44987results about "Auxillary welding devices" patented technology

The present invention relates to the field of welding technology, and discloses an automated welding path optimization method based on BIM and point cloud data, comprising the following steps: acquiring point cloud data and BIM model data, wherein the point cloud data is acquired by laser scanning or other three-dimensional scanning technology, and the BIM model data is a design model before construction; preprocessing the point cloud data, including denoising, simplification and surface reconstruction, to improve the quality and processing efficiency of the point cloud data; and registering the point cloud data and the BIM model data. By integrating BIM and point cloud data, the accuracy and quality of the welding path are significantly improved, welding defects are reduced, a multi-objective optimization algorithm is adopted, path planning is optimized, operation time and material consumption are reduced, and welding efficiency is improved at the same time. The real-time feedback and dynamic adjustment mechanism enable the welding path to adapt to on-site geometric deformation, ensure welding quality and accuracy, and is particularly suitable for complex and dynamically changing construction environments.

The invention provides an intelligent high-performance collaborative welding robot system, which belongs to the technical field of welding robots and comprises a multi-degree-of-freedom welding robot body, an intelligent control system, a high-performance welding power supply and auxiliary equipment. A welding process control module firstly obtains three-dimensional information of a workpiece based on visual inspection to construct a welding path; then selecting matched process parameters according to material characteristics and welding seam shapes; establishing a welding error matrix to monitor the welding process in real time; constructing a parameter error adjustment matrix for dynamic adjustment; analyzing parameter fluctuation by adopting a neural network to identify molten pool characteristics; the pre-trained neural network is used for evaluating the welding seam quality; and finally, a multi-robot collaborative welding strategy is integrated to achieve efficient operation, and the technical problem that in the prior art, welding process parameters in a welding robot are difficult to adjust accurately in real time so as to adapt to complex working condition changes is solved.

The invention provides a teaching-free welding robot path planning system based on visual autonomous learning, and relates to the technical field of industrial welding, and the teaching-free welding robot path planning system comprises a pose compensation module which is used for arranging three infrared reflective mark points on the surface of a clamp base in an L shape, collecting original point clouds of the mark points and a workpiece by using a stereo camera, and preprocessing the point clouds; generating a pose compensation matrix based on the offset of the actual coordinate and the theoretical coordinate of the mark point, and outputting a de-noising point cloud data set and a compensation matrix; and the pose correction module is used for fitting a workpiece plane equation by adopting a random sampling consistency algorithm on the basis of the de-noised point cloud data set, acting a pose compensation matrix on the workpiece plane equation, correcting a pose error caused by clamp drifting, calculating a welding seam track end point coordinate and outputting a corrected welding seam pose parameter and a scanning pose instruction. According to the method, clamp drift can be compensated, weld joint poses can be corrected, three-dimensional features are extracted, a collision-free path is planned, and the welding precision, efficiency and automation degree are improved.

The invention provides an aluminum alloy auxiliary frame welding accurate positioning and quality control method and system. The method comprises the steps that S4, welding gun track control parameters are updated through a dynamic adjustment instruction, laser tracking data are fused to optimize the welding path angle in real time, and the accurate movement track of each section of welding seam is determined; s5, acquiring real-time thermal expansion data during welding execution, monitoring temperature field distribution of a welding seam area by adopting an optical measurement technology, and judging whether thermal deformation adjustment exceeds a preset threshold value or not; s7, micron-sized welding spot positioning operation is executed according to the stable positioning state, the dynamic path optimization result is fused to generate a final welding instruction, and consistent welding seam quality data is output; and S8, after weld joint quality data are obtained, weld joint deviation and geometric consistency are detected through a laser tracking technology, whether welding quality meets design requirements or not is judged, and a quality verification report is generated. According to the method, the precision and consistency of intelligent welding of the aluminum alloy auxiliary frame are remarkably improved.

The invention provides a thermal deformation intelligent compensation and control method and system in a metal part welding process, and relates to the technical field of metal welding, and the thermal deformation intelligent compensation and control method comprises the following steps: obtaining a three-dimensional model and process parameters, constructing a thermal-mechanical coupling analysis model, and collecting real-time temperature and strain data; thermal deformation is predicted through a dynamic hierarchical graph structure and a bidirectional propagation neural network, optimal welding process parameters are calculated through a recursive optimizer integrating a gradient strategy and an evolution strategy based on thermal deformation deviation, accurate prediction and intelligent compensation of thermal deformation in the welding process can be achieved, and the welding quality and precision are improved.

