation, weld joint morphology, and temperature field data are obtained. Combined with a precision resistance meter to detect the contact resistance between the fuse and end electrodes, and outputting a pass / fail result according to preset judgment rules:

[0014] If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step.

[0015] If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

[0016] Optionally, the specifications of the fuse include the fuse material and / or fuse thickness.

[0017] Optionally, in step S1, the “fuse-end electrode specification-welding parameter” mapping model is constructed as follows:

[0018] Using the yield strength and thickness of the fused wire material as input variables, and "no false welds / over-welds, heat-affected zone depth ≤50μm" as the objective function, the corresponding relationship between laser preheating temperature, resistance welding current, and welding pressure was obtained by fitting experimental data.

[0019] Optionally, in step S2:

[0020] The wavelength of the pulsed laser is 1064nm, and the preheating temperature is controlled at 300℃±10℃.

[0021] The welding current of the micro-resistance electrode is adjustable from 50A to 200A, the welding time is controlled from 8ms to 12ms, and the depth of the heat-affected zone is controlled within 50μm.

[0022] Optionally, in step S3, the dual-band collaborative imaging system includes a visible light camera and a near-infrared thermal imager;

[0023] The visible light camera is used to acquire visible light images of the fuse and the end electrode, locate the edges of the fuse and the end electrode, and compensate for the relative position error of the fuse and the end electrode by combining the point cloud registration algorithm. At the same time, it captures the shape of the solder joint and identifies whether the area and shape of the solder joint meet the preset standards.

[0024] The near-infrared thermal imager is used to monitor the welding temperature field in real time. It identifies overheated areas within the welding area through a convolutional neural network and triggers cooling airflow when an overheated area is identified.

[0025] Optionally, S3 includes:

[0026] S31: Image acquisition and preprocessing: The visible light camera and near-infrared thermal imager simultaneously acquire visible light and infrared images of the fuse and end electrode; perform non-uniformity correction on the infrared image and denoise removal and contrast enhancement on the visible light image;

[0027] S32: Registration: Perform feature matching, transformation estimation, and image resampling on the corner / edge features detected in the visible light image and the thermal boundary features detected in the infrared image to make the two images spatially aligned accurately.

[0028] S33: Feature Extraction: Extracting features from the registered image:

[0029] From visible light images: the YOLO algorithm is used to identify the bounding boxes of the terminal electrodes and fuse wires, and the solder joint morphology data is obtained through contour analysis;

[0030] From infrared images: read temperature data of the welding area, calculate the highest and average temperatures of the component area, and identify overheated areas using a convolutional neural network;

[0031] S34: Quality Judgment and Data Recording: Logically judge the extracted feature data according to the preset judgment rules, output qualified / unqualified results, and store the results in the database in association with the fuse specifications and welding parameters.

[0032] Optionally, the step of performing logical judgment on the extracted feature data according to preset judgment rules and outputting a qualified / unqualified result includes:

[0033] Preset conditions 1-4: Welding is deemed qualified if and only if all conditions 1-4 are met; otherwise, it is deemed unqualified.

[0034] in,

[0035] Condition 1: The positioning deviation calculated by the visible light camera is ≤ ±3μm;

[0036] Condition 2: The weld joint shape meets the standard: area deviation ≤ ±5%, and the shape is circular or elliptical;

[0037] Condition 3: There are no overheated areas in the infrared image, and the highest temperature does not exceed the allowable material threshold.

[0038] Condition 4: The contact resistance measured by the precision resistor meets the standard.

[0039] Optionally, if any indicator fails to meet the standard, a parameter correction command is triggered and fed back to step S1 to adjust the parameters for the next welding operation, including:

[0040] If condition 1 is not met: adjust the relative position of the micro-resistance electrode and the fuse, compensate for the deviation, and then repeat step S2;

[0041] If condition 2 is not met:

[0042] If the weld area deviation is > ±5%, adjust the welding pressure according to the direction of the area deviation.

[0043] If the weld joint shape is not circular / elliptical: the contact position of the micro-resistance electrode is recalibrated using the point cloud registration algorithm of the visible light camera, and the resistance welding current is fine-tuned.

[0044] After adjustment, repeat step S2;

[0045] If condition 3 is not met: reduce the laser preheating temperature by 5-10℃, shorten the resistance welding time by 1-2ms, and repeat step S2.

