4564 results about "Electric arc" patented technology

The invention discloses a welding robot track self-adaptive correction method based on multi-modal data fusion, and particularly relates to the technical field of industrial robots, which comprises the following steps: synchronously acquiring visual three-dimensional point cloud and arc current and voltage transient waveform data in a welding process in real time; an enhanced working trajectory feature vector fusing the visual trajectory features and the arc deviation compensation amount is constructed; respectively calculating real-time confidence coefficients of the visual sense and the arc sensing mode; inputting the confidence coefficient into a weight distribution strategy model, dynamically resolving vision and arc weight coefficients, and when the confidence coefficient of one sensor is low, lifting the weight of the other sensor to dominate correction; performing weighted fusion on the two pose adjustment amounts by using a weight coefficient to generate a six-degree-of-freedom comprehensive trajectory correction amount; and finally, the robot is driven to execute online adaptive trajectory correction. Through a confidence-driven dynamic fusion strategy, the limitation of a single sensor is overcome, and the welding robot trajectory tracking precision and the adaptive capacity are improved.

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 3D printing path planning method based on electric arc additive anisotropy and a stress field, and the method comprises the steps: constructing a CAD three-dimensional model of a part, and obtaining the stress field of the part through finite element simulation; determining a slice plane; mapping the stress field to a slice plane to form a force flow line; according to the obtained force flow line, rotation transformation regeneration is carried out according to the anisotropy of the used electric arc additive, and a reference trajectory considering the anisotropy of the material is obtained; under the principle of alternate arc starting and extinguishing, the corresponding printing sequence in the layers and between the layers is further planned, and the reference trajectory lines are connected end to end to be planned into a continuous path; and generating a code file, and printing according to the printing sequence. The comprehensive mechanical property of a printed piece is improved.

The invention relates to the technical field of intelligent fire fighting, in particular to a building electrical fire identification method and system based on multi-source information fusion, and the method comprises the steps: firstly collecting the multi-source monitoring data of an electrical system in real time, then carrying out the preprocessing of the multi-source data, including noise filtering, time alignment and feature extraction, and constructing a dynamic weight fusion model; the weight of each data source is adaptively allocated based on the feature entropy, then fusion features are input to the fire risk grading model, a fire probability index and an early warning level are output, and when the early warning level exceeds a threshold value, a linkage control instruction is triggered and an alarm is given; according to the method, through dynamic fusion of multi-source information, the electrical fire identification precision is remarkably improved, multi-dimensional parameters such as current, temperature, smoke and arc are adaptively integrated by adopting an entropy weight assignment mechanism, the problems of false alarm and missing alarm of traditional single-threshold detection are solved, the missing alarm rate and the false alarm rate are remarkably reduced, and the reliability of fire early warning is ensured.

The invention discloses an intelligent response method for an arc fault of a high-altitude switch cabinet, relates to the technical field of safety protection of power equipment in a high-altitude area, and aims to solve the problems that the arc time of the arc fault is prolonged, the pressure in the cabinet is sharply increased, a traditional disposable pressure relief device cannot be reset and is lack of insulation state evaluation, and the reliability is poor. The invention aims to provide a response method which combines optical signal and pressure double-criterion detection, resettable pressure relief, gas component analysis and intelligent decision so as to improve the safety and reliability of the switch cabinet.

The invention discloses a direct-current hollow electrode hydrogen plasma furnace mineral powder smelting system and method and application, and belongs to the technical field of hydrogen metallurgy. The system comprises a hollow electrode gas powder injection hydrogen plasma gun system, a direct current bottom electrode ore-smelting electric furnace system, a fine ore and hydrogen supply system and the like. The hollow electrode and the furnace bottom electrode form a direct-current arc, hydrogen carrying mineral powder is sprayed into an arc area to generate high-temperature hydrogen plasma, mineral powder reduction is achieved, and metal and slag are separated. According to the method, hydrogen serves as a reducing agent, carbon emission is reduced, the reaction efficiency is high, energy consumption is low, and the method can be used for steelmaking, smelting of micro-carbon ferromanganese and titanium slag and recovery of valuable metal in nonferrous smelting waste slag and has good green metallurgy application prospects.

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.