A nozzle for a laser processing system is provided. A primary passage extends between the proximal end and the distal end of the nozzle body along a central longitudinal axis. At least one auxiliary passage is located within the body of the nozzle adjacent to the primary passage while substantially fluidly isolated from the primary passage. At least one conduit is located proximate the distal end of the body and in fluid communication with the at least one auxiliary passage. The at least one auxiliary passage is configured to flow a secondary fluid through the body of the nozzle in a first direction to impinge on a surface of the at least one conduit that is proximate the primary passage. The at least one conduit is configured to redirect the secondary fluid toward an exterior surface of the body in a second direction.

A laser processing apparatus irradiates a target with a laser light to form a modified region along a virtual plane in the target. The laser processing apparatus includes a support portion, an irradiation portion, a movement mechanism, and a controller. The controller performs a first processing process of irradiating a first portion in the target with the laser light under a first processing condition, and a second processing process of irradiating a second portion more on an inner side than the first portion in the target with the laser light under a second processing condition different from the first processing condition, after the first processing process.

The invention provides an array detection and positioning method combined with multi-welding-head battery welding, which comprises the following steps: monitoring the distribution of a welding head temperature field in real time by adopting an infrared thermal imaging technology, judging whether the welding head temperature field deviates or not by combining a preset temperature threshold value, and judging that the welding head temperature field deviates if detecting that the temperature of a certain welding head exceeds a threshold value range; according to the offset of the welding position, motion control parameters of the digital welding system are adjusted in a self-adaptive mode, and the offset error of a welding head is compensated in real time through a closed-loop feedback control algorithm; the welding spot quality online monitoring technology is adopted, the welding spot fusion depth and the welding spot diameter are extracted, whether the welding spot quality is qualified or not is judged in real time in combination with a pre-established welding spot quality evaluation model, and if the quality of a plurality of continuous welding spots is not qualified, it is judged that the welding spot quality is affected by welding head temperature field deviation.

The invention discloses a distributed reinforcement learning control method and system for multi-robot cooperative welding. A heterogeneous multi-robot task allocation algorithm, a multi-agent reinforcement learning model and welding parameters are combined. The method comprises the steps that a state space containing welding current, voltage, speed, welding gun posture, welding seam position and environment obstacle distribution is constructed, and an initial feasible operation area of the robot is determined; the overall welding task is decomposed into sub-tasks, and candidate robots are distributed; configuring a local decision module for each robot, and outputting an action decision containing a welding gun track adjustment amount and a parameter correction value; setting a global coordination module to generate coordination factors; each robot updates the decision and converts the decision into a driving instruction to execute operation, and molten pool temperature and weld size parameters are collected; the parameters are fed back to the model to adjust the state space characterization and decision weight. According to the method, decision collaborative precision is improved in combination with process parameters, self-adaptive optimization is achieved through real-time feedback, and collaborative welding efficiency and quality are improved.

The invention relates to the technical field of automatic welding control, and particularly discloses a multi-station automatic welding cooperative control method for electric iron accessories, which realizes full-closed-loop accurate control of a welding process through multi-sensor data fusion and an intelligent optimization algorithm. According to the method, an infrared thermal imager, an acoustic emission sensor and an ultrasonic thickness measuring device are adopted to collect molten pool temperature field, sound wave frequency spectrum and fusion depth data in real time, after feature extraction, the data are input into a multi-target optimization model, and a Pareto optimal solution set is generated with the fusion depth, the width of a heat affected zone and phase change latent heat as optimization targets; dynamically adjusting a segmented welding-back path and process parameters on the basis of an optimization result, and triggering model iterative correction through ultrasonic online monitoring; the central control unit adopts space voxelization monitoring and a three-level collision avoidance strategy to coordinate operation of the multiple mechanical arms, and collision emergency protection is achieved in combination with flexible pressure sensing.

