5075 results about "Titanium alloy" patented technology

The invention provides a titanium alloy thin-wall part high-precision milling method and system based on dynamic compensation, and the method comprises the following steps: constructing a multi-physics field coupling model based on the constitutive relation and milling process parameters of a titanium alloy material; according to the method, a multi-physical field coupling model represented by dynamic parameters is constructed, structural feature recognition and coupling weight dynamic allocation are combined, and the model is iteratively optimized through a detection result after processing, so that the problem that a traditional prediction model is disjointed from an actual working condition is solved; by building a real-time monitoring and feedback system and combining a dynamic compensation closed-loop mechanism, non-interruption linkage of monitoring-adjustment in the machining process is achieved, and the problem that the hysteresis of a traditional compensation method is remarkable is solved; the initial compensation amount is optimized through a multi-objective genetic algorithm, a self-adaptive processing path strategy is adopted, dynamic parameter adjustment of structure adaptation is combined, a traditional single compensation strategy is replaced, and the problem of dynamic rigidity change in the complex curved surface and material removal process can be flexibly solved.

The invention relates to the technical field of precision manufacturing nondestructive testing and machine vision image processing, in particular to a titanium alloy ring piece surface microcrack defect detection system based on machine vision, which comprises an image acquisition module for acquiring a to-be-processed image data set; the manifold calibration module is used for acquiring a main direction field of background textures and converting the to-be-processed image data set into a standard space image with aligned texture flow; the sparse decomposition module is used for acquiring a shear wave coefficient and decomposing the shear wave coefficient into a low-rank component matrix and a sparse component matrix; the reconstruction judgment module is used for generating a microcrack defect distribution diagram, obtaining a residual image and generating a final defect distribution diagram; the self-adaptive feedback module is used for adjusting the sparsity constraint weight in the robust principal component analysis algorithm; according to the method, the problem of signal aliasing caused by frequency overlapping of cracks and background textures is effectively solved, and the detection sensitivity under the strong texture background is remarkably improved.

The invention discloses an analysis method and system for a dynamic recrystallization structure form of a titanium alloy based on machine learning and a medium, and belongs to the technical field of metal material microstructure quantitative characterization, a Gleeble thermal compression test is processed on a titanium alloy to be tested, multi-modal data is collected, a DRX probability graph is output based on a DRX segmentation model, and then the characteristics of DRX are extracted. And respectively inputting the DRX features into the first-level classifier, carrying out PCA dimension reduction processing, splicing and fusing the prediction probability and the features after dimension reduction, and inputting the spliced and fused features into a second-level classifier to output a two-dimensional DRX segmentation map. Based on the FIB-SEM tomography sequence image, reconstructing a three-dimensional model of the DRX crystal grain so as to carry out consistency verification on the two-dimensional DRX segmentation image; and evaluating a correlation coefficient of the three-dimensional model and the two-dimensional DRX model, and finally carrying out three-dimensional visualization on the space aggregation of the DRX crystal grains. According to the method, the automation degree and efficiency of dynamic recrystallization proportion and type identification are remarkably improved.

The invention discloses a titanium alloy microscopic structure prediction method and system based on a conditional generative adversarial network and a storage medium, and belongs to the following steps: firstly, constructing a process-structure mapping model, and taking the output of the model as a rule constraint condition; inputting the random noise vector and the rule constraint condition into a conditional generative adversarial network to generate a prediction image; according to the generative adversarial network, thermal dynamic constraints based on physical quantities of microscopic structures are introduced in the training process, so that the interpretability of a prediction result is improved. And carrying out quantitative comparison on the predicted image and the real image, verifying the consistency of the statistical characteristics, and if the verification is passed, outputting a prediction result. According to the method, end-to-end prediction from process parameters to microscopic structure images is realized, the limitation that only symbolization or parameterization prediction can be carried out in a traditional method is broken through, and the intuition, the interpretability and the engineering application value of the method are remarkably enhanced.