[0046] If condition 4 is not met: increase the welding pressure by 0.1-0.3N, increase the welding current by 5-10A, and repeat step S2.

[0047] On the other hand, a wire welding apparatus is provided for the aforementioned wire precision welding method, comprising:

[0048] The welding parameter setting module is used to obtain the fuse wire specifications and end electrode parameters of the fuse to be welded. Based on the preset "fuse wire-end electrode specifications-welding parameters" mapping model, it automatically sets the laser preheating parameters and resistance welding parameters. The laser preheating parameters include preheating temperature and preheating time, and the resistance welding parameters include welding current, welding time, and welding pressure.

[0049] The composite welding module is used to align the end electrode with the molten wire, and then start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire to eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1.

[0050] The real-time quality inspection module is used during the welding process to perform a "visible light and infrared fusion" inspection process through a dual-band collaborative imaging system. It simultaneously acquires visible light images of the molten wire and end electrodes, and infrared images of the welding area. After registration and feature extraction, it obtains positioning deviation, weld joint morphology, and temperature field data. Combined with a precision resistance meter to detect the contact resistance between the molten wire and end electrodes, it outputs a pass / fail result according to preset judgment rules.

[0051] If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step.

[0052] If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

[0053] Optionally, a matrix clamping platform may also be included;

[0054] The matrix clamping platform includes a platform base plate, a plurality of vacuum suction heads arranged in a matrix on the platform base plate, and a plurality of shape memory alloy strips corresponding to each of the vacuum suction heads; wherein, the shape memory alloy strips have a bent state at a first temperature to cooperate with the platform base plate to clamp the workpiece, and a straight state at a second temperature to release the workpiece; the first temperature is higher or lower than the second temperature.

[0055] The beneficial effects of the present invention are as follows: It provides a precision welding method for fused wire, which effectively solves the defects of the prior art, such as poor process adaptability caused by fixed welding parameters, significant welding thermal damage, and reliance on manual re-inspection, through closed-loop control of adaptive setting of welding parameters (S1), laser-micro resistance composite welding (S2) and real-time quality detection (S3).

[0056] Specifically, S1 dynamically adjusts parameters based on a mapping model, overcoming the problems of fixed welding parameters and poor adaptability, and ensuring the welding quality of fuses of different specifications; S2 adopts a composite process of laser preheating and micro-resistance welding, avoiding the thermal damage of single laser welding, effectively controlling the depth of the heat-affected zone, and protecting the microstructure of the fuse; S3 achieves immediate judgment and feedback through real-time quality detection, eliminating the dependence on manual re-inspection, improving production efficiency and consistency, and thus meeting the production requirements of high-precision fuses.

[0057] Therefore, the precision welding method and equipment for fuses provided by this invention can achieve adaptive parameter adjustment, thermal damage control, and real-time quality closed-loop detection during the welding process of fuses and end electrodes, thereby meeting the production requirements of high-precision fuses. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart of a precision welding method for fused wires provided in this embodiment;

[0060] Figure 2 A structural block diagram of the wire bonding equipment provided in the embodiment;

[0061] Figure 3 This is a schematic diagram of the matrix clamping platform provided in the embodiment.

[0062] In the picture:

[0063] 1. Welding parameter setting module;

[0064] 2. Composite welding module;

[0065] 3. Real-time quality detection module;

[0066] 4. Matrix clamping platform; 401. Platform base plate; 402. Vacuum suction head; 403. Shape memory alloy strip. Detailed Implementation

[0067] In this invention, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the invention. The term "embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment, nor does it specifically limit its independence or connection with other embodiments. In principle, in this invention, as long as there is no technical contradiction or conflict, the technical features mentioned in each embodiment can be combined in any way to form a corresponding implementable technical solution.

[0068] Unless otherwise defined, the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the use of related terms herein is merely for the purpose of describing particular embodiments and is not intended to limit the invention.

[0069] In the description of this invention, the term "and / or" is used to describe the logical relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A exists, B exists, and A and B exist simultaneously. Additionally, the character " / " generally indicates that the preceding and following objects have an "or" logical relationship.

[0070] In this invention, terms such as “first” and “second” are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any actual quantity, hierarchy, or order between these entities or operations.

