21496 results about "Aluminium alloy" patented technology

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

The invention discloses an aluminum alloy surface defect detection method and system using deep learning, and relates to the related field of detection performed in combination with deep learning, and the method comprises the following steps: carrying out image acquisition on an aluminum alloy finished product, constructing a surface image data set to extract multi-scale surface features, and constructing a feature enhanced image set to carry out defect detection, and a defect detection result is obtained to dynamically optimize aluminum alloy production process parameters, and a process adjustment instruction is generated and fed back to a production system. The technical problems that traditional detection mostly depends on manual visual inspection or a machine vision system based on rules, imaging distortion, small defect missing detection and process adjustment are caused are solved, and the technical effects that deep learning is conducted through the double-branch network, the defect detection efficiency and the production yield are improved, and control over the aluminum alloy manufacturing quality is met are achieved.

The invention provides an aluminum alloy surface oxidation spot defect identification method and device based on machine vision, and relates to the field of intelligent manufacturing and industrial automation, and the method comprises the steps: obtaining an aluminum alloy surface color image, and carrying out the preprocessing of the image, so as to extract a brightness component image; self-adaptive threshold segmentation of local contrast enhancement is carried out on the brightness component image, a defect area binary mask is generated, morphological connected domains are extracted according to the mask, and three basic feature indexes of the area pixel value, the contour Fourier descriptor complexity and the area gray scale standard deviation contrast of each connected domain are calculated; and extracting and marking a connected domain boundary, verifying a boundary closed topological structure, and dynamically generating a curvature-driven self-adaptive sampling point through multi-scale B-spline curvature extreme value detection. Through optical-algorithm-process three-level collaborative innovation, the curved surface reflection false alarm rate is reduced, the pinhole detection rate is increased, and the boundary precision is + / -0.2 pixel.

The invention relates to the technical field of aluminum alloy cold stamping quality control, in particular to a multi-source data fusion and real-time optimization-based cold stamping quality control method, which comprises the following steps of: inputting a fusion feature space into a pre-trained LSTM (Long Short Term Memory) model, and associating a real-time stamping speed with a dwell time parameter through an attention mechanism; combined prediction of springback value deviation and defect probability is realized for the first time, a process parameter correction value is dynamically generated based on a prediction result, and a thermal expansion compensation algorithm and micron-sized mold compensation are combined, so that the quality regulation response speed reaches a millisecond level, the compensation precision is improved to + / -2 [mu] m, and the error is reduced by more than 50% compared with that of traditional PID (Proportion Integration Differentiation) control.

The invention relates to aluminum alloy pipe machining equipment, in particular to a polishing device for a formed aluminum alloy pipe. The right support and the left support are arranged in parallel at the same height, the left support is provided with an inner polishing part capable of going deep back and forth, and the right support is provided with a rotating part capable of driving a pipe to rotate. According to the grinding device for the formed aluminum alloy pipe, a left support and a right support which are symmetrically arranged form a main body frame, the front end of the left support is provided with an inner grinding part capable of conducting feeding movement in the front-back direction, and the right support is correspondingly provided with a rotating part for driving the pipe to rotate; the rotating part comprises two sets of supporting rollers coaxially installed on the right support, and a plurality of grinding blocks used for grinding the outer surfaces are evenly distributed on the peripheries of roller bodies of the supporting rollers. The inner grinding part carries a moving seat capable of longitudinally sliding through a left support guide rail, a grinding shaft capable of rotating at a high speed is arranged in the moving seat, the tail end of the grinding shaft is rigidly connected with a multi-blade grinding head used for inner wall machining, and progressive grinding of the grinding head in an inner cavity of the pipe is achieved through axial feeding driving of the moving seat.