High-frequency irreversible electroporation (H-FIRE) is a tissue ablation modality employing bursts of electrical pulses in a positive phase-interphase delay-negative phase-interpulse delay pattern. Despite accumulating evidence suggesting the significance of these delays, their effects on therapeutic outcomes from clinically-relevant H-FIRE waveforms have not been studied extensively. The present invention provides methods of pulse delivery, including delays, that mitigate bubble formation and / or minimize the risk of arcing, such as due to the presence of bubbles, and / or minimize muscle stimulation are described herein.

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 field of electrical parameter measurement of power distribution switch equipment, in particular to an arc fault measurement method, system and device in the power distribution switch equipment and a medium, and the method comprises the steps: collecting a current signal in a power distribution loop in real time; separating out target frequency band components of which the frequency is greater than a preset frequency threshold in the current signal; performing envelope extraction on the target frequency band component to obtain an envelope signal; performing time domain analysis on the envelope signal to obtain the regularity intensity of the pulse of the envelope signal; performing short-time Fourier transform on the target frequency band component, and calculating a frequency spectrum variance; taking the regularity intensity and the spectrum variance as feature vectors, and inputting the feature vectors into a pre-trained artificial intelligence model; outputting a first fault diagnosis result by the artificial intelligence model; and generating a control instruction based on the first fault diagnosis result to trigger the protection device to act. The method has the advantage that the dangerous electric arc in the power distribution loop can be accurately identified and quickly responded.

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 provides a rotating electrode atomization powder preparation control system and a control method. A multivariable machine learning prediction model among the electrode rotating speed, the plasma arc power, the protective gas flow, the powder particle size and the sphericity degree is established; calculating the optimal electrode rotating speed, plasma arc power and protective gas flow by using the multivariable machine learning prediction model according to the target powder particle size and sphericity; the optimal technological parameters are applied to the powder making process, and a powder making system is operated; the electrode rotating speed, the electric arc power and the gas pressure are monitored in real time in the atomization process, and technological parameters are dynamically adjusted to compensate fluctuation; the image acquisition unit is used for acquiring images of flying powder particles, particle size distribution and sphericity are analyzed in real time through an AI visual model, and the electrode rotating speed, plasma arc power and protective gas flow are fed back and adjusted according to analysis results.

The invention belongs to the technical field of metallurgical industry process intelligent control and prediction, and discloses a self-adaptive mixed intelligent prediction method and system for smelting endpoint parameters of an electric arc furnace. Acquiring smelting process data of the electric arc furnace; constructing a dual-drive prediction system comprising a mechanism model and a data drive model; calculating a decision coefficient of a prediction value and an actual measurement value of the theoretical model, and counting an effective historical data volume; constructing a machine learning prediction model, and selecting a modeling algorithm according to the effective historical data volume; selecting a hybrid prediction strategy based on the decision coefficient and the effective historical data volume; predicting and outputting an end point carbon content predicted value and an end point temperature predicted value according to a hybrid prediction strategy; predictive deviation threshold value judgment and execution control are conducted, and the electric arc power, the oxygen blowing flow, the feeding speed or the cooling water flow are adjusted. Accurate prediction and dynamic optimization control of the electric arc furnace end point parameters are achieved, and the smelting quality, the energy utilization rate and the production stability are remarkably improved.

The invention relates to the technical field of ammeter fault detection, and provides an intelligent ammeter series arc fault detection method, system and device, a medium and equipment, and the method comprises the steps: firstly obtaining an ammeter data set of an intelligent ammeter, which comprises a pre-ammeter voltage, a post-ammeter voltage and a total loop current in a continuous power frequency period, and then carrying out the division through a sliding time window, obtaining a plurality of ammeter data windows; for each window, calculating a voltage difference sequence and a dynamic loss impedance sequence; when the absolute value of the total loop current is smaller than a preset threshold value, determining the current zero-break interval of each power frequency period and the current zero-break time corresponding to the window; determining an arc voltage estimation value according to a voltage difference between non-zero-break intervals in the zero-break interval; and finally, integrating the current zero break time, the arc voltage estimated value and the dynamic loss impedance of each window to judge whether a series arc fault exists, and if so, triggering a protection action. According to the embodiment of the invention, high-reliability identification of the series arc fault is realized.