The invention relates to the technical field of welding quality evaluation, in particular to a carbon steel pipe welding quality evaluation system which comprises a welding area three-dimensional scanning module, a welding seam dynamic grid generation module, a welding form change analysis module, a welding seam structure diagram construction module, a welding seam quality diagram convolutional network module and a welding defect intelligent recognition module. According to the invention, through real-time adjustment of the dynamic grid generation module, tiny changes of the geometric shape of the welding seam can be captured, new dimensions are provided for welding quality evaluation through generation of welding form characteristic data and construction of the welding seam structure diagram, and the introduction of the welding seam quality diagram convolution network module can improve the accuracy of welding quality evaluation. Node relations and structural features in a weld joint diagram structure are analyzed through a deep learning technology, an intelligent means is provided for welding quality evaluation, an intelligent welding defect identification module optimizes an identification process, various welding defects can be accurately classified, and a powerful technical support is provided for guarantee of welding quality.

The invention discloses a full-automatic laser welding forming system, which relates to the technical field of laser welding, and comprises a laser generation and light beam modulation module, a material conveying and positioning module, a welding execution module, a visual inspection and monitoring module, an intelligent self-adaptive control module and an energy recovery and reutilization module, the material module accurately conveys and positions materials; the welding module robot is accurate in operation; the visual module detects welding seams; the intelligent module performs self-adaptive control; the energy module recycles energy. The welding quality is improved, and defects are reduced; the production efficiency is improved and the cost is reduced; operation is simple, and manpower requirements are reduced; energy is saved, environment is protected, and green concept is met; real-time monitoring is achieved, and the product quality and the management level are guaranteed.

The invention discloses an intelligent welding method for machine tool manufacturing, which comprises a multi-sensor fusion module, a welding quality real-time evaluation module, a dynamic path planning module, a self-adaptive parameter adjustment module and a human-computer interaction interface, and the multi-sensor fusion module comprises a visual sensor, a laser ranging sensor and a temperature sensor; the welding quality real-time evaluation module is connected with the dynamic path planning module, the multi-sensor fusion module is integrated into a unified data set based on a defect detection algorithm of deep learning, and the dynamic path planning module is combined with 3D visual scanning to produce three-dimensional point cloud data of a workpiece. The dynamic path planning module generates a welding path through an ant colony optimization algorithm, the adaptive parameter adjustment module adjusts the welding state in combination with data collected by the multi-sensor fusion module, and the training process of the anomaly detection model is optimized in combination with the adaptive learning rate and the regularization technology. And the mechanical welding gun is adjusted and controlled through the human-computer interaction interface.

The invention discloses a welding device for switch cabinet production, which belongs to the technical field of switch cabinet production and comprises a support base, a transverse clamping and sliding mechanism, a longitudinal clamping and sliding mechanism and a diagonal follow-up self-adjusting positioning mechanism. The transverse clamping and sliding mechanism and the longitudinal clamping and sliding mechanism are arranged on the side wall of the sliding drive, the transverse clamping and sliding mechanism and the longitudinal clamping and sliding mechanism are perpendicular to each other, and the sliding drive is in transmission connection with the transverse clamping and sliding mechanism and the longitudinal clamping and sliding mechanism. According to the welding device for switch cabinet production, a plurality of metal plates are stably clamped, meanwhile, the anti-deviation welding mechanism is automatically aligned with the abutting joint gap of the two metal plates, plates can be automatically supported and positioned at the same time from the inner side and the outer side during welding according to switch cabinets with different sizes and design requirements, and the welding efficiency is improved. And dislocation and offset are avoided.

The invention provides an industrial robot automatic welding method and control equipment, and relates to the technical field of machine control. The method comprises the following steps: acquiring three-dimensional point cloud data of a workpiece, and adjusting a pre-constructed BIM model of the workpiece according to the three-dimensional point cloud data, so that the adjusted BIM model is aligned with an actual workpiece position; obtaining a theoretical welding seam path from the adjusted BIM model; acquiring an actual welding seam image of the workpiece; according to the actual welding seam image and the theoretical welding seam path, calibration parameters of the robot are determined, and a final welding path is determined according to the calibration parameters; and according to the final welding path and the material and thickness of the workpiece, a final control instruction set is determined, and the robot is controlled to conduct automatic welding according to the final control instruction set. The welding precision can be improved, meanwhile, manual intervention is not needed, the welding efficiency can be greatly improved, and the method can adapt to complex and changeable welding scenes.

