3202results about "Arc welding apparatus" patented technology

The invention relates to the technical field of welding platforms, in particular to a multifunctional welding process experiment platform and a process optimization system.The process optimization method comprises the following steps that a welding process setting module is constructed, and a welding mode, a groove type and a heat input scheme are preset; outputting the initial process configuration parameter set to drive a welding execution unit to perform automatic welding operation according to the initial process configuration parameter set; extracting a multi-dimensional process response vector including a stability index, metal fusion depth distribution and a heat affected zone expansion degree; outputting a welding seam grade result according to a preset quality grading standard, and generating a feedback identifier; and after updating, inputting to the step S2 again to form closed-loop optimization control. According to the method, digital modeling and evaluation of key indexes such as the welding stability, the fusion depth and the heat affected zone are achieved, and the problem that a traditional process depends on visual inspection and experience judgment is solved.

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 relates to the technical field of metal welding automation control, in particular to a metal welding seam automatic tracking welding system based on machine vision. Comprising a data acquisition module used for acquiring initial three-dimensional geometric parameters of a welding seam and monitoring welding process parameters including welding current, arc voltage and welding speed; the thermal deformation prediction module is used for solving a weld joint thermal deformation displacement vector; the dynamic deviation evaluation module is used for calculating a dynamic deviation index; the risk grading module is used for judging the trajectory deviation risk as safety, first-level risk or second-level risk; the defect tendency prediction module is used for calculating an incomplete fusion index and a hot crack index; the comprehensive risk assessment module is used for determining a comprehensive process risk factor; and the track correction module is used for generating a corrected welding gun target track so as to carry out closed-loop correction control on the welding process. According to the method, the problem of trajectory deviation caused by thermal hysteresis and dynamic deformation is solved, and the tracking precision and stability of the welding path 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 provides a pipeline welding all-position welding seam identifying and tracking system and method, and belongs to the technical field of pipeline welding automation. In order to solve the problems of strong arc light interference, low tracking precision, slow response speed and insufficient robustness in the existing pipeline all-position welding tracking technology, the system comprises a sensing layer, a processing layer, a decision-making layer and an execution layer. The welding seam identifying and tracking method comprises the following steps: S1, calibrating the welding seam identifying and tracking system; s2, all-position welding tracking is carried out; and S3, performing adaptive adjustment on different scenes. According to the method, dynamic weighted fusion and fuzzy PID control are adopted, multi-posture welding such as flat welding, vertical position welding, horizontal position welding and overhead position welding can be automatically adapted, parameters do not need to be manually adjusted, and the operation threshold is lowered.

The invention relates to the technical field of process optimization, in particular to a collaborative optimization analysis method for multi-station tower drum welding. In order to solve the problem that cooperative control of tower drum multi-station welding is difficult, firstly, multi-mode sensing data of welding seam vision, arc sensing, thermal field distribution and welding voiceprint are loaded, a fusion evaluation model is constructed to obtain a welding seam deviation value and a sensor confidence score, and the health state of a sensor is judged according to a threshold value; and a corresponding fault-tolerant reconstruction control mode is triggered to obtain welding tracking control parameters, then a multi-station welding heat source model is loaded, thermal interference is decoupled in combination with the control parameters and thermal field data, multiple stations are cooperatively regulated and controlled, a cooperative control instruction is output and executed, and welding process optimization is achieved.

The invention relates to the technical field of welding quality detection, in particular to a surfacing process quality monitoring method, system and equipment, and the method comprises the steps that a dynamic parameter set of the surfacing process is obtained in real time, and the dynamic parameter set comprises arc characteristic parameters, temperature field distribution parameters and mechanical state parameters; setting an edge computing node, accessing the welding quality prediction model, inputting a dynamic parameter set, and outputting a quality evaluation result containing a defect probability and a fusion depth prediction value; a welding parameter adjusting instruction is generated based on the quality evaluation result, and the operation states of a welding power source and a wire feeding mechanism are adjusted in real time; and updating the dynamic parameter set according to the welding parameter adjusting instruction and transmitting the dynamic parameter set to the industrial control switchboard based on the edge computing node. According to the invention, the problem of uncontrollable instantaneous quality fluctuation caused by strong coupling of multiple physical fields in the surfacing process is effectively solved.

