1989 results about "Molten pool" patented technology

The invention provides an intelligent real-time detection method and system for PCCP welding quality, and relates to the technical field of online detection and intelligent evaluation of pipeline welding quality through machine learning. Light energy data and multi-light-source images of a spiral weld pool are collected, exposure parameters are dynamically adjusted through the energy difference of visible light near-infrared bands, and the real-time detection of the PCCP welding quality is achieved. Inhibiting strong light interference and generating a weld surface image; a stress concentration area is positioned by scanning a welding seam thermal deformation area and combining speckle pattern change, sound frequency change and the elastic characteristic of the thin-wall steel cylinder; inputting the surface image and the deformation data into a space-time convolutional neural network, fusing light energy change, image details and spatial features to construct a weld joint space structure diagram, and adaptively correcting the position of a sensor; and comparing the sinking depth of the three-dimensional point cloud reconstruction, analyzing the correlation between the sinking degree and the stress, and generating a probability thermodynamic diagram to output the pressure-bearing failure risk level, so that the probabilistic early warning of the pressure-bearing failure risk can be realized.

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 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 an intelligent welding quality evaluation method and system based on vision, and relates to the technical field of welding quality evaluation.The method comprises the steps that the welding process is monitored in real time through multi-mode imaging equipment, weld joint surface texture, molten pool heat distribution and three-dimensional shape information are synchronously obtained, and a three-dimensional voxel model is constructed; establishing a two-stage multi-channel architecture for executing dynamic resource scheduling, and extracting geometric features and deep semantic features in the three-dimensional voxel model; and on the basis of the defect confidence coefficient vector, in combination with the real-time process parameters and the molten pool state, a dynamic evaluation model of the welding quality index is constructed, and time-phased quality scores are calculated and output through stage weighting. According to the method, the welding seam surface texture, molten pool heat distribution and three-dimensional shape information are synchronously collected through multi-mode imaging equipment, a texture-temperature-space coordinate bound three-dimensional voxel model is constructed, and multi-source heterogeneous data fusion analysis of the welding quality is achieved.

The invention discloses a gradient welding strength control method and system for a welded galvanized steel pipe for fire fighting, particularly relates to the technical field of welding automation control, and aims to solve the problem of abnormal welding seam strength gradient caused by instantaneous unbalance of an electric field and a thermal field during dynamic parameter switching in the prior art. Electromagnetic distortion characteristic quantity is extracted through frequency domain energy analysis, and thermodynamic offset state quantity is deduced in combination with a thermal diffusion trend; on the basis of frequency band correlation mapping of electromagnetic and thermodynamic parameters, thermoelectric cooperative imbalance levels are divided through mutual information entropy evolution, and a self-adaptive harmonic attenuation weight tuning instruction is generated; analyzing a mismatching relation between transient disturbance of an environment magnetic field and arc voltage modulation distortion in real time, dynamically generating a magnetic field compensation factor and reversely superposing the magnetic field compensation factor to a control instruction; and in combination with the matching degree of molten pool oscillation energy and a harmonic frequency spectrum, correcting wire feeding rate calibration, reconstructing a multi-band harmonic energy proportion spectrum, outputting an anti-interference welding control signal, and realizing dynamic balance between arc stability and molten pool heat input.

The invention discloses a dynamic monitoring and analyzing method for a thermal management component molten pool based on image recognition, and relates to the technical field of laser powder bed melting additive manufacturing. The method comprises the following steps: continuously capturing an original thermal management component molten pool image and temperature field distribution data during laser powder bed melting additive manufacturing; and optimizing the original thermal management component molten pool image to generate an optimized thermal management component molten pool image. Molten pool images and temperature field data are captured in real time through a high-frame-rate synchronous camera and an infrared sensor, defect types are recognized online in combination with a lightweight classification model, classification results are fed back to a control system to dynamically adjust laser power or scanning speed, interlayer defect accumulation can be inhibited in time, and the defect quality is improved. The defect diffusion problem caused by response lag of a traditional off-line analysis method is avoided, and the forming precision and the process stability of the heat management component are remarkably improved.