The invention relates to the technical field of metal material detection, in particular to a titanium alloy bar machining quality detection method and system, and the method specifically comprises the steps: carrying out the superpixel segmentation of the section of a titanium alloy bar, constructing a mirror image edge texture saliency value of a superpixel block based on the proportion of edge points in the superpixel block and the edge gradient, and carrying out the detection of the machining quality of the titanium alloy bar. Constructing the mirror image texture intensity of the titanium alloy bar by combining the gray level distribution concentration characteristics of the titanium alloy bar, and performing image segmentation on the section of the titanium alloy bar; and in each segmented region, based on the edge line fuzzy degree difference and the pixel gray level difference of each super-pixel block and the rest of super-pixel blocks, combining a mirror image edge texture saliency value to construct a segregation evaluation value of each super-pixel block, and based on the segregation evaluation value, carrying out titanium alloy bar segregation quality defect detection. The titanium alloy bar segregation defect identification capability is enhanced, the titanium alloy bar segregation defect detection accuracy under the titanium alloy bar mirror image scene is improved, potential problems can be found earlier, missing detection is avoided, and the defective rate is reduced.

The invention belongs to the technical field of medical instruments, and particularly relates to a spinal epidural ventral side double-wing-shaped stimulation electrode and motion function reconstruction system, the spinal epidural ventral side double-wing-shaped stimulation electrode and motion function reconstruction system comprises two wing panels, each wing panel comprises a flexible substrate, the flexible substrate is provided with two bifurcated preset-curvature double-wing structures; the electrode contact array is integrated on the flexible polar plate through a bonding pad; according to the double-wing-shaped flexible substrate, through a double-wing structure with a preset curvature, after being unfolded under the driving of a nickel-titanium alloy framework, the double-wing-shaped flexible substrate accurately covers a spinal cord ventral side and double-side anterior angle motor neuron pool, and the problem that a traditional single-piece / rod-shaped electrode can only cover a back side sensing area and cannot cover a back side sensing area is solved. The ventral motor neuron group cannot be directly activated; a stimulation target spot is transferred to a ventral functional core area from a dorsal non-target area for the first time, and the anatomical suitability bottleneck of motor function reconstruction is solved.

The invention discloses a fuse wire additive manufacturing method for regulating and controlling the strength of titanium alloy by adding rare earth oxide, which comprises the following steps of: 1, ultrasonically stirring and mixing rare earth oxide nano powder and ethanol solution to obtain turbid liquid; 2, polishing the surface of the titanium or titanium alloy substrate until the roughness is not greater than Ra1.6; thirdly, the surface of a substrate is evenly coated with the turbid liquid, after drying, fuse wire additive manufacturing of titanium or titanium alloy wires is carried out under inert atmosphere protection, and the titanium alloy with the improved strength is obtained; the fuse wire additive manufacturing process comprises the steps that layer-by-layer deposition is conducted, and after each layer is deposited and completely solidified and cooled, the surface of the deposited layer is coated with turbid liquid and dried. According to the method, coating of the turbid liquid containing the rare earth oxide and the fuse wire additive manufacturing process are combined, the titanium or titanium alloy containing the rare earth oxide and uniform in component is prepared, metallurgical bonding of the rare earth oxide and the titanium or titanium alloy wire is achieved, and the method is suitable for the technical field of metal additive manufacturing.

The present invention relates to the field of titanium alloy smelting technology and discloses a method for preparing a high-performance two-phase titanium alloy at low cost by melting flat ingots in an electron beam cooling hearth furnace. The method comprises a two-phase titanium alloy, wherein the nominal composition of the two-phase titanium alloy is proportioned, with TC4 titanium alloy return material as the main material, supplemented by an intermediate compensating alloy, and an improved charging method. Subsequently, an electron beam cooling hearth furnace is used to melt the two-phase titanium alloy ingot. The present invention uses TC4 titanium alloy return material as the main material and melts the two-phase titanium alloy ingot in an electron beam cooling hearth furnace to produce a directly rolled two-phase titanium alloy ingot, eliminating the subsequent blanking and forging process. This not only reduces raw material costs but also shortens the process flow, thereby achieving the goal of low-cost production of the two-phase titanium alloy.

The invention relates to the technical field of defect detection systems, and discloses a titanium alloy surface crack defect detection system based on deep learning. According to the system, a crack feature extraction module is used for collecting a titanium alloy surface image and extracting multi-scale crack features including crack trend distribution features and micro-crack density features; the multi-modal data fusion module is used for receiving the multi-scale crack features and performing space-time alignment on the multi-scale crack features and ultrasonic reflection wave features collected in real time to generate a fusion defect feature matrix; the dynamic learning engine module is used for constructing a crack propagation prediction model according to the historical change trend of the fusion defect feature matrix and outputting a dynamic defect response vector; the defect positioning module is used for mapping the dynamic defect response vector to a titanium alloy surface three-dimensional coordinate space to generate a defect position thermodynamic diagram; and the self-adaptive scanning control module is used for analyzing the defect confidence of each area in the defect position thermodynamic diagram and dynamically adjusting the scanning path and the focal length parameter of the industrial camera.