[0071] Without further limitations, the use of terms such as “comprising,” “including,” “having,” or other similar expressions in this invention is intended to cover non-exclusive inclusion, which does not exclude the presence of additional elements in a process, method, or product that includes the stated elements, such that a process, method, or product that includes a list of elements may include not only those defined elements but also other elements not expressly listed, or elements inherent to such a process, method, or product.

[0072] Similar to the understanding in the Examination Guidelines, in this invention, expressions such as "greater than," "less than," and "exceeding" are understood to exclude the stated number; expressions such as "above," "below," and "within" are understood to include the stated number. Furthermore, in the description of the embodiments of this invention, "multiple" means two or more (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups" and "multiple times," unless otherwise explicitly specified.

[0073] In the description of the embodiments of the present invention, the spatial related expressions used, such as "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "vertical," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," "circumferential," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the specific embodiments or drawings. They are only for the purpose of describing the specific embodiments of the present invention or for the reader's understanding, and do not indicate or imply that the device or component referred to must have a specific position, a specific orientation, or be constructed or operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of the present invention.

[0074] Unless otherwise explicitly stated or limited, the terms "installation," "connection," "linking," "fixing," and "setting," as used in the description of the embodiments of this invention, should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral arrangement; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this invention according to the specific circumstances.

[0075] This invention provides a precision welding method and equipment for fused wire. Through closed-loop control of adaptive welding parameter setting (S1), laser-micro resistance composite welding (S2), and real-time quality detection (S3), it effectively solves the defects of existing technologies, such as poor process adaptability caused by fixed welding parameters, significant welding thermal damage, and reliance on manual re-inspection.

[0076] On the one hand, see Figure 1 This embodiment provides a method for precision welding of fused wires, including:

[0077] S1: Adaptive Welding Parameter Setting: Obtain the fuse wire specifications (material, thickness) and end electrode parameters (material, size) of the fuse to be welded. Based on a preset "fuse-end electrode specifications-welding parameters" mapping model, automatically set the laser preheating parameters (preheating temperature 280-320℃, duration 10-20ms) and resistance welding parameters (welding current 50-200A, time 8-12ms, pressure 0.5-10N±0.05N). The laser preheating parameters include preheating temperature and preheating duration, and the resistance welding parameters include welding current, welding time, and welding pressure.

[0078] S2: Laser-micro-resistance composite welding: After aligning the end electrode with the molten wire, start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire and eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1.

[0079] S3: Real-time Quality Inspection: During the welding process, a dual-band collaborative imaging system executes a "visible light and infrared fusion" inspection process, simultaneously acquiring visible light images of the fuse and end electrodes, and infrared images of the welding area. After registration and feature extraction, positioning deviation, weld joint morphology, and temperature field data are obtained. Combined with a precision resistance meter to detect the contact resistance between the fuse and end electrodes, and outputting a pass / fail result according to preset judgment rules:

[0080] If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step.

[0081] If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

[0082] Specifically, S1 dynamically adjusts parameters based on a mapping model, overcoming the problems of rigid welding parameters and poor adaptability, and ensuring the welding quality of fuses of different specifications (such as thin silver alloys or thick copper). S2 adopts a composite process of laser preheating and micro-resistance welding, avoiding the thermal damage of single laser welding, effectively controlling the depth of the heat-affected zone, and protecting the microstructure of the fuse. S3 achieves immediate judgment and feedback through real-time quality detection, eliminating the dependence on manual re-inspection, improving production efficiency and consistency, and thus meeting the production requirements of high-precision fuses.

[0083] Therefore, the precision welding method for fuses provided by this invention can achieve adaptive parameter adjustment, thermal damage control, and real-time quality closed-loop detection during the welding process of fuses and end electrodes, thereby meeting the production requirements of high-precision fuses.

[0084] Optionally, the specifications of the fuse include the fuse material and / or fuse thickness. These parameters serve as key inputs for querying the "fuse-end electrode specification-welding parameter" mapping model to accurately set the laser preheating parameters and resistance welding parameters.

[0085] Generally speaking, the fuse wire is the key component that determines the core performance of a fuse. The material of the terminal electrode is relatively fixed, usually copper or silver-plated copper. Furthermore, the mating surface with the fuse wire can be silver-plated (0.5-1μm thick), and the size is adapted to fuse housings with diameters of 5-50mm. Therefore, the main difference between products with different positioning is the fuse wire. Thus, the mapping model of "fuse wire-terminal electrode specification-welding parameters" can be simplified to a mapping model of "fuse wire-welding parameters," that is, the terminal electrode specification is treated as an invariant.