The invention discloses an intelligent welding control system and method based on multiple sensors and electronic equipment, and belongs to the technical field of automatic welding, the system comprises a sensing layer, a decision-making layer and an execution layer, through cooperative work of a front laser vision sensor, a rear laser vision sensor and a molten pool image sensor, a groove three-dimensional model can be accurately established before welding, and the welding precision is improved. And dynamic information of the molten pool is continuously collected in the welding process, a dual monitoring mechanism for the geometric characteristics of the welding line and the state of the molten pool is formed, and multi-source data collection and fusion in the whole welding process are achieved. The control method comprises the steps of pre-scanning modeling, feedforward parameter planning, real-time feedback adjustment of a molten pool, data fusion optimization and the like, and high-precision self-adaptive control over welding parameters is achieved by combining deep learning and the Kalman filtering technology. According to the method, the welding adaptability, the control precision and the intelligent level can be remarkably improved, and the method is suitable for high-precision welding scenes such as pipelines, pressure containers and steel structures and has remarkable engineering application value and popularization prospects.

The invention relates to the technical field of welding, and discloses an intelligent control method and system for the welding process of a thin-wall metal component, and the intelligent control method for the welding process of the thin-wall metal component comprises the steps that an initial welding parameter set is determined, and time synchronization is conducted; obtaining multi-source original data with timestamps in the welding process; time alignment is carried out; respectively calculating a current stability index, a heat accumulation index and a molten pool width measured value to obtain a key deviation index; based on the key deviation index, current adjustment amount, pulse parameter adjustment amount and position compensation amount are obtained through calculation; obtaining an adjustment amount set; the current welding parameters are subjected to amplitude limiting updating, and an updated current welding parameter set is obtained through a step-by-step transition method and a high-priority fast instruction; recording a welding process data log, and judging a welding state; carrying out comprehensive evaluation and data storage on the welding process; according to the method, various dynamic changes in the welding process are comprehensively coped with, and the stability and consistency of the welding quality are improved.

The invention discloses a laser energy threshold millisecond-level dynamic matching method for multi-metal fuse manufacturing, and the method comprises the steps: pre-storing a multi-metal thermophysical parameter model, calibrating a thermal signal in real time through Kalman filtering, and carrying out the online correction of a melting threshold key parameter during the switching of a material; millisecond-level thermal feedback closed-loop control is achieved through the high-frame-rate thermal imaging technology, and the laser power accurately follows the corrected melting threshold value; meanwhile, a three-dimensional imaging and deep learning segmentation algorithm is adopted, geometric information of a welding wire and a molten pool is obtained, the position and the diameter of a light spot are adjusted in real time through an adjustable optical system after the offset is calculated, and millimeter-level space registration closed-loop control is achieved; the two closed-loop systems cooperatively operate according to respective control periods, and precise dynamic matching of laser heat input in a time domain and a space domain is achieved. The problem that the adaptability of a traditional process is insufficient during multi-metal switching and complex geometric change is solved, and the forming quality, the process stability and the efficiency of manufacturing are remarkably improved.

The invention relates to the technical field of welding parameter correction, and provides a welding parameter correction method for real-time molten pool morphology feedback, which comprises the following steps of: capturing a molten pool image, an arc spectrum and an infrared radiation signal in real time, accurately extracting geometrical characteristics and contour vibration frequency of a molten pool, and dynamically evaluating arc stability and a thermal attenuation state. And when defects are detected, welding parameter correction is generated based on a process knowledge graph and Bayesian reasoning, collaborative correction of parameters such as welding current, welding voltage and welding speed is achieved through reinforcement learning optimization weight distribution, and the change trend of morphology characteristics of a molten pool is continuously monitored after correction. According to the method, the depth belief network is judged and optimized by combining the descending rate of the morphology defect probability, and the corrected successful case is supplemented to the process knowledge graph, so that the welding quality stability is remarkably improved, the method is particularly suitable for automatic production of a high-precision welding scene, the defect rate can be effectively reduced, and the production efficiency can be effectively improved.