A metal-part welding apparatus based on an angular direction change, comprising a base (1) and a welding torch body (2). The apparatus does not require the cooperation between two operators for welding, and by means of the welding torch body, circumferential weld seams can be automatically welded, thereby improving the work efficiency and welding precision. The present disclosure also relates to a metal-part welding method based on an angular direction change.

The invention relates to the technical field of artificial intelligence welding, and discloses an automatic welding robot based on artificial intelligence and a welding system thereof. The system comprises a welding feature acquisition module, a process parameter generation module, a real-time regulation and control module and a motion planning module. The welding characteristic acquisition module is used for acquiring three-dimensional contour data, material component information and welding seam geometric parameters of a workpiece to be welded, and generating a welding characteristic spectrum through characteristic fusion; a process parameter generation module retrieves a matching template from a welding knowledge base according to the parameters, and outputs a reference welding process parameter combination in combination with an environment temperature and humidity compensation coefficient; the real-time regulation and control module dynamically corrects the reference parameters to generate an optimization instruction according to the molten pool form, thermal radiation distribution and electric arc voiceprint characteristics in the welding process; and the motion planning module calculates a motion track, attitude parameters and a speed curve of the welding execution mechanism according to the optimization instruction to form a robot control instruction set. The system can improve the intelligent level of welding, guarantees stable welding quality, and is suitable for welding scenes of multiple manufacturing industries.

The invention discloses a welding device and method for metal corrugated pipe production, and relates to the technical field of metal pipe production. A sliding rail is arranged at the top of the base, a collecting box is arranged on one side of the back of the sliding rail, two linkage plates are symmetrically arranged in the sliding rail, an L-shaped plate is arranged at the edge of the top of the base, an annular rail is arranged on the side, close to the axis of the base, of the L-shaped plate, and a welding assembly is arranged in the annular rail. Two deviation prevention devices are symmetrically arranged on the top of the base, and anti-falling devices are arranged on the inner sides of the deviation prevention devices. By means of the inclined plate and the round roller, it is guaranteed that a pipe entering the limiting ring is located in the center of the interior of the limiting ring all the time, the phenomenon of slight deviation in the pipe alignment process is avoided, and workers need to observe the deviated direction with the naked eyes so that manual adjustment can be conducted; and the alignment accuracy between the two pipes is effectively improved, and the welding preparation time is shortened.

The invention discloses a mechanical arm welding detection intelligent diagnosis method and system based on laser ultrasonic guided waves. According to the system, a high-precision multi-degree-of-freedom steering engine, an infrared distance measurement array, a temperature sensor, a laser vibration exciter and a laser vibration meter are integrated at the tail end of a mechanical arm, synchronous operation of welding and online detection is achieved by presetting a welding track, and the system collects an excitation signal, a reflection ultrasonic signal and temperature data through a high-speed data collection card; and the signal is preprocessed through a temperature matching model, phase compensation and baseline correction. Then, wavelet decomposition is adopted to extract time-frequency features, intelligent diagnosis is achieved through a pre-trained one-dimensional convolutional neural network, a dynamic threshold value is set based on the 3 sigma criterion, and recheck feedback is automatically triggered when detection data exceed the limit, the welding detection efficiency and precision are remarkably improved through the scheme, data closed-loop management and intelligent quality tracing are achieved, and the reliability of welding detection is improved. And the automatic production requirement of modern steel structure manufacturing is met.

The invention discloses an automatic welding method and system based on a collaborative robot, and the method comprises the steps: collecting and preprocessing three-dimensional point cloud data of a to-be-welded steel part and the collaborative robot, and collecting thermal physical property data of to-be-welded steel; based on the three-dimensional point cloud data and the thermophysical property data of the steel, a welding simulation model is constructed through the digital twin technology; constructing a welding quality evaluation model based on a deep learning technology, and performing a virtual welding test by using the welding simulation model and the welding quality evaluation model to obtain an optimal welding route and optimal welding parameters; and based on the optimal welding route and the optimal welding parameters, the collaborative robot is started to conduct automatic welding. The invention relates to the technical field of automatic welding, and solves the technical problem that an existing automatic welding technology lacks welding parameter self-adaptive optimization and welding route intelligent planning through combination of a digital twinning technology and a deep learning technology.