[0086] Therefore, the construction method of the "fuse-end electrode specification-welding parameter" mapping model in step S1 can be simplified as follows:

[0087] Using the yield strength and thickness of the fused wire material as input variables, and "no false welds / over-welds, heat-affected zone depth ≤50μm" as the objective function, the corresponding relationship between laser preheating temperature, resistance welding current, and welding pressure was obtained by fitting experimental data.

[0088] Optionally, a piezoelectric ceramic micro-actuator (response time <5ms) and an electromagnetic damper can be integrated at the micro-resistive electrode that serves as the welding head to detect the welding pressure in real time and feed it back to the control system.

[0089] Optionally, the welding pressure range is 0.5N±0.05N-10N±0.05N. Further, when the fuse material is silver alloy, the initial welding pressure is set to 0.8N-2N; when the fuse material is copper, the initial welding pressure is set to 1.5N-3N.

[0090] By constructing a mapping relationship through scientific models and optimizing parameters based on the mechanical properties (yield strength) and geometric dimensions (thickness) of the weld wire, the welding process becomes more precise and controllable, effectively preventing thermal damage and welding defects. Pressure feedback mechanisms (such as piezoelectric ceramic micro-actuators) ensure the stability and accuracy of the welding pressure, further reducing the risk of incomplete or over-welded welds and improving welding consistency and reliability.

[0091] Optionally, in step S2 of this embodiment:

[0092] The wavelength of the pulsed laser is 1064nm, and the preheating temperature is controlled at 300℃±10℃.

[0093] The welding current of the micro-resistance electrode is adjustable from 50A to 200A, the welding time is controlled from 8ms to 12ms, and the depth of the heat-affected zone is controlled within 50μm.

[0094] These parameters are strictly controlled during the welding process to ensure the precision of preheating and welding. By fixing the laser wavelength and preheating temperature, and constraining the welding current and time, precise management of heat input is achieved, significantly reducing the depth of the heat-affected zone (≤50μm) and avoiding damage to the microstructure of the weld wire. This solves the problem of significant thermal damage in laser welding in the prior art and improves the mechanical strength and electrical performance stability of the weld wire.

[0095] Optionally, in step S3, the dual-band collaborative imaging system includes a visible light camera and a near-infrared thermal imager;

[0096] The visible light camera has a resolution of 5μm and is used to acquire visible light images of the fuse and the end electrode, locate the edges of the fuse and the end electrode, and compensate for the relative position error of the fuse and the end electrode by combining a point cloud registration algorithm. The positioning accuracy reaches ±3μm. At the same time, it captures the shape of the solder joint and identifies whether the area and shape of the solder joint meet the preset standards (the allowable deviation of the solder joint area is ±5%, and the shape is circular or elliptical with no jagged edges).

[0097] The near-infrared thermal imager is used to monitor the welding temperature field in real time. It identifies overheated areas within the welding area through a convolutional neural network (CNN) and triggers cooling airflow when an overheated area is identified.

[0098] Optionally, the near-infrared thermal imager has a temperature detection accuracy of ±1℃ and a temperature data acquisition frequency of ≥200Hz; the cooling airflow speed adjustment range is 5-10m / s, and the airflow direction forms a 45° angle with the welding point. The point cloud registration algorithm extracts the feature point cloud of the fuse and the edge of the end electrode, calculates the position deviation compensation value, and realizes dynamic positioning calibration.

[0099] The precision resistance meter has a detection accuracy of ±0.01mΩ, and the qualified standard for contact resistance is: contact resistance ≤5mΩ after welding silver alloy wire, and contact resistance ≤8mΩ after welding copper wire.

[0100] The point cloud registration algorithm achieves dynamic positioning and calibration through feature point cloud extraction. A high-precision imaging system enables multi-dimensional real-time detection: a visible light camera ensures accuracy in positioning and weld joint morphology, while a near-infrared thermal imager provides temperature monitoring and overheat protection. Combined with point cloud registration and CNN algorithms, the reliability and efficiency of detection are improved. This effectively identifies latent defects (such as microcracks), reduces the need for manual re-inspection, and improves the level of production automation.