The invention discloses a welding robot self-adaptive wire feeding control method, a platform and a medium, relates to the technical field of welding automation process control, and is suitable for welding process management under complex working conditions. According to the method, an arc voltage sequence and a molten pool characteristic parameter sequence in the welding process are collected, a welding state characteristic value is obtained through calculation, a reference database containing welding process parameters, welding working condition parameters and the welding state characteristic value is constructed based on historical experimental data, and corresponding preset reference indexes are generated through a mapping relation function; and in real-time welding, the welding state characteristic value of the current wire feeding control period is obtained and compared with a preset reference index, the deviation value is calculated, the welding state is judged according to the grading threshold value interval, the wire feeding speed is dynamically adjusted, and self-adaptive matching of the wire feeding speed and the welding state is achieved. According to the method, instability caused by traditional adjustment depending on experience can be overcome, dynamic control over the welding process is achieved, and the stability of a welding pool and the welding seam forming quality are improved.

The invention relates to the technical field of welding automation, and discloses an intelligent welding system for an electric pole steel reinforcement framework. The system comprises a welding execution module, a multi-mode sensing module, an edge calculation module, a real-time regulation and control module and a system control center. Synchronous collection and real-time analysis of images, temperature and sound signals of a welding pool area are achieved, so that defects such as air holes, slag inclusion and incomplete fusion can be recognized online in a key time window when the welding pool is not solidified, and time delay caused by a traditional off-line detection mode is thoroughly eliminated. Through a real-time regulation and control module, on the basis of a multi-target optimization decision and parameter self-adaptive adjustment mechanism, the system can dynamically adjust key process parameters such as welding current, arc voltage and welding speed at the moment of identifying defect germination or process deviation, and real-time intervention and closed-loop control on welding quality are achieved; therefore, the final formation of defect welding seams is avoided fundamentally, and the rework rate and the material waste are remarkably reduced.

The invention relates to the field of welding quality detection, and discloses a steel structure welding quality detection method and system based on machine vision, and the method comprises the steps: obtaining an original welding seam image sequence through high-frequency sampling, and carrying out the preprocessing to generate a clear sequence; extracting features from the sequence to obtain a welding seam static defect index; time sequence data are constructed according to the time arrangement characteristics, and a dynamic time sequence data set is obtained by calculating the welding seam symmetry fluctuation amplitude and the molten pool shape change trend; inputting the data set into a neural network model, analyzing a surface profile curve time sequence evolution mode, and determining potential defect points; extracting a crack period amplitude sequence from the potential defect points, and performing Fourier transform to obtain a defect frequency distribution diagram; extracting a frequency peak value position from the graph, judging process parameter deviation, generating an alarm and updating a database; and determining a sampling frequency deviation value according to the alarm, adjusting the high-frequency sampling frequency through feedback circulation, and optimizing dynamic detection. According to the invention, the detection real-time performance, the accuracy and the parameter adjustment accuracy are improved.

The invention relates to the technical field of laser deposition control, in particular to an unmanned aerial vehicle metal part ultrasonic field auxiliary laser deposition system which comprises the following modules: a data acquisition module for acquiring a molten pool thermal field signal, a sound field signal and a laser scattering signal, and performing sampling, filtering and synchronous processing to obtain molten pool original data; the micro-flow digital twinning module is used for establishing a molten pool micro-flow digital twinning model according to the molten pool original data and simulating molten pool micro-flow behavior to obtain micro-flow prediction data; and the microflow ultrasonic regulation and control module is used for generating an ultrasonic pulse sequence according to the microflow prediction data and applying the ultrasonic pulse sequence to the molten pool to regulate and control the flow field. According to the invention, through the molten pool microflow digital twinning module and the microflow ultrasonic regulation and control module, real-time modeling and regulation and control of the molten pool microflow structure in the complex geometric part deposition process are realized, the problem that local vortexes, shear layer differences and flow field anomalies cannot be identified in real time in the traditional technology is solved, and the molten pool microflow evolution can be actively reconstructed.