The invention relates to the technical field of power system equipment state monitoring and fault diagnosis, and discloses an arc light online monitoring method and system based on a spectrum sensing technology, and the method comprises the steps: arranging a first spectrum sensor and a second spectrum sensor corresponding to a detected target, and respectively detecting optical signals in different wavelength ranges; collecting optical data according to a set period, and identifying abnormal features according to a preset template; when the double abnormal features exist, the duration of the double abnormal features is calculated, and if the duration exceeds the corresponding reference duration, a duration reference value is generated; and performing weighted calculation on the time length analysis value, if the time length analysis value is within a preset range, giving a partial discharge abnormal prompt, and resetting the reference value. Multi-wavelength spectrum monitoring is utilized, non-contact and high-sensitivity detection of partial discharge is achieved, electrical equipment is prevented from being damaged, fault hidden dangers are found in time, and safe and stable operation of the equipment is guaranteed.

The invention relates to the technical field of electric power system control, and discloses an electric power system arc harmonic collaborative suppression and intelligent closed-loop control system, which comprises the steps of: acquiring sensor data and uploading the sensor data to an edge computing unit by deploying a sensor; wavelet threshold denoising and electromagnetic interference compensation are adopted; the method comprises the following steps: constructing a coupling model containing arc plasma dynamic resistance, optimizing VMD parameters through PSO, extracting a joint feature vector, filling an arc and harmonic dynamic coupling analysis gap, calculating a total harmonic distortion rate and arc extinction time in combination with a power grid damping ratio, solving an optimal SVG trigger angle, and solving the problem of lack of power grid stability evaluation; correcting the opening time of the circuit breaker, calculating the error of the total harmonic distortion rate and the error of the arc extinction time, and adjusting the SVG trigger angle; calculating the precision of the evaluation model, calculating the full life cycle through the aging coefficient, analyzing and judging whether an early warning signal is generated or not, and triggering equipment replacement early warning based on the generated early warning signal.

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 provides an automatic positioning welding robot, and belongs to the technical field of automatic welding. Comprising a rack, the top of the rack is slidably provided with a portal frame, the top of the portal frame is slidably provided with a bearing frame, the top of the bearing frame is fixedly connected with a first electric push rod, the telescopic end of the first electric push rod is fixedly connected with a case, the bottom of the case is fixedly connected with a laser vision sensor, and the bottom of the case is provided with a mounting frame. The laser vision sensor is linked with the posture adjusting assembly and the transverse linear module, the problem that traditional automatic welding equipment cannot adapt to weld joint misalignment and gap changes is solved, the center position and the misalignment amount of a weld joint can be obtained before welding and in the welding process, and the welding quality is improved. The posture adjusting mechanism is driven to adjust the transverse position and the inclination angle of the welding gun, it is ensured that the arc of the welding gun is always accurately centered, the defects of undercut, incomplete fusion and the like caused by misalignment are effectively prevented, and the quality of a welded joint is improved.

The invention discloses a method for preparing spherical metal fine powder by using coarse / waste powder through ultrasonic atomization, which comprises the following steps of: (1) collecting coarse / waste powder raw materials for ultrasonic atomization powder preparation, (2) conveying the coarse / waste powder to an electric arc melting area through argon gas flow, and carrying out melting and ultrasonic atomization powder preparation processing; (3) in the powder preparation process, the powder is continuously collected by using argon circulating airflow, so that the continuity of the powder preparation process is ensured; and (4) finally screening the prepared powder in particle size ranges to obtain high-quality spherical fine powder in different particle size ranges. According to the method, the recycling and reusing problems of 3D printing splashing waste powder and coarse powder in the traditional gas atomization powder manufacturing process are solved, and the powder pollution risk is remarkably reduced; according to the ultrasonic atomization re-powdering technology, the high-quality spherical metal fine powder needed by additive manufacturing can be efficiently prepared, powder waste discharge and environmental burden are reduced, the obtained powder can be directly used as a high-quality raw material for additive manufacturing, and green and sustainable development of the metal additive manufacturing industry is promoted.