[0101] In this embodiment, S3 includes:

[0102] S31: Image acquisition and preprocessing: The visible light camera and near-infrared thermal imager simultaneously acquire visible light and infrared images of the fuse and end electrodes (ensuring time synchronization between the visible light and infrared images); non-uniformity correction is performed on the infrared image (to eliminate sensor noise), and noise reduction and contrast enhancement are performed on the visible light image;

[0103] S32: Registration: Perform feature matching, transformation estimation (calculate affine / perspective transformation matrix) and image resampling on the corner / edge features detected in the visible light image and the thermal boundary features detected in the infrared image to make the two images spatially aligned precisely (each hot spot in the infrared image corresponds to the specific location of the fuse-terminal electrode docking point in the visible light image).

[0104] Furthermore, the "thermal boundary features" mentioned in step S32 are extracted by the Canny edge detector or a gradient-based feature detection algorithm, and form matching point pairs with the corner / edge features detected by the visible light camera to ensure that each hot spot in the infrared image corresponds to a specific physical location in the visible light image.

[0105] S33: Feature Extraction: Extracting features from the registered image:

[0106] From the visible light image: the YOLO algorithm is used to identify the bounding box of the terminal electrode and the fuse, and the solder joint morphology data is obtained through contour analysis (area deviation is allowed to be ±5%, and the shape is circular or elliptical).

[0107] From infrared images: read temperature data of the welding area, calculate the maximum temperature (T_max) and average temperature (T_avg) of the component area, and identify overheated areas using a convolutional neural network (CNN); the maximum temperature (T_max) should not exceed the allowable threshold, which is set according to the material.

[0108] Optionally, the "temperature threshold" mentioned in step S33 is set according to the fuse material: silver alloy fuse + copper end electrode ≤ 400℃, copper fuse + copper end electrode ≤ 450℃.

[0109] S34: Quality Judgment and Data Recording: Logically judge the extracted feature data according to the preset judgment rules, output qualified / unqualified results, and store the results in the database in association with the fuse specifications and welding parameters.

[0110] Through the four standardized detection sub-steps described above, accurate fusion and analysis of visible light and infrared data are achieved, improving the accuracy and repeatability of quality judgment. Registration and feature extraction algorithms ensure data consistency, avoid false detections, thereby reducing the rate of missed defective products and supporting large-scale mass production.

[0111] In this embodiment, the step of performing logical judgment on the extracted feature data according to preset judgment rules and outputting a qualified / unqualified result includes:

[0112] Preset conditions 1-4: Welding is deemed qualified if and only if all conditions 1-4 are met; otherwise, it is deemed unqualified.

[0113] in,

[0114] Condition 1: The positioning deviation calculated by the visible light camera is ≤ ±3μm;

[0115] Condition 2: The weld joint shape meets the standard: the area deviation is ≤ ±5%, and the shape is round or elliptical (without serrated edges).

[0116] Condition 3: There are no overheated areas in the infrared image, and the maximum temperature (T_max) does not exceed the allowable material threshold;

[0117] Condition 4: The contact resistance measured by the precision resistance meter meets the standard (silver alloy fuse - end electrode ≤ 5mΩ, copper fuse - end electrode ≤ 8mΩ).

[0118] By employing multi-condition logic judgment, a comprehensive quality assessment is achieved, covering key indicators such as positioning, morphology, temperature, and resistance, ensuring the overall reliability of welding quality. This avoids missed defects caused by deviations in a single indicator, improving product consistency and safety.

[0119] Furthermore, if any indicator fails to meet the standard, a parameter correction command is triggered and fed back to step S1 to adjust the parameters for the next welding operation, including:

[0120] If condition 1 is not met (positioning deviation exceeds ±3μm): adjust the relative position of the micro-resistance electrode and the fuse, compensate for the deviation, and then repeat step S2;

[0121] If condition 2 is not met (solder joint morphology is unacceptable):

[0122] If the weld area deviation is > ±5% (area too small or too large): adjust the welding pressure according to the direction of the area deviation—if the area is < 5% or more of the standard value, increase the welding pressure by 0.2-0.4N; if the area is > 5% or more of the standard value, decrease the welding pressure by 0.1-0.3N.