The invention relates to the technical field of image processing, in particular to an aluminum alloy casting processing forming quality evaluation method, which comprises the following steps of: acquiring a multi-angle image of the surface of an aluminum alloy casting, determining a brightness defect coefficient of each pixel point according to the difference between each pixel point and a neighborhood pixel point in the multi-angle image, and calculating the brightness defect coefficient of each pixel point; screening suspected defect pixel points according to the brightness defect coefficient, and determining a suspected defect area by utilizing a watershed algorithm and connected domain analysis; all edge pixel points of each suspected defect area are obtained, the density of each edge pixel point is calculated, feature edge pixel points are screened out according to the density, Fourier transform is carried out on a coordinate sequence of the feature edge pixel points, shape feature vectors of the suspected defect areas are constructed, clustering is carried out according to the shape feature vectors, and the shape feature vectors of the suspected defect areas are obtained. And obtaining a defect area. According to the method, the accuracy of the defect detection result of the surface of the aluminum alloy casting is improved by accurately analyzing the brightness characteristics and the shape characteristics.

The invention belongs to the technical field of metal material engineering, and relates to a light high-toughness low-cost aluminum alloy and a preparation method thereof.The alloy comprises, by mass, 7.0%-9.2% of Mg, 2.5%-4.0% of Zn, 0.06%-0.20% of Zr, 0.01%-0.03% of Sb, main impurities including Fe smaller than or equal to 0.15%, Si smaller than or equal to 0.12%, other single impurities smaller than or equal to 0.05%, the total impurity smaller than or equal to 0.15% and the balance Al. Compared with 2xxx series and 7xxx series aluminum alloys, the alloy has certain advantages in the aspects of density, specific strength, ductility, corrosion resistance and the like, and has a remarkable cost advantage compared with a low-density aluminum-lithium alloy, so that the core competitiveness of an alloy product is improved, and the alloy product has the potential of becoming a next-generation commercial aluminum alloy.

The invention discloses a fatigue life simulation evaluation method for a lightweight aluminum alloy material of a new energy automobile, and relates to the technical field of material life evaluation. A microstructure image is collected, coupling features are extracted through machine learning, and heterogeneous data fusion and enhancement are completed; generating a topological optimization structure based on a GAN, introducing a VPSC model to describe anisotropy according to a stress gradient dynamic grid, and constructing a dynamic finite element model; fusing vehicle driving data, predicting a load by using LSTM, performing VMD decomposition and environment correction, and realizing space-time correlation load spectrum reconstruction; a phase field model is used in a microcosmic mode, cracks are tracked in a macroscopic mode through XFEM, damage parameters are transmitted in a bidirectional coupling mode, and multi-physics field coupling simulation is carried out; fusing simulation and test data by adopting Bayesian reasoning, calculating life probability distribution, and correcting parameters when errors exceed the limit; according to the method, the fatigue life prediction error is finally reduced, the time consumption of single simulation is reduced, full-life-cycle evaluation and visual early warning are realized, an efficient scheme is provided for lightweight design, and industrial technology upgrading is promoted.

The invention relates to the technical field of aluminum alloy processing, in particular to an aluminum alloy component multi-source heterogeneous production data acquisition system and method. The method comprises the following steps that multi-source heterogeneous sensing equipment is dynamically deployed along a drill bit machining track of a core machining unit to extract original signals, then multi-source data streams are gathered according to aluminum alloy working procedure features, and finally a component-level original heterogeneous data set is generated; carrying out feature enhancement processing according to the component-level original data set, and carrying out band element data matrix construction to obtain a band element process instance record; therefore, by constructing the cross-scale fused aluminum alloy full-process digital twin, the problem that a traditional manufacturing process lacks whole-process, multi-dimensional and reversible traceability data support is solved, and the precision of aluminum alloy component quality analysis, the pertinence of process optimization and the automation level of data reporting are improved.