The invention discloses a closed-loop self-adjusting method for online defect identification and real-time feedback in the additive manufacturing process of a titanium alloy component based on intelligent sensing, belongs to the field of laser additive manufacturing, and solves the key problems of insufficient defect identification capability, quality control lag and the like in the current additive manufacturing process. The method is based on a multi-mode sensor architecture, integrates an infrared thermal imager, a molten pool camera and a spectrum sensor, and synchronously monitors a molten pool thermal field, radiation characteristics and surface topography. Traditional image processing and signal analysis are adopted to extract defect features such as air holes and cracks, and calibration is implemented in combination with off-line detection such as industrial CT. The recognition result is analyzed in real time through the central control platform, causes are automatically diagnosed based on defect types and distribution characteristics, parameters such as laser power and scanning paths are dynamically adjusted by matching a preset control strategy, and defect suppression and online repair are achieved. And a closed-loop self-adaptive dynamic adjustment mechanism improves the forming quality and reliability. The method is suitable for aerospace and other scenes with extremely high requirements for the quality of large complex titanium alloy components.

The invention belongs to the technical field of electroplating process optimization, and particularly discloses a titanium alloy surface electroplating control method which comprises the following steps: dynamically generating a hanger posture configuration scheme based on workpiece three-dimensional contour data acquired in real time; a bubble distribution image and electroplating liquid flow field data are synchronously collected, and a bubble-flow field coupling feature set is generated through multi-modal fusion; performing real-time linkage adjustment on the rotation speed and the swing amplitude of the workpiece according to the coupling feature set; after electroplating is completed, plating thickness, edge integrity and surface defect data are collected, and a multi-source plating data set is formed by combining workpiece position information; historical data and real-time data are integrated to carry out hanger layout adjustment judgment, and hanger spacing dynamic reconstruction optimization is started when adjustment is needed. According to the method, multi-parameter cooperative control and closed-loop quality optimization in the electroplating process are achieved, the uniformity and integrity of a titanium alloy workpiece coating are remarkably improved, and generation of bubble related defects is effectively restrained.

The utility model provides a titanium alloy pipe surface polishing device which comprises a machine frame, the upper end of the machine frame is provided with a double-roller transmission machine, a pipe outside polishing machine and a pipe inside polishing machine, the double-roller transmission machine can drive a pipe to be machined to rotate and transmit the pipe forwards, the top of the double-roller transmission machine is provided with a pressing component used for pressing the pipe, and the double-roller transmission machine is connected with the pipe outside polishing machine. The pipe outside polishing machine comprises a first polishing wheel and a second polishing wheel, and the pipe inside polishing machine is arranged in the advancing direction of the pipe, moves relative to the pipe and can extend into the pipe to polish the inner wall of the pipe. The double-roller conveyor is adopted to drive the pipe to rotate and be conveyed forwards, and internal and external polishing is carried out on the same station at the same time. The pipe outside polishing machine polishes the outer wall of the pipe through double polishing wheels, and the pipe inside polishing machine polishes the inner wall of the pipe through a long rod capable of stretching into the pipe. According to the synchronous polishing, the clamping frequency and the station switching time of the pipe are obviously reduced, and the polishing efficiency is greatly improved.

The invention discloses intelligent detection equipment for internal defects of a titanium alloy cartridge receiver, and relates to the technical field of nondestructive testing, the intelligent detection equipment comprises a supporting base, a self-adaptive electromagnetic active vibration isolation assembly and a magnetic suspension pneumatic fine adjustment assembly, and by means of the synergistic effect of two core assemblies, namely the self-adaptive electromagnetic active vibration isolation assembly and the magnetic suspension pneumatic fine adjustment assembly, the internal defects of the titanium alloy cartridge receiver are detected. Ultra-stable vibration isolation and nanoscale precise positioning of the industrial CT three-coordinate measuring machine in the precise scanning process are achieved, and different from a traditional lag and friction scheme depending on passive air floating vibration isolation and mechanical transmission positioning, high-precision scanning operation is more stable and more precise, and the precision of the industrial CT three-coordinate measuring machine is improved. Firstly, a magnetic suspension friction-free support of the magnetic suspension pneumatic fine adjustment assembly is matched with a pneumatic nozzle matrix in a zero-contact and zero-abrasion mode, the bottleneck that a traditional lead screw guide rail mechanism is large in positioning error due to friction stick-slip and idle stroke is broken through, stable support is achieved through non-contact suspension, and accurate micro-power output is achieved through pneumatic counter-acting force; and the full-scale range from macroscopic positioning to nanoscale fine adjustment is ensured.