[0123] If the weld joint shape is not circular / elliptical (including serrated edges): the contact position of the micro-resistance electrode is recalibrated using the point cloud registration algorithm of the visible light camera (correction deviation ≤ ±2μm), and the resistance welding current is finely adjusted to ±8A (too small a current can easily lead to irregular edges, and too large a current can easily lead to edge erosion).

[0124] After adjustment, repeat step S2;

[0125] If condition 3 is not met (overheated area exists or T_max exceeds the threshold): reduce the laser preheating temperature by 5-10℃, shorten the resistance welding time by 1-2ms, and repeat step S2.

[0126] If condition 4 is not met (contact resistance exceeds the standard): increase welding pressure by 0.1-0.3N, increase welding current by 5-10A, and repeat step S2.

[0127] By adjusting specific parameters, dynamic adaptive adjustment of the welding process was achieved, effectively correcting defects detected in real-time inspections and preventing the generation of batches of defective products. This improved production efficiency and resource utilization, and reduced rework costs.

[0128] On the other hand, see Figure 2 This embodiment provides a wire welding apparatus for performing any of the above-described wire precision welding methods, including:

[0129] The welding parameter setting module 1 is used to acquire the fuse wire specifications (material, thickness) and end electrode parameters (material, size) of the fuse to be welded. Based on a preset "fuse wire-end electrode specifications-welding parameters" mapping model, it automatically sets the laser preheating parameters (preheating temperature 280-320℃, duration 10-20ms) and resistance welding parameters (welding current 50-200A, time 8-12ms, pressure 0.5-10N±0.05N). The laser preheating parameters include preheating temperature and preheating duration, and the resistance welding parameters include welding current, welding time, and welding pressure.

[0130] The composite welding module 2 is used to align the end electrode with the molten wire, and then start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire to eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1.

[0131] Real-time quality inspection module 3 is used during the welding process to execute a "visible light and infrared fusion" inspection process through a dual-band collaborative imaging system. It simultaneously acquires visible light images of the molten wire and end electrodes, and infrared images of the welding area. After registration and feature extraction, it obtains positioning deviation, weld joint morphology, and temperature field data. Combined with a precision resistance meter to detect the contact resistance between the molten wire and end electrodes, it outputs a pass / fail result according to preset judgment rules.

[0132] If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step.

[0133] If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

[0134] The modular design enables automated operation of the method, integrating parameter adaptation, composite welding, and real-time detection, thus addressing three major shortcomings of the prior art. The equipment improves welding accuracy, consistency, and production efficiency, making it suitable for large-scale production of high-precision fuses.

[0135] Optionally, the fuse and the terminal electrode are pre-mounted and fixed on the fuse housing, with the welding areas of the fuse and the terminal electrode exposed. In this case, simply clamping and fixing the fuse housing is sufficient to position the fuse and the terminal electrode.

[0136] See Figure 3 The wire welding equipment also includes a matrix clamping platform 4;

[0137] The matrix clamping platform 4 includes a platform base plate 401, a plurality of vacuum suction heads 402 arranged in a matrix on the platform base plate 401, and a plurality of shape memory alloy strips 403 corresponding to each of the vacuum suction heads 402; wherein, the shape memory alloy strips 403 have a bent state at a first temperature to cooperate with the platform base plate 401 to clamp the corresponding fuse housing, and a straight state at a second temperature to release the corresponding fuse housing; the first temperature is higher or lower than the second temperature.

[0138] The working process of the matrix clamping platform 4 is a temperature-controlled clamping-release cycle, as follows:

[0139] (1) Feeding and clamping:

[0140] The fuse housing, pre-loaded with fuse wire and terminal electrode, is initially adsorbed and fixed by vacuum suction head 402;

[0141] Subsequently, the system will heat up or cool down the shape memory alloy strip 403 (to bring it to the "first temperature").

[0142] Once a specific temperature is reached, the shape memory alloy strip 403 will return to its preset curved shape, like a hook, firmly pressing the fuse housing onto the platform base plate 401 from the side.

[0143] At this point, the fuse and end electrodes are precisely positioned and ready for welding.

[0144] (2) Welding completion and release:

[0145] After the welding process is completed, the system changes the temperature of the shape memory alloy strip 403 (to bring it to the "second temperature").

[0146] Under temperature changes, the shape memory alloy strip 403 changes from a bent state to a straight state, automatically releasing the clamping force on the fuse housing.