The invention provides a pre-buried brazing flux aluminum alloy brazing filler metal plate blank and a preparation method thereof, a pre-buried brazing flux composite aluminum alloy brazing plate strip and a preparation process and application thereof. After the mixed powder of the aluminum-silicon alloy and the brazing flux is pressed into the cylinder, the cylinder is extruded into the aluminum alloy brazing filler metal plate blank with the pre-embedded brazing flux through the semi-continuous extruding machine, the production efficiency is high, the yield is high, and the prepared aluminum alloy brazing filler metal plate blank with the pre-embedded brazing flux is uniform in component and good in extensibility. The prepared pre-buried brazing flux aluminum alloy brazing filler metal plate blank and an aluminum alloy core material are easy to roll and compound, the obtained pre-buried brazing flux composite aluminum alloy brazing plate strip has a good compound interface, does not have obvious defects such as slag inclusion, bubbles, layering and peeling, has the mechanical property meeting the requirements, has excellent ductility and good brazing performance, and is suitable for large-scale production. And the brazing effect with other aluminum components is good, the surface of a workpiece is bright, and soldering flux traces are not left. The technology can greatly simplify the manufacturing process of the aluminum heat exchanger, and can be used for large-scale industrial production.

The invention relates to the technical field of aluminum alloys, in particular to a high-strength light aluminum alloy and a preparation method and application thereof. The aluminum alloy comprises the following chemical components in percentage by weight: 3.5 to 6.5 percent of Mg, 2.5 to 5.0 percent of Zn, 0.2 to 1.0 percent of Cu, 0.1 to 0.4 percent of Mn, 0.05 to 0.25 percent of Zr, 0.05 to 0.25 percent of Sc, 0 to 0.12 percent of Fe, 0 to 0.12 percent of Si and the balance of Al and inevitable impurity elements. Wherein the mass ratio of Mg to Zn is 1.0-2.0, the total content of Mn, Zr and Sc does not exceed 0.5%, the total content of Zr and Sc does not exceed 0.38%, and the mass ratio of Zr to Sc is 0.6-1.5. By accurately controlling the contents and proportions of elements such as Mg, Zn, Cu, Mn, Zr, Sc and the like, perfect combination of high strength and light weight of the alloy is realized. The density of the alloy is smaller than or equal to 2.72 g / cm < 3 >, the yield strength is larger than or equal to 350 MPa, the tensile strength is larger than or equal to 450 MPa, the ductility is larger than or equal to 10%, the welding coefficient is not smaller than 0.75, and the exfoliation corrosion performance is not lower than the EA level.

The invention relates to the technical field of production monitoring, in particular to an aluminum alloy casting integrated frame forming process monitoring system and method based on multi-source fusion, and the method comprises the following steps: collecting melt mold filling vibration data, mold interface temperature gradient distribution and pressure waveform data, and constructing a time-space associated multi-physical field original data set; respectively extracting a characteristic frequency band energy value, a temperature change rate extreme value and a pressure pulsation amplitude value in a mold filling stage, and generating a three-dimensional characteristic vector group; adaptive fusion decision making: inputting the three-dimensional feature vector group into a pre-trained space-time convolutional network, and outputting a fusion decision index representing the microdefect formation tendency; carrying out feedforward-feedback composite regulation and control; and online self-correction is carried out. According to the method, the temperature, the pressure and the mold filling speed in the casting process are optimized, defects in the casting are reduced, and particularly in the aspect of temperature control, it is ensured that the temperature in the casting process is kept within an ideal range, so that the casting quality and the production efficiency are improved.

The invention relates to the technical field of metal defect detection, and discloses an aluminum alloy round aluminum rod surface defect image super-resolution method. The method comprises the following steps: acquiring a low-resolution original image sequence of surface defects of the aluminum alloy round aluminum rod, and synchronously acquiring gray value distribution at different illumination angles through a multi-channel optical sensor; constructing a dynamic degradation model according to pixel displacement of adjacent frames in the original image sequence, extracting cross-scale defect features in the original image sequence, and taking output parameters of the dynamic degradation model as spatial constraint conditions of a feature extraction network; and a high-resolution defect image is generated through the multi-stage residual error reconstruction network, the high-resolution image output by the reconstruction network is fed back to the dynamic degradation model, and the frequency domain response coefficient of the spatial fuzzy kernel function is updated to form closed-loop optimization. The identification degree of defect features is improved, and a reliable image data basis is provided for accurate detection of the surface defects of the aluminum alloy round aluminum rod.