The invention provides a swing control method based on molten pool oscillation multi-feature fusion and related equipment, and relates to the technical field of welding, the method comprises the steps that in the argon arc welding process, an electric arc signal and a molten pool oscillation signal of a variable wall thickness welding area are collected in real time; oscillation amplitude, main frequency characteristics, current fluctuation coefficients and voltage-current phase difference characteristics are extracted from the molten pool oscillation signals and the electric arc signals and combined, and an oscillation comprehensive characteristic matrix is obtained; inputting the oscillation comprehensive characteristic matrix into a pre-trained classification model, and identifying a current molten pool state type; a corresponding swing compensation strategy is matched according to the state type of the molten pool, and asymmetric swing parameters are generated; and the asymmetric swing parameters and a preset basic welding track are subjected to superposition operation, and a composite control instruction is generated to control a welding gun to execute asymmetric swing welding. By implementing the method, different abnormal states of different molten pools can be subjected to differential control, and the stability of the variable-wall-thickness welding process and the forming quality of a final weld joint are improved.

The invention discloses a nickel-based alloy additive manufacturing method for high-frequency ultrasonic dynamic forging printing. The method comprises the steps that nickel-based alloy powder and a base plate are pretreated; scanning the nickel-based alloy powder layer by layer through laser to form a molten pool; in the machining process of each layer, when the temperature of the molten pool ranges from 1000 DEG C to 1400 DEG C, ultrasonic waves are activated to generate compound vibration; the composite vibration comprises axial vibration and transverse vibration; when the ultrasonic vibration phase difference reaches a preset first interval, short pulse laser is triggered; the ultrasonic vibration phase difference is a phase deviation between an ultrasonic vibration waveform and a pulse laser shock triggering moment; and until all layers are machined, a formed part is obtained. According to the scheme, the dislocation density is improved, secondary grain refinement and bubble escape are achieved, and interlayer stress redistribution is made uniform.

The invention relates to the technical field of double-roller cast rolling, and provides a roller gap control method. According to the method, in the casting and rolling process, controlled floating of a roll gap is achieved under the condition of constant opening degree by controlling the overall movement of a driving device and a roll system and the relative movement between the driving device and the roll system, and therefore the material updating process in a molten pool is stabilized. Different from a traditional technical scheme, the method can keep the two roller bodies and the side sealing device static relative to the ground in the roller gap floating period, the thickness fluctuation of the green body is effectively avoided, the abrasion rate of the side sealing plate is reduced, and therefore the stability of the cast-rolling process and the quality of the green body are improved.

The invention relates to the technical field of laser welding, and discloses a laser welding method for accurately controlling weld penetration. According to the invention, through fusion of coaxial multispectral sensing and a back monitoring unit, multi-dimensional information synchronous acquisition of weld front molten pool morphology, a temperature field and a back thermal radiation signal is realized, and limitation of single sensing is overcome; furthermore, a dynamic instruction is generated based on the extracted multi-characteristic parameters and an adaptive fuzzy PID algorithm, thereby realizing precise closed-loop control of laser energy and heat input, and improving real-time performance and robustness of control. Particularly, a digital twin model is introduced to carry out forward prediction, cross validation is carried out with back monitoring signals, a triggered lead compensation mechanism effectively overcomes hysteresis of traditional feedback control, finally, precision control and stable forming of weld penetration are achieved, the defects of incomplete penetration, burnthrough and the like are effectively avoided, and the welding quality is improved. And the device is particularly suitable for occasions with extremely high welding quality requirements.