[0147] At this point, the welded workpiece can be easily removed, and the next cycle can begin.

[0148] During the clamping and fixing process described above, the entire clamping and releasing process is automatically completed by controlling the temperature, eliminating the need for complex mechanical transmission mechanisms (such as springs, cylinders, etc.), reducing the risk of mechanical wear, jamming, and other malfunctions, and ensuring reliable operation. Furthermore, the shape memory alloy exhibits smooth and controllable deformation, providing a stable and uniform clamping force, thus preventing damage to the fuse housing due to excessive or asymmetrical clamping stress.

[0149] In summary, the matrix clamping platform 4, through the unique properties of temperature-controlled shape memory alloys, achieves efficient, automatic, precise and reliable clamping and release of multiple workpieces, perfectly adapting to the high-precision and automated welding process described in this invention.

[0150] Finally, it should be noted that although the above embodiments have been described in the text and drawings of this application, this should not limit the scope of patent protection of this application. Any technical solutions that are based on the essential concept of this application and utilize the content described in the text and drawings of this application, resulting in equivalent structural or procedural substitutions or modifications, as well as the direct or indirect application of the technical solutions of the above embodiments to other related technical fields, are all included within the scope of patent protection of this application.

Claims

1. A method for precision welding of fused wires, characterized in that, include: S1: Adaptive setting of welding parameters: Obtain the fuse wire specifications and end electrode parameters of the fuse to be welded, and automatically set the laser preheating parameters and resistance welding parameters based on the preset "fuse wire-end electrode specifications-welding parameters" mapping model; the laser preheating parameters include preheating temperature and preheating time, and the resistance welding parameters include welding current, welding time, and welding pressure; S2: Laser-micro-resistance composite welding: After aligning the end electrode with the molten wire, start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire and eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1. S3: Real-time Quality Inspection: During the welding process, a dual-band collaborative imaging system executes a "visible light and infrared fusion" inspection process, simultaneously acquiring visible light images of the fuse and end electrodes, and infrared images of the welding area. After registration and feature extraction, positioning deviation, weld joint morphology, and temperature field data are obtained. Combined with a precision resistance meter to detect the contact resistance between the fuse and end electrodes, and outputting a pass / fail result according to preset judgment rules: If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step. If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

2. The precision welding method for fused wire according to claim 1, characterized in that, The specifications of the fuse include the fuse material and / or fuse thickness.

3. The precision welding method for fused wire according to claim 2, characterized in that, In step S1, the "fuse-end electrode specification-welding parameter" mapping model is constructed as follows: Using the yield strength and thickness of the fused wire material as input variables, and "no false welds / over-welds, heat-affected zone depth ≤50μm" as the objective function, the corresponding relationship between laser preheating temperature, resistance welding current, and welding pressure was obtained by fitting experimental data.

4. The precision welding method for fused wire according to claim 3, characterized in that, In step S2: The wavelength of the pulsed laser is 1064nm, and the preheating temperature is controlled at 300℃±10℃. The welding current of the micro-resistance electrode is adjustable from 50A to 200A, the welding time is controlled from 8ms to 12ms, and the depth of the heat-affected zone is controlled within 50μm.

5. The precision welding method for fused wire according to claim 1, characterized in that, In step S3, the dual-band collaborative imaging system includes a visible light camera and a near-infrared thermal imager; The visible light camera is used to acquire visible light images of the fuse and the end electrode, locate the edges of the fuse and the end electrode, and compensate for the relative position error of the fuse and the end electrode by combining the point cloud registration algorithm. At the same time, it captures the shape of the solder joint and identifies whether the area and shape of the solder joint meet the preset standards. The near-infrared thermal imager is used to monitor the welding temperature field in real time. It identifies overheated areas within the welding area through a convolutional neural network and triggers cooling airflow when an overheated area is identified.