The invention relates to the technical field of metal net welding, in particular to a welding control method and system for the metal net production process, and the method specifically comprises the steps that firstly, functional areas are divided based on the geometric structure of a metal net, temperature changes in thermal imaging images of all the functional areas are analyzed in real time, and weights of different areas are defined; environmental parameters and equipment state data are collected in real time through multiple types of sensors, and comprehensive deviation of materials, environments and equipment at all moments is calculated in combination with material characteristic parameters; adjusting the proportion parameter of each functional area at each moment based on the weight and the comprehensive deviation, and dynamically adjusting the welding power of each functional area at each moment in combination with a self-adaptive PID (Proportion Integration Differentiation) algorithm; the problems that under traditional unified parameter control, the weld quality is not uniform, and the production line rhythm and energy consumption cannot be considered at the same time are solved, and the production efficiency is improved while the welding quality is guaranteed.

The invention discloses a laser-assisted helium arc penetration fusion welding method, and belongs to the technical field of welding. The problems that according to an existing paraxial laser-electric arc composite structure, the welding track is difficult to control, the energy coupling efficiency is low due to laser energy loss, and weld joint partial melting and undercut defects are caused due to uneven distribution of a welding temperature field due to a generated asymmetric heat source are solved. The welding method comprises the steps of 1, pretreatment; 2, after being focused by a focus lens, the laser is divided into three laser beams through a spectroscope, then the three laser beams are converged again through a plurality of reflectors, three fan-shaped light spots are formed on the surface of the to-be-welded plate after convergence, and finally the focal plane position of the laser is adjusted to be located on the surface of the to-be-welded plate; 3, setting welding current and arc voltage; and fourthly, laser is used for assisting helium arc penetration fusion welding. The method is used for laser-assisted helium arc penetration fusion welding.

The invention discloses a Zr / TiC composite reinforced 7075 aluminum alloy wire as well as a preparation method and application thereof, and the aluminum alloy wire comprises the following chemical components in percentage by mass: 5.8%-6.1% of Zn, 2.1%-2.4% of Mg, 1.4%-1.7% of Cu, 0.6%-2.0% of Zr, 0.3%-2.8% of Ti, less than or equal to 0.15% of Cr, less than or equal to 0.15% of Fe, 0.1%-0.4% of C and the balance of Al and other inevitable impurities. The preparation method comprises the following steps: smelting an aluminum alloy ingot by using a pure Al ingot, pure Zn particles, pure Mg particles, pure Cu particles, an Al-Zr intermediate alloy and an Al-Ti-C intermediate alloy, and carrying out homogenization, hot extrusion and drawing reducing deformation processing on the ingot to obtain the wire. An electric arc additive structural part prepared from the aluminum alloy wire is stable in quality and good in mechanical property.

This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect of the disclosure, the assembly robotic system includes a tool coupled to a robot device and configured to be selectively coupled to a first object. The assembly robotic system also includes a welding tool, one or more sensors configured to generate sensor data, and a controller. The controller is configured to control the tool to couple the tool to the first object based on the sensor data, control the robot device to bring the first object into a spatial relationship with a second object, and generate a weld instruction to cause the weld tool to weld a seam formed between the first and second objects. Other aspects and features are also claimed and described.

The invention relates to the technical field of welding automation, in particular to a quality sensing intelligent welding wire allowance monitoring system and method. According to the system, the total mass is detected in real time through a mass detection mechanism comprising a welding wire storage device, a weighing body and a plurality of force sensors, the mass of the remaining welding wires is accurately calculated through a controller according to pre-stored self-weight parameters, and then the remaining length is converted through welding wire specification parameters. According to the method, self-adaptive threshold early warning is achieved by comparing the remaining length with the required length calculated according to the next welding parameters, and the welding sequence can be automatically adjusted to optimize production. According to the method, the problems of interruption risk and resource waste caused by the fact that the allowance cannot be accurately measured due to the fact that the dead weight of the welding wire barrel is too large and estimation depends on experience in a traditional method are solved, real-time accurate monitoring of the allowance of the welding wire is achieved, welding continuity of important structural parts is guaranteed, material waste is remarkably reduced, and production efficiency is improved.