The invention provides an insulating material surface arc ablation resistance simulation method based on magnetohydrodynamics, and belongs to the field of insulating material performance detection. The method comprises the following steps: establishing an insulating material surface arc ablation resistance model; constructing a magnetohydrodynamic control equation set; setting boundary conditions of the model; and iteratively solving the magnetohydrodynamic control equation set through finite element simulation software to obtain a temperature distribution diagram of the insulating material under different arc ablation times, and comparing the temperature distribution diagram with a TGA curve of the insulating material to judge the arc ablation resistance of the insulating material. According to the invention, the power-frequency alternating-current high-voltage arc and the insulating material are used as simulation objects, engineering practice is better met, the surface arc ablation resistance process of any insulating material can be simulated by changing the physical characteristic parameters of the insulating material, and the TGA curve of the material is introduced to judge the arc ablation resistance of the insulating material. And technical support is provided for high-voltage switch equipment insulating material type selection.

The invention discloses an electric arc detection method based on differential increase and structured attention, and the method comprises the steps: firstly carrying out the collection and preprocessing of a current signal, carrying out the differential enhancement according to a sample type, carrying out the strong enhancement of an electric arc sample, improving the generalization capability, and carrying out the weak enhancement of a normal sample, thereby avoiding the overfitting; the problem of class imbalance is relieved, and the model generalization ability is improved; secondly, obtaining six complementary feature representations of time domain waveform, frequency domain frequency spectrum, time frequency analysis, envelope features, statistical distribution and related features from the differentially enhanced current signal through a multi-modal feature extraction method, and fusing to generate a multi-modal image; then, designing a deep learning model integrated with structured attention, carrying out distinguished attention on different feature analysis areas of the multi-modal image, and directionally enhancing arc features; and finally, dynamically quantifying the trained model, reducing the size of the model and reasoning delay, and supporting efficient deployment of various edge computing devices.

The invention discloses an electric arc three-dimensional reconstruction system and method based on binocular vision. The system comprises a double-camera image acquisition module, a correction module, a boundary contour point extraction module and a three-dimensional reconstruction module. The dual-camera image acquisition module completes dual-camera parameter calibration and dual-vision arc image shooting operation at different positions; the correction module corrects an optical distortion area and a breakpoint area of the double-vision arc image to obtain a corrected double-vision arc image; the boundary contour point extraction module adopts a third-order Bezier curve to perform segmentation fitting on the boundary contour of the corrected double-vision arc image to obtain continuous double-vision arc boundary points; and the three-dimensional reconstruction module reconstructs a three-dimensional contour line of the electric arc through a triangulation method according to the camera calibration parameters and the double-vision electric arc boundary points, and generates a corresponding three-dimensional point cloud data set. According to the method, the distortion and breakpoint phenomena of the arc image can be repaired, and high-precision reconstruction of three-dimensional data of the arc is realized.

The invention relates to the technical field of building construction welding, in particular to steel structure electric arc welding equipment for building construction. The device comprises a welding gun, a nozzle structure is installed at the bottom of a welding head connecting pipe in a threaded mode, the nozzle structure comprises a hollow spraying pipe and a contact tube extending from the interior of the welding head connecting pipe, an isolation inner pipe is installed in the spraying pipe in a clamped mode, and a gas flow channel formed between the spraying pipe and the contact tube is separated through the isolation inner pipe. The external expansion structure at the lower end of the isolation inner pipe is matched with the height difference between the bottom end of the isolation inner pipe and the bottom end of the spray pipe, physical shielding is formed, and high-temperature splashes entering the external sub-runner during welding are reduced; therefore, adhesion on the inner wall of the outer sub-runner is effectively avoided, the outer sub-runner is kept smooth all the time, and stable conveying of the protective gas 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 relates to the technical field of metal wire processing, and discloses a high-performance metal wire plastic coating process for aerospace engineering, which comprises the following steps: carrying out base material type selection on a metal wire, and carrying out surface treatment of precise cleaning, etching and depth gradient activation; a Ti-Cr alloy and graphene-copper composite transition layer is deposited through a magnetron sputtering technology, and a multi-layer coating structure is formed through electrostatic spraying of a base coating, a fluidized bed dipping function layer and high velocity oxy-fuel spraying of a nano composite coating in sequence; the molybdenum-gold composite sealing layer is prepared by adopting an electric arc spraying technology, and is subjected to vacuum ultraviolet curing enhancement, high-temperature gradient annealing, gradient sintering and vacuum curing treatment; and heat radiation on the surface of the coating is enhanced through laser-induced micro-nano structure regulation and silicon nitride film sputtering. Through collaborative optimization of base material treatment, coating construction, function strengthening and quality control, the interface bonding strength, the comprehensive performance and the environmental adaptability of the spaceflight metal wire coating are remarkably improved, and the service life of the spaceflight metal wire coating is remarkably prolonged.