The invention relates to an additive-welding integrated manufacturing cooperative control system for a TA15 titanium alloy material aviation complex component. The additive-welding integrated manufacturing cooperative control system comprises a state sensing module, a control module and a control module, wherein the state sensing module is used for collecting multi-source physical process state data of the aviation complex component in the welding increasing process; the state modeling module is used for performing fusion modeling to obtain a high-dimensional state data set; the strategy generation module is used for constructing a multi-source cooperative control strategy based on the high-dimensional state data set; the anomaly identification module is used for identifying an abnormal action under a multi-source cooperative control strategy and inserting physical action compensation; the action coordination module is used for generating a physical action instruction based on a multi-source coordination control strategy and physical action compensation and performing dynamic coordination; the auxiliary control module is used for matching and correcting physical action instructions of historical tasks according to the working condition similarity when a new task is switched; and the optimization updating module is used for collecting physical action instructions to carry out performance evaluation and carrying out feedback optimization on a multi-source cooperative control strategy after each task is finished.

The invention discloses a structure characteristic quantitative extraction method and system for a titanium alloy microstructure image, and the method comprises the steps: obtaining the data of a titanium alloy microstructure grain image, and carrying out the data marking and image preprocessing; constructing and training a ResNet-based classification model, and distinguishing different tissues in various titanium alloy microstructure grain images; constructing a segmentation model TiGrainsU-Net by using the U-Net and an attention mechanism, inputting original microstructure grain image data and labeled mask data into the segmentation model for model training, and predicting different phase structures in the titanium alloy microstructure image by learning characteristics of different phase grains; performing multi-stage image optimization processing on a segmentation result, clustering different phases by using a final segmentation result, and calculating a quantization parameter; according to the method, the recognition capability of the model on boundary features and local detail features is improved, the segmentation accuracy is improved, and the precision and robustness of quantization parameter calculation are improved.

The invention belongs to the technical field of titanium alloy materials, and discloses a Ti65 alloy bar for eliminating microtexture and a manufacturing method thereof, and the manufacturing method comprises the following steps: carrying out homogenization treatment and cogging forging on an alloy ingot, heating an alloy forging stock to 30-55 DEG C above a beta phase transformation point, and carrying out one-heating-number primary upsetting and drawing deformation; the alloy forging stock subjected to primary upsetting deformation is heated to 5-15 DEG C above the beta phase transformation point, and secondary upsetting deformation of 1-2 heating numbers is carried out; the alloy forging stock subjected to secondary upsetting deformation is heated to 75-30 DEG C below the beta phase transformation point, and third upsetting deformation with 6-8 heating numbers is carried out; and shaping the alloy forging stock subjected to the three times of upsetting and drawing deformation at 75-30 DEG C below the beta phase transformation point, and then carrying out solution treatment and aging treatment to obtain the Ti65 alloy bar with the microtexture eliminated. By optimizing the forging process and parameters, micro-textures and strong deformation textures in the alloy structure are basically eliminated.

The invention discloses an environment-friendly electrolyte for anodic oxidation of titanium and titanium alloy workpieces and an electrolytic coloring method. The electrolyte comprises 8-12 parts of lactic acid, 5-10 parts of sodium tartrate, 2-5 parts of sodium bicarbonate and the balance of deionized water. The electrolytic coloring method comprises the steps of pretreatment, anodic oxidation coloring and aftertreatment. The pretreatment comprises alkali washing oil removal, water washing and laser treatment; and an electrolyte mixed by 8-12 parts of lactic acid, 5-10 parts of sodium tartrate, 2-5 parts of sodium bicarbonate and the balance of deionized water is used for anodic oxidation coloring. The post-treatment comprises sealing treatment and drying. According to the technical scheme, the technical problems that the anodic oxidation coloring technology is completely free of fluorine, low in toxicity and safe to operate, and the oxidation waste liquid is free of pollution and easy to treat can be solved, existing pretreatment steps can be simplified, and meanwhile uniform coloring is achieved.