The invention discloses an electric arc fuse wire additive manufacturing method for a complex metal component with a protruding part, which comprises the following steps of: 1, three-dimensional modeling optimization: analyzing a three-dimensional model of the complex metal component; through local treatment, right-angle or oblique angle treatment and protruding part bottom supporting treatment, it is guaranteed that arc fuse wire additive manufacturing can be achieved; the optimized three-dimensional model is subjected to slicing treatment, and an electric arc fuse wire additive manufacturing path is obtained and optimized; and thirdly, the complex metal component with the protruding part is obtained through electric arc fuse wire additive manufacturing. According to the method, through three-dimensional modeling optimization, combined path optimization and additive manufacturing process parameter real-time adjustment, one-time additive manufacturing forming of the complex metal component with the protruding part is achieved, the continuity of the additive manufacturing process is guaranteed, the consistency of the overall performance of the complex metal component is improved, and the manufacturing method is simple in process, controllable and suitable for large-scale production. The method is suitable for the field of electric arc fuse wire additive manufacturing.

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.

The invention discloses an austenitic stainless steel welding wire for a liquid hydrogen storage tank and a preparation method and application of the austenitic stainless steel welding wire, and belongs to the technical field of welding materials and preparation of the welding materials. The welding wire solves the problem that the low-temperature performance of a welding seam is poor when the current welding wire for the liquid hydrogen storage tank is used for welding. The welding wire comprises the following chemical components in percentage by mass: less than or equal to 0.02% of C, 0.4-1.5% of Si, 5.0-7.5% of Mn, less than or equal to 0.020% of S, less than or equal to 0.030% of P, 16.0-22.0% of Cr, 15.0-18.0% of Ni, 2.0-5.0% of Mo, 0.05-0.2% of N, less than or equal to 0.01% of O and the balance of Fe and inevitable impurities. According to the welding wire, deposited metal is low in low-temperature embrittlement tendency, high in low-temperature strength and excellent in low-temperature impact and fracture toughness. The welding wire is used for welding the austenitic stainless steel liquid hydrogen storage tank and is wide in application range, and the mechanical property of deposited metal is good.

The invention provides a Q890qE and Q420qE bridge steel flat butt joint combined welding method which comprises the following steps: step 1, grinding and derusting grooves of upper and lower asymmetric double-sided V-shaped joints to expose metallic luster; 2, preheating is conducted in an electric heating mode; 3, a solid welding wire CO2 gas shielded welding is adopted for backing welding of one weld joint on the upper V-shaped deep groove side; 4, welding seams are filled in the side of the V-shaped deep groove through submerged arc automatic welding, and the filling thickness is about 1 / 2 of the groove depth; 5, back gouging is conducted on the back face through carbon arc air gouging, and a carburized layer is polished and cleaned till metallic luster is exposed; 6, the V-shaped shallow groove is welded and filled; seventhly, the submerged arc automatic welding continues to weld the remaining weld joints of the V-shaped deep groove till the remaining weld joints are filled; and 8, postweld heat treatment is conducted. According to the method, a combined welding method of solid welding wire CO2 gas shielded welding bottoming, submerged arc automatic welding filling and capping is adopted, the problems of welding cold cracking and early joint breakage of the dissimilar bridge steel are solved by combining joint design, and the mechanical properties of a welding seam and a fusion area meet the standard requirements.

The invention discloses an intelligent welding seam automatic tracking system based on multi-modal sensing fusion, which comprises a mobile detector, the mobile detector comprises a mobile detection box, the mobile detection box is L-shaped, a pair of crawler-type movers is mounted on the mobile detection box, and the crawler-type movers are connected with the mobile detection box. A lifting bottom end welding device and a welding mechanical arm are installed on the movable detection box, and through deep cooperation of a multi-mode sensing array and a mechanical execution mechanism, a closed-loop control framework of sensing, decision making, execution and feedback is constructed; high precision and intellectualization of all-position welding under complex working conditions are achieved; the device has the core advantages that the arc blocks unfolded in a fan shape are combined with the crawler-type mover, and dead-corner-free welding of complex workpieces such as pipelines and ship sections is supported; and multi-modal data fusion is combined with a deep learning algorithm, so that the tracking precision is improved, and arc strong light and noise interference are effectively inhibited.

The invention relates to the technical field of welding materials, in particular to a titanium carbide reinforced iron-based wear-resistant corrosion-resistant flux-cored wire for surfacing on the surface of a conveying roller. According to the specific technical scheme, the flux core comprises, by mass, 10%-20% of graphite, 25%-35% of ferrotitanium, 2%-6% of ferrovanadium, 3%-8% of electrolytic manganese metal, 2%-10% of ferromolybdenum, 5%-15% of ferrosilicon, 2% of aluminum-magnesium alloy and the balance Fe powder. According to the flux-cored wire prepared through the flux core, the surfacing alloy obtained through electric arc surfacing is good in surfacing manufacturability, attractive in weld joint forming and small in surface air hole number, and the flux-cored wire has high hardness, high-temperature abrasion resistance and corrosion resistance.