The invention provides a self-adaptive variable-parameter composite swing welding control method and related equipment, and relates to the technical field of welding. The method comprises the steps that real-time multi-physics field sensing data is obtained; inputting the real-time multi-physical field sensing data into a simulation model for predicting the behavior of the molten pool, and outputting a state parameter predicted value of the molten pool in a future preset time period; matching a composite swing track parameter corresponding to the molten pool state parameter predicted value from a preset database; and when the welding gun enters the residence area of the welding seam swing edge according to the macroscopic reference track, the tip of the welding gun is controlled to execute asymmetric spiral oscillation motion in the preset residence area according to the microcosmic modulation track until the tip leaves the preset residence area. By implementing the method, the problems of edge overheating, undercut or insufficient fusion caused by fixed parameters can be relieved, and the welding seam forming quality and the stability of the welding process are improved.

The invention relates to a low-power pulse laser-induced enhanced double-TIG (Tungsten Inert Gas) composite heat source medium-thickness plate narrow-gap efficient welding method, which adopts two independent TIG welding machines, a pulse laser and a wire feeder, and two TIG welding guns are positioned in a narrow-gap groove on the same side of a plane on which a laser beam perpendicular to the plate welding direction is positioned, the angle and distance of each heat source can be independently adjusted, before welding, the space angle and distance among the two TIG welding guns, laser beams and welding wires are adjusted, tungsten electrodes at the front ends of the two TIG welding guns and the laser beams emitted by a laser device are arranged in the corresponding space range, and a plate to be welded and the welding wires can obtain sufficient heat for melting, wetting and spreading; during welding, welding parameters are adjusted, the coupling plasma energy density in the narrow gap space range is controlled, and the droplet transition behavior of a welding wire and the flow characteristic of a molten pool are adjusted and controlled in real time. Compared with traditional arc welding, the welding process window can be improved, and the welding deposition efficiency is improved by more than 10 times.

The invention provides a narrow gap swing laser welding pool wettability prediction method based on CFD simulation. The method comprises the following steps that an interaction platform is constructed through Python + PyQt5, and geometric modeling, UDF compiling and a material library module are integrated; the groove parameters and the swing track are dynamically loaded to a Fluent solver, and a full-coupling transient model of a steam recoil pressure-buoyancy-molten drop mass source item is established; in CFD-POST, the widest section of the molten pool is positioned on the basis of the contour surface with the volume fraction being 0.5, and Z-direction displacement-flow velocity data are extracted along the two side wall surfaces; fusing defects are predicted through double criteria of a bilateral average flow velocity difference threshold value and F test variance homogeneity; according to the method, dynamic quantitative evaluation of wetting behaviors can be achieved, the process development period is shortened, the defect detection rate is increased, and the method is suitable for aerospace thick plate welding quality control.

The invention provides a method and system for on-line determination of molten steel carbon content in converter steelmaking, and relates to the technical field of converter steelmaking, the method comprises the following steps: obtaining multi-source process data, the multi-source process data comprising exhaust gas components, furnace mouth flame multispectrum and process parameters; performing time synchronization and feature extraction on the multi-source process data to generate a feature vector; inputting the feature vector into a carbon content prediction model to obtain a carbon content prediction value and an uncertainty estimation value thereof; the molten pool temperature is obtained, and based on the molten pool temperature, the waste gas components and the technological parameters, a theoretical carbon content value is calculated through a thermodynamic carbon content calculation model; and carrying out weighted fusion on the carbon content predicted value and the theoretical carbon content value to generate a fused carbon content as a target carbon content. According to the method and system for online determination of the carbon content of the molten steel in converter steelmaking, the precision and reliability of online determination of the carbon content of the molten steel can be effectively improved, and powerful support is provided for intelligent production of converter steelmaking.