The invention relates to the technical field of titanium alloy bar detection, and discloses a titanium alloy bar quality detection system and method. The system comprises a multi-modal data acquisition module, a detection reference dynamic optimization module, a data standardization processing module, a multi-modal feature fusion module, an intelligent defect identification and evaluation module, a quality grade evaluation module and a quality detection report generation module. When the quality of the titanium alloy bar is detected, through a multi-mode nondestructive detection mechanism integrating ultrasonic detection data, optical surface detection data and eddy current electromagnetic detection data, all-dimensional defect information of the interior, the surface and the near surface of the bar is synchronously obtained, and complementation and cross validation of the multi-mode detection data are achieved; the problem of limitation of a single sensor detection visual angle is solved, the missed detection and misjudgment risks are reduced, and the comprehensiveness and reliability of a defect detection result are ensured.

The invention relates to the technical field of ultrasonic detection, in particular to an ultrasonic imaging method and system for ultrasonic detection of a titanium alloy bar, and the method comprises the steps: obtaining an ultrasonic detection signal of each detection point; the ultrasonic detection signals of the detection points form an initial imaging area according to the combined probing path, and a state label about amplitude deviation in the initial imaging area is recognized; performing conditional mapping on the frequency spectrum difference of each detection point and the interval time during detection by using the state label of the initial imaging area to obtain the difference classification of each detection point; according to the difference classification of each detection point, identifying the difference guidance of the current detection path, converting the corresponding detection point into a displacement component of the surface of the titanium alloy bar according to the combination position of each detection point in the difference guidance, analyzing partial data of a minimum value, a minimum value inflection point and an offset standard value of the displacement component distribution, and calculating the displacement of the titanium alloy bar. Identifying the surface defect form of the titanium alloy bar; and the titanium alloy bar defect identification accuracy and efficiency are realized.

The invention relates to the technical field of titanium alloy detection, and discloses a titanium alloy wire performance detection method, equipment and system. The method comprises the following steps: acquiring real-time force value displacement data of a tensile test and echo signal data of ultrasonic detection, and processing to obtain smooth force value displacement data and spectrum characteristic parameters; performing feature layer fusion on the yield strength, the tensile strength, the peak frequency and the amplitude attenuation rate to construct a first multi-dimensional feature matrix; inputting a pre-trained deep belief network model, and predicting mechanical properties such as elongation and hardness value; and comparing with a preset threshold value, marking unqualified items and generating a detection report. According to the method, through multi-source data fusion and advanced algorithm processing, the comprehensiveness and accuracy of detection are improved, efficient evaluation of the performance of the titanium alloy wire is achieved, and the method is suitable for the strict detection requirements for the quality of the titanium alloy wire in the fields of aerospace, medical instruments and the like.

The invention relates to an anorthite material and a preparation method thereof. The adopted technical proposal comprises the following steps of: according to (ZL200510019664.3) patent technology, namely a method for preparing titanium and a titanium alloy by utilizing titanium-containing furnace slag, taking molten tailings which is extracted with the titanium alloy as a raw material, adding 20 to 50 weight percent of silica, 0 to 60 weight percent of clay and 0 to 40 percent aedelforsite, and cooling a melt to obtain the anorthite material after the mixture is completely molten and a bath composition is uniform; or taking cold tailings extracted with the titanium alloy as the raw material, adding 20 to 50 weight percent of the silica, 0 to 60 weight percent of the clay and 0 to 40 percent the aedelforsite, carrying out mix grinding on the raw material and the admixture until the particle size is less than 0.1 mm, performing blank compression, and calcining the mixture at a temperature of between 1,200 and 1,400 DEG C to obtain the anorthite material. The method takes the tailings extracted with the titanium as the raw material, saves precious bauxite resources, has low cost, ensures that industrial residue is utilized with high added value, is environment-friendly and has simple process.

The invention discloses a TC4 titanium alloy preformed blank, a TC4 titanium alloy plate with a full lamellar structure and a preparation method of the TC4 titanium alloy plate, and belongs to the technical field of titanium alloy machining. According to the method, TC4 alloy powder prepared through hydrogenation dehydrogenation and plasma rotating electrode atomization serves as a raw material, and a high-density binary structure preformed blank is prepared through a three-step type hot isostatic pressing technology; a pure titanium sheath is adopted for packaging, two-heating-number rolling is conducted through the sheath, and the plate shape is optimized through convexity design of a working roller and dynamic roller bending force control; and after rolling, solid solution and two-stage aging composite heat treatment are combined, the head and the tail are cut off, and the TC4 titanium alloy plate is obtained. The problem of tissue segregation of a traditional cast ingot is solved through powder metallurgy, the obdurability is improved, and the anisotropy is reduced; and meanwhile, the raw material cost is reduced, the production period is shortened, the yield is increased, the surface quality is improved, and a reliable scheme is provided for green and efficient preparation of high-performance titanium alloy plates in the aerospace field.