The invention discloses an extrusion production process for an aluminum alloy multi-cavity profile. The extrusion production process comprises the following steps that S1, raw materials are prepared; s2, designing and manufacturing a mold; s3, pretreatment before extrusion; s4, extrusion forming; s5, cooling treatment; s6, straightening and finishing; s7, aging treatment; and S8, detecting and packaging. According to the invention, the friction is further reduced by adopting a special high-temperature lubricant and an ultrasonic vibration device in the pre-extrusion pretreatment, the precise control is realized by arranging real-time monitoring and feedback systems such as a laser range finder and an infrared thermometer in the extrusion forming process, and the cooling treatment is realized by automatically adjusting parameters by adding a corrosion inhibitor and arranging a sensor, so that the production efficiency is improved. The cooling quality of the profile is ensured; laser scanning and electrolytic polishing technologies are adopted for straightening and finishing, the straightening precision and the surface quality are improved, a circulating hot air system and a segmented aging mode are adopted for aging treatment, and the aging effect is improved.

The invention discloses a system and a method for optimizing and improving the performance of a manufacturing and processing material based on aluminum alloy parts, and relates to the technical field, the system comprises the following components: a data acquisition and storage module, a machine learning model construction module, a user interaction module and a scheme generation and optimization module; related data of an aluminum alloy material are widely collected through the data acquisition and storage module, training is carried out based on a deep learning algorithm by utilizing the machine learning model building module, an aluminum alloy material component-process-performance relation model is built, a user only needs to input target performance parameters through the user interaction module, and the aluminum alloy material component-process-performance relation model is built. The system can generate aluminum alloy material components and machining process schemes meeting the requirements through reverse calculation, optimization screening is carried out, the period of material performance optimization is greatly shortened through the process, and optimization efficiency and accuracy are improved.

Embodiments of the present disclosure generally relate to an electrostatic chuck assembly suitable for use in cryogenic applications. In one or more embodiments, an electrostatic chuck assembly is provided and includes an electrostatic chuck having a substrate supporting surface opposite a bottom surface, a cooling plate having a top surface, where the cooling plate contains an aluminum alloy having a coefficient of thermal expansion (CTE) of less than 22 ppm / ° C., and a bonding layer securing the bottom surface of the electrostatic chuck and the top surface of the cooling plate.

The invention discloses an adaptability improving system and method based on a new energy aluminum alloy part manufacturing and machining environment, and relates to the technical field of new energy aluminum alloy part manufacturing. The system comprises the following components: a data acquisition module, a digital twin model construction module, a data transmission and processing module, a quality tracing and analysis module and a decision and optimization module. According to the new energy aluminum alloy part manufacturing and processing full-process digital twinborn model, the processing equipment operation parameters, the part processing process data and the processing environment data are comprehensively collected, and the new energy aluminum alloy part manufacturing and processing full-process digital twinborn model is constructed, so that the processing process is accurately simulated and monitored in real time; the system can quickly position environmental factors and processing links which cause quality problems, and generates a processing technology optimization scheme in combination with a decision and optimization module, and the adaptive capacity of new energy aluminum alloy part manufacturing and processing to environmental changes is remarkably improved through a series of measures.

The invention provides an aluminum alloy 45-degree trimming parameter optimization method and system based on digital twinning, and relates to the technical field of aluminum alloy 45-degree trimming. The initial geometric deviation and the machining dynamic mechanical parameters of the profile are sensed in real time, and the trimming quality is predicted and the cutting parameters are optimized in combination with a digital twin model, so that the deviation caused by the dynamic deformation of the profile and the fluctuation of the clamping state is actively compensated, the trimming end face quality is remarkably improved, and the rejection rate is reduced.