The invention provides a machine learning method and system, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting a real-time sensing data stream of industrial equipment at an edge calculation node, the data stream comprising a welding robot end temperature value, a driving motor current value and a mechanical arm vibration frequency value; and step 2, based on the real-time sensing data stream, extracting characteristic values of a starting positioning point, a path midpoint and an ending positioning point in the welding track through an edge intelligent processing unit, and dynamically generating an anomaly judgment threshold according to the characteristic values. The method can quickly respond to instantaneous abnormity, improves the progressive fault recognition and prediction capability, reduces the equipment fault risk and maintenance cost, and guarantees the production safety and quality.

A kink prevention jig used in a pail pack to prevent kinks when wire is pulled out is provided with a housing that has a base plate part and a tubular outer tube part, and that accommodates a laminated wire and a wire extraction hole thereabove. This kink prevention jig is provided with an outwardly extended section above the laminated wire and that extends in the radial direction of the outer tube part, and a wire abutment section above the outwardly extended section and which abuts on a welding wire W and thereby prevents kinks when the welding wire W is pulled out from the extraction hole.

The invention discloses a multi-robot path planning method for an electric arc additive manufacturing system. The multi-robot path planning method comprises the specific steps that a three-dimensional model is obtained, slicing and layering are conducted, environment information is obtained, and environment modeling is conducted; determining an ideal task load; performing matrix iteration, and optimizing the current task load; constructing a minimum spanning tree, and generating a two-dimensional optimal task path of each robot; and performing three-dimensional conversion and asynchronous execution. Compared with the prior art, the method has the advantages that the form requirement of an actual additive manufacturing path is fully considered, the process defects of air holes, insufficient fusion, slag inclusion and the like in the manufacturing process are effectively reduced, and the problems of region segmentation and deposition path planning in an electric arc additive manufacturing (WAAM) task cooperatively executed by multiple robots are successfully solved; and therefore, high-quality additive manufacturing of the component is realized. Meanwhile, the path design strategy proposed in the method avoids the start-stop operation of the welding gun, ensures the parallelism and independence of each robot path in the three-dimensional space, and further improves the operation efficiency and stability of the system.

The invention discloses a remote welding machine control system and method based on the Internet of Things, and the method comprises the following steps: S1, collecting and preprocessing multi-source time sequence data, and generating a time sequence data set; s2, constructing a variational auto-encoder model, extracting potential features and reconstructing original data; s3, using a bird flock optimization algorithm to optimize hyper-parameters of the VAE model; s4, performing feature extraction and data reconstruction through the optimized VAE model; s5, model output and actual data are compared, the welding quality is evaluated, and control parameters are adjusted; s6, real-time welding operation is carried out according to the adjusted control parameters, and equipment identity binding and permission verification are carried out; s7, performing real-name fire approval through the platform, and remotely starting the equipment after the approval is passed; s8, the welding state is monitored, early warning is conducted on abnormity, and a maintenance plan and reminding are pushed; and S9, uniformly managing equipment states, task approval, early warning and operation and maintenance, and generating an analysis report. Intelligent control and safety management of the remote welding machine are achieved, and automation and efficiency of welding operation are improved.

Provided are a gas-shielded metal arc welded joint of high-Mn steel, which is simple, has high strength and excellent extremely low-temperature toughness, and a method for producing the same. A gas-shielded metal arc-welded joint in which a welding metal is formed from a steel material of a high-Mn-content austenitic steel containing, in mass%, 18.0-30.0% of Mn using a shielding gas and a solid welding wire, the welding metal having a chemical composition containing, in mass%, 0.15-0.80% of C, 0.10-1.00% of Si, 17.0-30.0% of Mn, 0.030% or less of P, 0.030% or less of S, 0.001-0.100% of Al, 0.4-5.5% of Cr, 0.01-3.50% of Mo, 0.01-10.00% of Ni, and 0.0200-0.1500% of N, with the remainder being Fe and unavoidable impurities. Methods of making a gas shielded metal arc welded joint by incorporating a given concentration of nitrogen in a shielding gas, or increasing the N content of a solid wire.