A tooling fixture for welding an automobile accessory. The tooling fixture for welding an automobile accessory comprises a workbench (100), wherein transverse adjustment devices (200) are fixedly mounted on an upper side of the workbench (100), and a set of clamping devices (300) for clamping an automobile accessory is fixedly mounted at an adjustment end of each transverse adjustment device (200); and a support device (400) for supporting a welding position is provided on the workbench (100) and is located between the two sets of clamping devices (300). When the automobile accessory is welded, the automobile accessory can be clamped and fixed, thereby improving the welding quality.

The invention provides an inner flanging welding method of a water tank inner container and the water tank inner container, and relates to the technical field of welding manufacturing, and the inner flanging welding method comprises the following steps: obtaining three-dimensional point cloud data of an inner flanging interface of the water tank inner container in real time, and registering the point cloud data with a preset three-dimensional geometric model; based on an improved RRT algorithm, in combination with geometric features represented by the registered three-dimensional point cloud data, an initial motion track of a welding gun is planned; welding is conducted on the basis of the initial motion trail, and the weld width, the fusion depth feature and the defect feature are extracted from a molten pool image obtained in the welding process; correcting welding parameters of a welding gun in real time based on the weld width and fusion depth characteristics; and when the defect characteristics do not meet the preset conditions, path re-planning is triggered, a real-time movement track and synchronously-adjusted welding parameters are generated based on the currently-corrected welding parameters and the defect characteristics, and a welding gun is controlled to execute compensation welding. And the welding quality is improved.

The invention relates to the technical field of welding automation and robot visual perception, and discloses a robot intelligent welding method and system.The method comprises the steps that a three-dimensional point cloud image is constructed through a laser triangulation method; filtering and enhancing the point cloud image, and extracting a weld point cloud set by adopting a U-Net semantic segmentation model; carrying out space path identification and attitude regression based on the set to obtain a track element of a position-attitude pair; fitting a path by adopting a cubic B-spline curve and interpolating to generate a continuous welding track; and in the welding process, visual feedback is combined, and proportional differential control logic is introduced for closed-loop track error compensation. Compared with the technical problem that in the prior art, weld joint path recognition and accurate tracking cannot be stably achieved under complex structures such as curved surfaces and variable cross sections, a perception control closed loop based on visual servo is constructed, high-precision automatic welding of the complex weld joint structures is achieved, and the track fitting precision is improved.

The invention relates to the technical field of steel box girder welding, and particularly discloses a steel box girder welding device and method.The steel box girder welding device comprises a platform, a movable frame body and a welding mechanism, the movable frame body is provided with a bearing frame, and the bearing frame is provided with a rolling assembly and a first driving assembly for driving the rolling assembly to abut against the top face of a U-shaped rib of a steel box girder; the bearing frame is provided with two symmetrically-distributed clamping assemblies and a second driving assembly for driving the clamping assemblies to abut against the two side faces of the U-shaped rib, each clamping assembly comprises a mounting frame and a clamping plate connected to the mounting frame, a crawler belt is arranged on the periphery of each clamping plate, and the mounting frame is provided with a third driving assembly for driving the crawler belt to rotate; the third driving assembly drives the crawler belt to rotate to be matched with the moving speed of the moving frame body, so that sliding friction does not occur between the crawler belt and the U-shaped rib. According to the steel box girder welding device and the welding method, the abrasion of the U-shaped rib caused by sliding friction is avoided, and the stability of the moving process of the movable frame body and the continuous proceeding of the welding operation are ensured.

An automatic welding production line for a large complex workpiece includes a base station, a welding robot, a displacement worktable, an auxiliary robot, a feeding system and a blanking system. The displacement worktable has multi degrees of freedom, the position and angle of the workpiece can be flexibly adjusted during welding to meet the welding requirements of any position and angle of the welding equipment, thereby realizing the welding operation of large complex special-shaped three-dimensional components, and multi-point welding at any point can be realized through the cooperation of the welding robot and the auxiliary robot. The control system controls the robot and the feeding and blanking system to cooperate with the displacement worktable to realize automatic feeding, welding and blanking operations, the welding parameters and operations can be automatically adjusted for the special components of the structure, to realize integration and intelligence, improve production efficiency and reduce production costs.