The invention relates to the technical field of new energy aluminum alloy precision casting multi-modal quality monitoring, in particular to a new energy aluminum alloy precision casting multi-modal quality monitoring device and method. According to the technical scheme, the new energy aluminum alloy precision casting multi-mode quality monitoring device comprises a quality monitoring device body, an infrared thermal imager probe, a germanium single crystal protection lens, an integrated spectrometer probe debugging port, an acoustic detection microphone array and a honeycomb acoustic shielding cover. An infrared thermal imager probe is arranged on one side of the quality monitoring device main body, and a germanium single crystal protection lens is arranged on the outer side of the infrared thermal imager probe; synchronous acquisition and fusion analysis of multi-physical field data are realized by integrating six modes of spectrum, infrared thermal imaging, vibration, machine vision, acoustics and pressure deformation, and meanwhile, when the shrinkage risk is predicted by the infrared thermal imaging, a die-casting process compensation mechanism is automatically triggered to kill defects in the germination stage, so that the defect rate is greatly reduced.

The invention discloses a low-temperature minimal quantity lubrication cooling method in aluminum alloy precision machining, and relates to the field of aluminum alloy precision machining. Machining parameters such as the cutting speed and the feeding amount are determined according to the aluminum alloy material, the machining requirement and the tool performance, and finite element simulation optimization is carried out; high-purity vegetable oil-based lubricating oil is selected, a nano anti-wear agent and an antioxidant are added, and cooling liquid is prepared by mixing compressed air through vortex tube refrigeration; spraying to a processing area through a special multi-channel nozzle, and dynamically adjusting the flow; multiple sensors are used for monitoring the temperature, the tool abrasion and the surface quality, and adjustment is conducted when threshold values are exceeded; and the cooling liquid is recycled after being subjected to centrifugation and membrane filtration treatment, and the metal filing is classified, recycled and reused. The cooling and lubricating effects are good, cutting heat and tool abrasion are reduced, the machining precision is improved, and the tool service life is prolonged; environment-friendly lubricating oil is recycled, so that pollution and cost are reduced; real-time monitoring and adjustment guarantee stable machining quality, machining efficiency is improved, and high-end manufacturing requirements are met.

The invention relates to the technical field of aluminum foil processing, in particular to a method for producing high-stability 3102 alloy air-conditioning foil in a short process, which comprises the following steps of: smelting, continuously casting and continuously rolling an aluminum alloy raw material to obtain a strip, directly trimming the strip, rolling the strip on a cold rolling unit, preparing a cold-rolled coil with the thickness of 0.15-0.2 mm after three-pass rolling, rolling the cold-rolled coil by an aluminum foil rolling mill, and rolling the cold-rolled coil by an aluminum foil rolling mill to obtain the high-stability 3102 alloy air-conditioning foil. The tensile strength of the aluminum foil finished product is 135-139 Mpa, the ductility is larger than or equal to 19%, and the cupping is larger than or equal to 5.9 mm. The aluminum foil finished product is suitable in tensile strength, small in fluctuation range, higher in ductility and cupping value, capable of better meeting the use requirements of air conditioner foil, capable of guaranteeing the product quality and meanwhile capable of improving the product quality. According to the method, the production process is greatly shortened, the production cost is reduced, and the production efficiency is improved.