An assembly and method for preparing a pipe elbow for welding. The assembly has a cone clamping sleeve assembly adapted to be inserted into an end of the pipe elbow and a faceplate assembly removably affixed to the cone clamping sleeve assembly. The cone clamping sleeve assembly has a face at one end thereof. The face has at least one locating hole and at least one screw hole. The faceplate assembly has at least one locating pin receivable by the locating hole of the cone clamping sleeve assembly. The faceplate assembly has a captive screw threadedly received by the screw hole. The faceplate assembly has at least a pair of centering pins positioned at diametrically opposed locations on a faceplate. The centering pins are radially adjustable and adapted to bear against an inner diameter of the end of the elbow.

To suppress a welding quality from deteriorating even if an arc-interruption occurs due to arc blow, in consumable electrode pulse arc welding.SOLUTION: In a consumable electrode pulse arc welding control method, in which a welding wire is fed at regular feeding speed and rising transition currents that rise from base currents to peak currents are distributed during a rising period of time, the peak currents are distributed during a peak period of time, falling transition currents that fall from the peak currents to the base currents are distributed during a falling period of time, the base currents are distributed during the base period of time, and welding currents Iw described above are repeatedly distributed in a first pulse period to perform welding, feeding speed Fw in an arc-interruption period of time at times of T13-t2 is set to be higher than the regular feeding speed at times of t1-t13.SELECTED DRAWING: Figure 2

The invention discloses a heat-treatment-free control method for inhibiting hydrogen-induced cracks in ultrahigh-strength steel welding, which belongs to the technical field of welding, and enables weld metal to obtain a low-phase-transition-temperature characteristic and a double-phase structure containing retained austenite under a specific dilution rate window by cooperatively regulating and controlling components of a welding material and welding process parameters. Therefore, preheating-free and post-heat-treatment-free efficient welding of the ultrahigh-strength steel is achieved. According to the method, the volume expansion effect generated by low-temperature martensite phase transformation of weld metal is utilized to actively counteract restrained tensile stress formed by welding cooling shrinkage; on the other hand, the effect of the retained austenite serving as an efficient'hydrogen trap 'is fully played, migration and enrichment of hydrogen to crack sensitive areas such as a heat affected zone or a fusion line are effectively blocked, and finally effective inhibition of hydrogen-induced cracks in ultrahigh-strength steel welding is achieved; the obtained welding joint is free of hydrogen-induced cracks and has the mechanical property level well matched with base metal.

The invention provides a welding seam quality prediction and process optimization method based on a welding cloud platform. The initial optimization parameters of the weld joint process parameters are determined on the basis of the weld joint quality data and in combination with the preset target requirements, it is ensured that the optimization direction meets the actual production requirements, a scientific basis is provided for real-time adjustment of welding equipment, real-time optimization is conducted through a welding equipment controller according to the initial optimization parameters, and the welding efficiency is improved. The current welding seam quality data in the optimization process are collected in real time and fed back to the welding cloud platform to update the welding seam quality prediction model, quality fluctuation in the welding process is quickly responded, defect expansion is avoided, the welding quality stability is improved, and the welding quality prediction efficiency is improved. The current welding seam quality data in the optimization process is fed back to the cloud platform, and the model is updated, so that the model can continuously adapt to the change of the welding scene, the prediction and optimization accuracy is gradually improved, and the iterative upgrading of the technical scheme is realized.

The invention discloses a welding workshop robot state real-time monitoring method based on digital twinning, which relates to the technical field of intelligent welding monitoring, and comprises the following steps: comparing twinning prediction data with aligned multi-channel data moment by moment to obtain virtual-real contrast characteristics, extracting a key process section set according to the virtual-real contrast characteristics, and carrying out real-time monitoring on the state of a welding workshop robot according to the key process section set. Calculating a fast consistency ratio mean value and a welding stability index mean value; according to the fast consistency ratio mean value and the welding stability index mean value, a stability consistency function is constructed, a welding state interval boundary is defined, the welding state of the key process section is judged, and the abnormal type of the key process section is recognized; and based on the abnormal types of the key process sections, event trigger signals are generated, real-time path adjustment is executed, and energy control, motion control and visual acquisition control in the welding process are dynamically coordinated. State recognition and abnormal parting of key process sections are achieved, and stable operation of the welding process is guaranteed.