The invention relates to the technical field of arc fault detection, and discloses a method and device for detecting an arc fault in a switch cabinet, and the method comprises the steps: collecting a three-phase current signal of each feeder loop in the switch cabinet, and obtaining target current data through preprocessing; decomposing the target current data to obtain a plurality of current mode components, and performing clustering reconstruction on the plurality of current mode components to obtain an arc feature set; and inputting the arc characteristic set into the time sequence convolutional network embedded with the Mayr arc physical model to carry out fault identification, and obtaining a fault identification result, the Mayr arc physical model is embedded into the time sequence convolutional network, the arc fault detection accuracy is improved, the full-process automatic response from early warning monitoring to emergency isolation is realized, and the fault identification efficiency is improved. A protection action can be completed before a series arc fault evolves into a serious inter-phase short circuit, and the real-time protection capability of the switch cabinet is improved.

The invention belongs to the technical field of research and development of fast neutron reactor jackets and structural materials, and particularly relates to a high-temperature-lead-bismuth-corrosion-resistant high-silicon-content ferrite / martensite steel ladle tube and a preparation method thereof. According to the mass percentage, the composition mainly comprises the following components: 0.16-0.24% of C; 0.4 to 0.8 percent of Mn; cr: 11.6% to 12.4%; 1.2 to 1.8 percent of W; 0.1 to 0.4 percent of Ta; 0.2 to 0.4 percent of V; 1.0%-1.8% of Si and Fe. The preparation method comprises the steps of vacuum induction and vacuum arc remelting. Carrying out homogenization treatment and forging; extruding and annealing; cold rolling and annealing; and performing normalizing and tempering treatment. Through an efficient short-flow process route and reasonable smelting, pipe machining deformation and heat treatment processes, the microscopic structure of the material is remarkably improved, then the mechanical property and high-temperature lead and bismuth corrosion resistance of the finished pipe are improved, and the use requirement of the lead and bismuth cooling fast reactor fuel assembly cladding material under the high-temperature working condition is met.

The invention belongs to the technical field of additive manufacturing, and particularly relates to a strong electromagnetic pulse-ultrasonic auxiliary electric arc additive manufacturing platform. The platform body is provided with an upper substrate used for providing an initial plane for electric arc additive manufacturing; the water cooling device comprises a water cooling box used for containing cooling water, and the substrate is contained in the water cooling box; the base plate locking clamp comprises a positioning clamping table and a clamping device. The positioning clamping table and the clamping device are arranged on the two sides of the upper base plate and matched to form a fixing structure for fixing the relative positions of the upper base plate and the platform body. The welding gun head is connected with the six-axis mechanical arm and is used for carrying out additive manufacturing on the upper substrate; the clamping device and the welding gun head are arranged on the two opposite sides of the upper base plate in a spaced mode. And the clamping device is partially arranged outside the water cooling box. The clamping device and the welding gun head are arranged on the two sides of the water cooling box respectively, space interference between the clamping device and the welding gun head in the working process can be effectively avoided, meanwhile, a principle heat source of the clamping device can be guaranteed, and normal work of the clamping device is guaranteed.

An AC series arc detection method, system and device and a readable storage medium relate to the technical field of electrical engineering, and specifically comprise the following steps: generating a current anomaly event and a corresponding current anomaly time window based on a current signal at a current sampling moment and a current signal at a previous sampling moment; the current abnormal events comprise current short-time sudden change abnormity, high-frequency energy sudden increase abnormity and intermittent conduction interruption abnormity; generating a voltage abnormal event and a corresponding voltage abnormal time window according to all voltage signals in the current abnormal time window and the voltage signal at the current sampling moment, wherein the voltage abnormal event comprises zero-crossing conduction abnormity and voltage transient amplitude abnormity; determining a current and voltage dual-channel abnormal event based on the current abnormal time window and the voltage abnormal time window in a preset time alignment window; and determining an alternating-current series arc event according to the current-voltage dual-channel abnormal event to realize alternating-current series arc detection. According to the invention, the accuracy and realizability of alternating-current series arc detection can be ensured.