The invention provides an industrial robot welding track real-time optimization method and system based on deep learning, and relates to the technical field of industrial robots, and the method comprises the steps: collecting three-dimensional point cloud data, carrying out the multi-scale processing to generate a high-precision curved surface, constructing a welding seam feature descriptor, and carrying out the real-time optimization of the welding track of an industrial robot; and the mapping relation between the technological parameters and the welding posture is optimized on the basis of a multi-target reward function, the mapping relation is converted into an initial movement track, the track is dynamically optimized through a segmented self-adaptive optimization model and a variable structure filtering algorithm, and self-adaptive adjustment of the welding process is achieved. The welding precision and quality of the complex curved surface are improved, and the adaptability and stability of robot welding are enhanced.

The invention discloses a body-in-white welding seam recognition and automatic welding method based on a machine vision technology, particularly relates to the technical field of computer vision and image processing, and is used for solving the problem of welding seam track recognition accuracy caused by insufficient processing capability of an existing three-dimensional vision recognition method on incomplete and uncertain point cloud data. Through the steps of multi-view point cloud acquisition and registration, probabilistic confidence evaluation, region growth of track continuity constraint, multi-track fusion optimization and the like, accurate identification of a body-in-white welding seam track under a complex working condition is realized; firstly, multi-view point cloud data are obtained, probabilistic registration is carried out to generate a confidence evaluation result, then candidate tracks are generated based on confidence weighting and semantic constraint, finally, an optimal track is generated through intelligent optimization and converted into a welding instruction which can be executed by a robot, and the accuracy and robustness of weld joint recognition are effectively improved.

An overturning clamp for automobile plate machining relates to the technical field of overturning clamping tools and comprises a clamping base, and a conveying overturning assembly, a transferring overturning assembly, a reversing overturning assembly and a butt-joint overturning assembly are sequentially arranged on the clamping base. The conveying and overturning assembly comprises a conveying belt rolling circularly, and an inclined conveying clamping plate is fixed to the outer surface of the conveying belt. The conveying and overturning assembly further comprises an overturning positioning barrel, two cylindrical sliding seats are arranged in the overturning positioning barrel in a telescopic mode, and four feeding clamping seats are arranged on each cylindrical sliding seat in a telescopic mode. The transferring and overturning assembly comprises a U-shaped overturning mounting frame; a strip-shaped overturning plate is rotationally arranged on the overturning mounting frame, and rotating chucks are arranged at the two ends of the strip-shaped overturning plate. The problems that when an overturning clamp in the prior art is used for machining, clamping and overturning of automobile plates, the feeding and overturning efficiency and the automation degree are low, the plate posture adjusting flexibility is poor, the butt joint or lap joint precision of multiple plates is low, and the clamping stability is insufficient are solved.

A method for manufacturing a continuous torque tube of a solar tracking system on site includes the steps of: placing raw material at a rolling apparatus on site; shaping the raw material into torque tube components at the rolling apparatus on site; joining the shaped torque tube components output from the rolling apparatus on site to create a continuous torque tube; and placing solar modules at the continuous torque tube to create a continuous solar tracker row.

The invention relates to the technical field of electronic packaging, in particular to a welding process applied to a double-mesa device. The technology comprises the following steps that firstly, a heat conduction model of a double-table-board device is built, a temperature field prediction system is built in combination with measured data, secondly, an asymmetric double-pulse-current welding strategy is adopted, differential pulse waveforms are loaded to an upper table board and a lower table board respectively, independent temperature control over all welding areas is achieved, a temperature difference closed-loop feedback mechanism is introduced in the process, and the temperature field prediction system is obtained. Pulse parameters are dynamically adjusted according to real-time temperature deviation, a stress prediction and weld penetration monitoring module is used for assistance, the welding spot forming quality and heat stress balanced release are ensured, a staged annealing type cooling mode is adopted after welding, and the structural stability is improved. The method can be widely applied to MEMS modules, SiC power devices and heterogeneous chip laminated packaging double-mesa structure devices, and has the advantages of being high in welding precision, high in reliability and wide in process adaptability.