The invention provides a full-laser multi-energy-field remanufacturing device and method, and relates to the technical field of laser cladding remanufacturing, and the full-laser multi-energy-field remanufacturing device comprises a laser system, an energy field auxiliary system, a powder conveying system, a monitoring system and an intelligent management and control system; the energy field auxiliary system comprises a magnetic field generation unit and an ultrasonic vibration unit; the monitoring system is used for collecting multi-source sensing data reflecting the state of the molten pool in real time; the intelligent management and control system comprises a machine learning digital twinning module used for acquiring historical process data and receiving and performing analysis and prediction based on multi-source sensing data and the historical process data so as to generate a dynamic cooperative control instruction; and the numerical control execution module is used for receiving the control instruction and performing real-time feedback adjustment on the technological parameters of the laser system and the technological parameters of the magnetic field generation unit, the ultrasonic vibration unit and the powder conveying system according to the control instruction. And real-time and dynamic collaborative feedback regulation and control on a plurality of process units such as laser, a magnetic field, an ultrasonic field and powder feeding are realized.

The invention relates to the technical field of additive manufacturing, and discloses a method and equipment for restraining the crack defect of a high-temperature alloy difficult to weld in laser additive manufacturing. When the gradient of a first molten pool is larger than a preset temperature gradient threshold value, a metal powder scanning area corresponding to each layered slice of a target part can be fused through a composite laser spot; the central light spot is used for providing enough energy to melt metal powder and form a stable molten pool, and the annular light spot preheats the periphery of the molten pool to adjust temperature distribution of the molten pool. The second laser power needed by the annular light spot is determined according to the molten pool center temperature and the molten pool radius generated by the center light spot in the scanning area at the preset scanning speed, so that accurate control over the gradient and the cooling rate of the molten pool is met, the molten pool can be cooled more uniformly in the solidification process, and the solidification quality of the molten pool is improved. The defects of cracks, air holes and the like caused by high temperature gradient and high cooling rate are effectively reduced, and the problem that high-performance high-temperature alloy laser additive manufacturing cracks are difficult to weld is solved.

The invention belongs to the technical field of welding process optimization, provides a pipeline welding parameter optimization method and system for natural gas conveying system construction, and is used for solving the technical problems of high hydrogen-induced cracking risk, parameter dependence on artificial experience and optimization process isolation lag in shallow hydrogen natural gas conveying pipeline welding. According to the method, a visual image of a molten pool, a joint thermal field, electric arc electrical parameters and environmental data are synchronously collected through a multi-source sensor, a hydrogen diffusion-thermal coupling model is constructed to calculate hydrogen concentration and stress, after reference parameters of a knowledge base are called, current, voltage and speed adjustment amounts are generated through a GBDT algorithm, and then real-time correction is conducted through a closed-loop module. According to the method, hydrogen-induced cracking can be quantitatively prevented and controlled, the weld joint failure probability in the shallow hydrogen environment is reduced, the process robustness and quality consistency are improved, the safe service life of the pipeline is effectively prolonged, and the high-safety energy conveying requirement is met.

The invention provides a metal printing control method, electronic equipment, a system and a storage medium, and is applied to the technical field of additive manufacturing. The method comprises the steps that multi-dimensional monitoring data of the metal printing process are obtained, wherein the multi-dimensional monitoring data at least comprise a molten pool visual image, molten pool temperature field distribution, printing layer three-dimensional shape data and forming cabin environment data; performing corresponding dimension feature extraction on each dimension of monitoring data in the multi-dimensional monitoring data to obtain a multi-dimensional feature parameter; based on the multi-dimensional characteristic parameters, performing evaluation to obtain a state evaluation result; according to a state evaluation result, determining a to-be-adjusted process parameter and a target adjustment amount corresponding to the process parameter; and according to the target adjustment amount, an execution mechanism corresponding to the technological parameters in the metal printing control system is controlled to act so as to correct the printing state. The method is used for achieving the effects that the printing yield is improved, the printing quality is guaranteed, and then the process quality and the process stability of the metal parts are effectively guaranteed.