The invention belongs to the technical field of aluminum alloy materials, and particularly discloses a preparation method of a cast-rolled 8021 alloy aluminum foil, an 8021 alloy blank with the thickness of 6-8 mm is produced through cast rolling, the blank is subjected to direct homogenizing annealing under the condition of not cooling, is rolled through a cold rolling production process, and then is subjected to edge cutting, secondary intermediate annealing and foil rolling to be subjected to multi-pass rolling to obtain the finished product with the thickness. Compared with a traditional direct-cooling cast ingot hot rolling process, multiple links such as hot-rolled plate ingot casting, ingot blank sawing and face milling, uniform annealing and large-machining-amount hot roughing mill cogging rolling are omitted, energy is saved, consumption is reduced, carbon dioxide emission is reduced, the performance of a finished product is equal to or even superior to that of a hot-rolled product, and the use requirements of customers are met.

The invention relates to an additive manufacturing method and application of an aluminum-based silicon carbide composite material complex component, and the additive manufacturing method of the aluminum-based silicon carbide composite material complex component comprises the following steps: step 1, uniformly mixing silicon carbide powder and aluminum alloy powder, and drying; 2, establishing a structural model for the target part, and importing the structural model into selective laser melting forming equipment; thirdly, selective laser melting forming is conducted; fourthly, linear cutting and surface treatment are conducted; and fifthly, hot isostatic pressing treatment is conducted. The invention further provides application of the aluminum-based silicon carbide composite material complex component to precise structural components such as aviation structural components, guided missile and satellite components and optical instruments. According to the method, the problem of subsequent large-allowance removal of the aluminum-based silicon carbide composite material component is solved, the wettability between the aluminum alloy and the silicon carbide particles is improved, the mechanical property meets the application requirement, and the aluminum-based silicon carbide structural component with stable performance is obtained.

The invention relates to the technical field of bar conveying, in particular to tungsten aluminum alloy production line production automation conveying equipment which comprises a rack and a chain scraper conveyor installed on the rack, a plurality of bearing tables are evenly installed on the chain scraper conveyor in the circumferential direction, and centering fixing mechanisms are installed on the bearing tables. An interlocking mechanism for connecting and locking the two adjacent bearing tables is mounted on the bearing tables, and a guide limiting mechanism for guiding the movement of the bearing tables is mounted on the rack. Through linkage cooperation of the supporting plate, the fixing assembly and the centering assembly, a tungsten rod placed on the supporting plate is centered, clamped, pressed and fixed, and the tungsten rod is prevented from moving and deviating in the transportation process; the connecting assemblies, the locking assemblies and the driving assemblies are in linkage fit to lock the two adjacent bearing tables for conveying the tungsten rods, so that the multiple bearing tables for conveying the tungsten rods are connected into a whole, and the stability of the bearing tables during tungsten rod conveying is greatly improved.

The invention discloses a full life cycle quality tracing system and method based on aluminum alloy parts, and relates to the technical field of quality tracing, the system comprises a multi-source heterogeneous data acquisition module, a data fusion and preprocessing module, a quality prediction and trend analysis module and a quality optimization decision module; according to the full-life-cycle quality tracing system based on the aluminum alloy parts, comprehensive and accurate management of production data is achieved, the system integrates a multi-source heterogeneous data acquisition module, structured production data, semi-structured document data and non-structured image data can be efficiently acquired and integrated, and the quality of the whole life cycle quality tracing system based on the aluminum alloy parts is improved. The method has the advantages that a solid foundation is provided for quality tracing, in the data fusion and preprocessing stage, data cleaning, conversion and feature fusion algorithms are adopted, the accuracy and availability of data are improved, the data processing efficiency is improved, and powerful data support is provided for subsequent quality prediction, trend analysis, quality tracing and root positioning.

When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.