The invention relates to the technical field of metal plastic forming, and discloses a titanium alloy radial forging reduction rate collaborative optimization method based on material testing, which comprises the following steps of: acquiring dynamic characteristic data in a forging process in real time by acquiring multi-dimensional material performance parameters, and constructing a multi-target collaborative optimization model; and intelligent collaborative configuration of the reduction rate parameters is realized by adopting a self-adaptive weight distribution strategy. And a thermal coupling factor normalization equation and a phase field free energy functional normalization model are established, and the technical problems that in a traditional forging process, due to empirical configuration of reduction rate parameters, the structure is uneven, and residual stress exceeds the standard are solved. A lightweight model is deployed through edge computing nodes, millisecond-level dynamic correction of an optimization scheme is realized in combination with a 5G industrial private network, and the grain size qualification rate and the size precision of the titanium alloy forgings are improved. The method improves the yield of the grain size of the forge piece, ensures that the residual stress of the forge piece is reduced, stably controls the size precision, and improves the batch stability of high-end titanium alloy parts.

The invention discloses a titanium alloy based on lamellar alpha phase and nanophase precipitation and a preparation method of the titanium alloy, belongs to the field of titanium alloy materials, and aims to solve the bottleneck that strength and work hardening of a high-strength titanium alloy are difficult to cooperate. The titanium alloy comprises, by weight, 2.0%-7.5% of Al, 1.0%-6.0% of V, 1%-8% of x (x is at least one eutectoid beta stable element of Fe, Mn, Cr, Ni and Cu) and the balance Ti and impurities. And the beta-phase molybdenum equivalent [Mo] eq is controlled to be 5.0-10.0. The preparation method comprises the following steps: 1) smelting an ingot for three times in a vacuum consumable electric arc furnace, and cutting a dead head after scaling and flaw detection; (2) carrying out hot rolling at 810-950 DEG C in an alpha + beta two-phase region with the accumulative deformation amount of 75-95%, and constructing a multi-scale lamellar alpha phase, and (3) carrying out solid solution for 30-120 minutes at 700-850 DEG C, rapidly cooling at 50-250 DEG C / s, and inducing the precipitation of a nano eutectoid compound. Aging treatment is not needed, the yield strength is greater than 900 MPa, the work hardening amount is greater than 150 MPa, the elongation is greater than or equal to 15%, the process is simple and easy to industrialize, and the method can be applied to the fields of aerospace, ocean engineering and the like.

The invention discloses a 1500MPa-grade titanium alloy bar and a preparation method thereof, and belongs to the field of titanium alloy preparation. The 1500MPa-grade titanium alloy bar comprises the following chemical components in percentage by mass: 5.5 to 6.5 percent of V, 4.5 to 5.5 percent of Mo, 3.0 to 4.0 percent of Al, 2.5 to 3.5 percent of Zr, 1.5 to 2.5 percent of Cr, 1.5 to 2.5 percent of Nb, 0.9 to 1.1 percent of Fe and the balance of Ti and impurities. The preparation method comprises the following steps: preparing raw materials according to the components, pressing the raw materials into electrode blocks, welding to obtain consumable electrodes, and performing multi-vacuum consumable smelting to obtain cast ingots; the cast ingot is subjected to cogging forging in a beta area, multi-heating-number upsetting and drawing deformation in the beta area and forged into a bar in a two-phase area; and through multi-pass rolling and multiple solid solution aging heat treatment, the 1500MPa-grade titanium alloy bar is obtained, meanwhile, the ductility is kept to be 6% or above, and the requirement of future aerospace for high-performance titanium alloy is met.