The invention belongs to the technical field of smelting furnace intelligent control, and particularly relates to an intelligent smelting furnace for titanium alloy heating, which comprises a data acquisition module, an arc stability judgment module, a position adjustment control module and a feedback adjustment module. And the voltage and current variation coefficient weight design is dynamically adjusted based on the electrode consumption height, the change of the current fluctuation sensitivity after electrode consumption is adapted, real-time accurate quantitative evaluation of the arc stability is realized, the abnormal state of the consumable electrode can be timely and accurately identified, and through the morphological characteristics of the molten pool and the arc deviation characteristics, the arc quality is improved. According to the method, an adjustment vector containing height and transverse displacement is generated, the smelting defects such as molten pool writhing, local overheating and component segregation caused by insufficient adjustment pertinence are avoided, finally, weight distribution and adjustment coefficients are dynamically optimized through a feedback mechanism, and the electric arc stability control and adjustment accuracy is remarkably improved.

The invention discloses a B-type sleeve welding control system and method, and belongs to the technical field of welding automation, and the B-type sleeve welding control system comprises a welding trolley, a welding gun, a visual perception unit and a control unit. By constructing a composite sensing system combining laser vision, molten pool recognition and welding gun sounding calibration, continuous and effective positioning in a narrow space in the sleeve under the condition that multiple layers of welding beads cover layer by layer is achieved. A welding gun is used for conducting welding wire penetration detection in a set coordinate system, space point positions are recorded in real time when the end of a welding wire makes contact with a sleeve and a base metal entity, self-adaptive correction of a welding bead starting point and a swing center is achieved, the positioning precision in the welding process of multiple layers of welding beads is greatly improved, and reliable reference is provided for follow-up path planning of the welding beads. A multi-sensor fusion algorithm is adopted, parameters such as the swing amplitude, the swing frequency, the welding height and the walking speed in the welding process are adjusted in real time, and the forming quality consistency of multiple layers of welding seams can be guaranteed.

The invention relates to the technical field of bridge construction, and discloses a bridge steel member welding parameter self-adjustment control system and method.The bridge steel member welding parameter self-adjustment control system comprises an acoustic sensing module used for simultaneously obtaining real-time feedback data reflecting the geometric morphology of a current molten pool and feedforward data reflecting disturbance in front of a welding path; the feedback calculation module is used for calculating a feedback adjustment amount according to the deviation between the feedback data and a preset target; and the feed-forward calculation module is used for calculating a feed-forward adjustment amount according to the feed-forward data so as to suppress disturbance in advance. By combining direct feedback control of geometric morphology in a molten pool, predictive feedforward control of front disturbance and online self-adaptive updating of a control model, accurate closed-loop control over key indexes such as penetration depth can be achieved, meanwhile, sudden disturbance such as groove change is actively coped with, material characteristic change in the welding process is adapted, and the welding quality is improved. Therefore, the welding quality and stability of the bridge steel member under the complex dynamic working condition are remarkably improved.

The invention relates to the field of mechanical engineering, discloses a quick-connection welding control method and system for aluminum alloy pipe fittings, and aims to solve the problems that in the prior art, heat input control is not accurate, the positioning and centering efficiency is low, parameter adjustment lacks self-adaptability, and the multivariable cooperative control capacity is insufficient. The method comprises the following steps: acquiring point cloud data of the end surface of a pipe fitting through three-dimensional scanning, and calculating a six-degree-of-freedom butt joint deviation by adopting an improved iterative nearest point algorithm; a compensation track is generated based on multi-objective optimization, and the six-degree-of-freedom parallel robot is driven to achieve fine adjustment; and after the butt joint deviation is stable, welding is started according to a sectional type current increasing strategy, and the wire feeding and welding speed is dynamically adjusted in combination with fusion depth feedback and visual detection. According to the scheme, high-precision automatic butt joint, stable molten pool control and online defect closed-loop treatment are achieved, the welding quality consistency and the production efficiency are remarkably improved, and the method is suitable for efficient and high-quality connection of various aluminum alloy pipe fittings.