The invention relates to the technical field of numerical control machining process optimization, in particular to an aluminum alloy milling parameter optimization method based on an improved Bayesian neural network, and the method comprises the following steps: S1, building an aluminum alloy thin-wall part milling finite element model based on a Johnson-Cook constitutive model; s2, carrying out a single-factor milling experiment, and verifying the reliability of the finite element model; s3, constructing a Bayesian neural network model fused with a multi-head attention mechanism, and establishing a mapping relation between process parameters and surface quality indexes; s4, establishing a multi-objective optimization model based on the MHA-BNN prediction model, and solving by adopting an NSGA-II algorithm; and S5, performing experimental verification and analysis on an optimization result. According to the method, a multi-head attention mechanism is introduced into a Bayesian neural network, and a milled surface roughness and residual stress probability prediction model is constructed; and a multi-objective optimization framework fusing physical constraint and data driving is established, collaborative optimization of the surface roughness, the residual stress and the processing efficiency is realized, and meanwhile, the problem that a traditional deep learning method is insufficient in prediction precision under a small sample condition is solved.

The invention belongs to the technical field of aluminum alloy preparation, and particularly relates to an Al-Cu-X eutectic phase reinforced aluminum alloy material for additive manufacturing. According to the Al-Cu-X eutectic phase reinforced aluminum alloy material, besides Al, the Al-Cu-X eutectic phase reinforced aluminum alloy material comprises Cu, Mg, V, eutectic elements and inevitable impurity elements, the eutectic elements comprise at least one of Fe, Co, Mn and Ni, and original alloy powder is obtained after raw materials are pretreated; and the original alloy powder is used for laser melting printing forming, and the Al-Cu-X eutectic phase reinforced aluminum alloy material is obtained. According to the method, the multiphase reinforced aluminum alloy material is controllably prepared through additive manufacturing, the formability of the aluminum alloy is improved and the overall performance of the aluminum alloy is enhanced by optimizing the component proportion of the aluminum alloy through a method of combining eutectic reaction and fine grain strengthening, and the composite performance such as high strength, high toughness and high temperature resistance of the aluminum alloy is improved.

The invention discloses an integrated insert rear floor, a vehicle body and a manufacturing method of the integrated insert rear floor. The integrated insert rear floor comprises an aluminum alloy die-cast rear floor body and a plurality of steel inserts pre-embedded in the aluminum alloy die-cast rear floor body, and the connecting edges of the steel inserts and the rear floor body are filled with molten aluminum to form interlocking. The steel inserts comprise various connecting beams, wheel cover reinforcing pieces and front floor connecting inserts. During manufacturing, the steel insert is placed in a die for high-pressure die-casting of aluminum alloy. The vehicle body comprises the integrated insert rear floor and a lower vehicle body front structure, and the front floor connecting insert of the rear floor is welded to the lower vehicle body front steel structure. By embedding the steel insert, the connection problem of the floor and the steel vehicle body after die casting is solved, a large number of steel-aluminum connection points are omitted, the influence on an existing production line is small, and the integration level, precision and rigidity are improved.

The invention relates to the field of aluminum materials, and provides an automobile corrosion-resistant aluminum material and a preparation method thereof.The automobile corrosion-resistant aluminum material is prepared from cerium oxide loaded aluminum oxide nanorods, scandium / boron nitride nanotubes, zirconium powder, magnesium powder, copper powder, manganese powder, silicon carbide nanoparticles, TiB2 nanoparticles, aluminum powder and stearic acid. Wherein the cerium oxide loaded aluminum oxide nanorod is composed of an aluminum oxide nanorod and cerium oxide nanoparticles loaded on the surface of the aluminum oxide nanorod, and the scandium / boron nitride nanotube is composed of a boron nitride nanotube and a scandium nanolayer uniformly coated on the surface of the boron nitride nanotube. The material is prepared through mechanical ball milling, cold isostatic pressing forming, vacuum sintering and aging treatment, and finally the aluminum-based composite material containing the Al3Sc nano precipitated phase and the boron nitride nanotube reinforced phase is formed. And an Al3Sc precipitated phase and an aluminum matrix form a coherent interface, so that the strength, the corrosion resistance and the wear resistance of the material are improved. Through nanostructure optimization, high performance of the aluminum alloy is achieved, and the aluminum alloy is suitable for the fields of automobiles, aerospace and the like.