6. The precision welding method for fused wire according to claim 5, characterized in that, S3 includes: S31: Image acquisition and preprocessing: The visible light camera and near-infrared thermal imager simultaneously acquire visible light and infrared images of the fuse and end electrode; perform non-uniformity correction on the infrared image and denoise removal and contrast enhancement on the visible light image; S32: Registration: Perform feature matching, transformation estimation, and image resampling on the corner / edge features detected in the visible light image and the thermal boundary features detected in the infrared image to make the two images spatially aligned accurately. S33: Feature Extraction: Extracting features from the registered image: From visible light images: the YOLO algorithm is used to identify the bounding boxes of the terminal electrodes and fuse wires, and the solder joint morphology data is obtained through contour analysis; From infrared images: read temperature data of the welding area, calculate the highest and average temperatures of the component area, and identify overheated areas using a convolutional neural network; S34: Quality Judgment and Data Recording: Logically judge the extracted feature data according to the preset judgment rules, output qualified / unqualified results, and store the results in the database in association with the fuse specifications and welding parameters.

7. The precision welding method for fused wire according to claim 6, characterized in that, The step of performing logical judgment on the extracted feature data according to preset judgment rules and outputting a qualified / unqualified result includes: Preset conditions 1-4: Welding is deemed qualified if and only if all conditions 1-4 are met; otherwise, it is deemed unqualified. in, Condition 1: The positioning deviation calculated by the visible light camera is ≤ ±3μm; Condition 2: The weld joint shape meets the standard: area deviation ≤ ±5%, and the shape is circular or elliptical; Condition 3: There are no overheated areas in the infrared image, and the highest temperature does not exceed the allowable material threshold. Condition 4: The contact resistance measured by the precision resistor meets the standard.

8. The precision welding method for fused wire according to claim 7, characterized in that, If any indicator fails to meet the standard, a parameter correction command is triggered and fed back to step S1 to adjust the parameters for the next welding operation, including: If condition 1 is not met: adjust the relative position of the micro-resistance electrode and the fuse, compensate for the deviation, and then repeat step S2; If condition 2 is not met: If the weld area deviation is > ±5%, adjust the welding pressure according to the direction of the area deviation. If the weld joint shape is not circular / elliptical: the contact position of the micro-resistance electrode is recalibrated using the point cloud registration algorithm of the visible light camera, and the resistance welding current is fine-tuned. After adjustment, repeat step S2; If condition 3 is not met: reduce the laser preheating temperature by 5-10℃, shorten the resistance welding time by 1-2ms, and repeat step S2. If condition 4 is not met: increase the welding pressure by 0.1-0.3N, increase the welding current by 5-10A, and repeat step S2.

9. A wire welding apparatus for performing the wire precision welding method according to any one of claims 1-8, characterized in that, include: The welding parameter setting module is used to obtain the fuse wire specifications and end electrode parameters of the fuse to be welded. Based on the preset "fuse wire-end electrode specifications-welding parameters" mapping model, it automatically sets the laser preheating parameters and resistance welding parameters. The laser preheating parameters include preheating temperature and preheating time, and the resistance welding parameters include welding current, welding time, and welding pressure. The composite welding module is used to align the end electrode with the molten wire, and then start the pulsed laser according to the laser preheating parameters set in step S1 to locally preheat the surface of the molten wire to eliminate the oxide layer on the surface of the molten wire; then start the micro-resistance electrode of the welding equipment to contact the joint between the molten wire and the end electrode, and complete the penetration welding according to the resistance welding parameters set in step S1. The real-time quality inspection module is used during the welding process to execute a "visible light and infrared fusion" inspection process through a dual-band collaborative imaging system. It simultaneously acquires visible light images of the molten wire and end electrodes, and infrared images of the welding area. After registration and feature extraction, it obtains positioning deviation, weld joint morphology, and temperature field data. Combined with a precision resistance meter to detect the contact resistance between the molten wire and end electrodes, it outputs a pass / fail result according to preset judgment rules. If the positioning deviation, weld point shape, temperature field data, and contact resistance all meet the preset standards, the welding is deemed qualified and the process proceeds to the next step. If any indicator fails to meet the standard, a parameter correction instruction is triggered, which is fed back to step S1 to adjust the parameters for the next welding and sort out the defective products.

10. The wire welding equipment according to claim 9, characterized in that, It also includes a matrix clamping platform; The matrix clamping platform includes a platform base plate, a plurality of vacuum suction heads arranged in a matrix on the platform base plate, and a plurality of shape memory alloy strips corresponding to each of the vacuum suction heads; wherein, the shape memory alloy strips have a bent state at a first temperature to cooperate with the platform base plate to clamp the workpiece, and a straight state at a second temperature to release the workpiece; the first temperature is higher or lower than the second temperature.

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