The invention discloses a plasma surface activation pre-bonding-femtosecond laser connection integrated process, belongs to the technical field of advanced dissimilar material precision connection, and particularly relates to a multi-material interface efficient connection method based on plasma surface activation pre-bonding and femtosecond laser processing. The method is suitable for high-strength and low-thermal-damage heterogeneous bonding of transparent materials (such as glass, quartz and sapphire) and transparent materials or metal materials (such as titanium alloy, stainless steel and invar alloy). According to the method, interface atomic-scale cleaning and chemical activity regulation and control are achieved through plasma activation, interface connection of the two materials is induced by combining the femtosecond laser ultrafast nonlinear effect, and the bottlenecks that in a traditional connection technology, optical contact depends on a mechanical clamp, and heat input is uncontrollable are broken through; and an innovative solution is provided for cross-material interface functional manufacturing in the fields of photoelectric device packaging, optical-electronic integrated systems and the like.

The invention discloses a short-process low-cost preparation method for forging a TC4 titanium alloy bar. The short-process low-cost preparation method comprises the following steps: (1) cogging and forging a beta-phase region; (2) performing drawing-out thermal deformation on an alpha + beta region; (3) static quasi-beta annealing water quenching treatment; (4) carrying out thermal deformation in a near alpha + beta region; and (5) alpha + beta area small-deformation multi-tempering drawing-out finish forging forming is carried out. The method has the advantages that the requirements of uniform orientation distribution, sufficient grain refinement, process simplification and convenient operation in the short-process low-cost TC4 titanium alloy manufacturing bar are met, the structure uniformity of the large bar is improved, the obtaining of a homogeneous fine structure is facilitated, the requirement of nondestructive testing of the flaw detection clutter level is met, and the product quality is improved.

The invention relates to the technical field of image data processing, in particular to a titanium alloy plate section deformation identification method based on machine vision, and the method comprises the steps: firstly obtaining an actual contour and a standard contour of a plate section, and generating a deviation sequence; performing multi-scale wavelet transform on the sequence, calculating coherent energy of each scale, and constructing a coherent energy sequence according to a scale sequence; then, based on the coherent energy sequence, extracting a first characteristic value and a second characteristic value which quantify the defect frequency attribute and the structure complexity respectively; and finally, identifying the deformation type according to the position of a two-dimensional feature point formed by the two feature values in a preset feature space. According to the invention, high-precision classification of various deformation defects such as burrs and waves is realized, and the accuracy and reliability of automatic detection are improved.

The invention discloses a novel electrolytic tank pipeline filter and a self-cleaning system. The novel electrolytic tank pipeline filter comprises a multi-stage filtering part, the self-cleaning system and an intelligent control system, the multi-stage filtering part comprises multi-stage filter elements arranged in the material pipeline, and the multi-stage filter elements are arranged from large to small according to the filtering particle size to form a filtering gradient; the self-cleaning system acts on the multi-stage filter element part at the same time or in a time-sharing manner on the basis of a fluid reverse recoil principle; the self-cleaning system is combined with pulsating flushing control, so that the filter element is separated from a filter cake at low loss; the multi-stage gradient filtration is adopted, impurities are efficiently and accurately intercepted, the filter elements with the particle sizes from large to small are arranged in a gradient mode, the first-stage titanium alloy filter element intercepts large particles, the second-stage polytetrafluoroethylene membrane filters tiny impurities, the efficiency is improved through graded interception, the loss of the filter elements is reduced, and the material purity and the hydrogen production quality are guaranteed. The multi-element self-cleaning technology is adopted, low-loss deep cleaning is achieved, and the self-cleaning system integrates multiple technologies such as fluid reverse backflushing, pulsating flushing, ultrasonic vibration and a pulsed electric field.

The present application relates to the technical field of metal plastic forming, and discloses a titanium alloy radial forging reduction rate collaborative optimization method based on material testing, which acquires dynamic characteristic data of a forging process in real time through multi-dimensional material performance parameter collection, constructs a multi-objective collaborative optimization model, and realizes intelligent collaborative configuration of the reduction rate parameter by using an adaptive weight distribution strategy. A thermal coupling factor normalization equation and a phase field free energy functional normalization model are established to solve the technical problems of uneven structure and excessive residual stress caused by the empirical configuration of the reduction rate parameter in the traditional forging process. A lightweight model is deployed through an edge computing node, and millisecond-level dynamic correction of the optimization scheme is realized in combination with a 5G industrial private network, thereby improving the grain size qualification rate and size accuracy of titanium alloy forgings. The present application improves the grain size qualification rate of forgings, ensures stable control of the size accuracy while reducing the residual stress of forgings, and improves the batch stability of high-end titanium alloy components.