12326 results about "Metallic materials" patented technology

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 metal material welding performance testing device and testing method, and belongs to the technical field of welding testing devices. The metal material welding performance testing device is characterized by comprising a workbench, a fixed clamp is arranged at one end of the workbench, a movable clamp is arranged at the other end of the workbench, and a loading mechanism is arranged between the fixed clamp and the movable clamp; the fixed clamp comprises a fixed seat, the movable clamp comprises a movable seat, and a power structure for driving the movable seat to slide on the supporting table is arranged on the supporting table; clamping mechanisms for clamping a workpiece are arranged on the fixed seat and the movable seat, a vibration structure for applying vibration to the workpiece is arranged in the center of the clamping mechanism on the fixed seat, and the vibration structure is located in the workpiece. By adopting the device and the method for testing the welding performance of the metal material, disclosed by the invention, the problem that an existing testing device cannot be used for testing the tensile property and the compressive property of a welded suspension arm under the condition of multi-load loading can be solved.

The invention discloses a multi-scale fatigue crack propagation prediction method and system based on a physical information neural network, and aims to improve the prediction precision of a crack propagation rate. The method comprises the following steps: S1, acquiring crack lengths and cycle cycles of a metal material under different scales by using a microscope; s2, calculating an initial small crack propagation rate based on the acquired data, performing fitting by adopting a Newman-Wu model, constructing an initial crack propagation physical model, further combining experimental data to identify physical characteristics influencing propagation behaviors, introducing a PSC-LC turning point to divide small crack and long crack stages, and constructing a crack propagation rate model fusing multiple characteristics; s3, preprocessing the expansion rate data; and S4, constructing a physical loss function in combination with a crack propagation rule in an experiment, fusing the physical loss function with data loss to form a total loss function, and training the neural network model to realize accurate prediction of the multi-scale fatigue crack propagation behavior of the metal material.

This application relates to a test device applied to a coupled environment of stress, wear, and corrosion, and a quantitative evaluation method, and belongs to the field of failure analysis of materials. The test device includes a stress-loading mechanism configured to load a stress on a sample, a corrosion mechanism configured to conduct an electrochemical corrosion test on the sample, and a wear mechanism configured to wear a sample. The test device applied to a coupled environment of stress, wear, and corrosion of this application can establish a wear-stress-corrosion coupled action test process, and can investigate service behaviors of various metallic materials and metal matrix composites under conditions close to actual service conditions to obtain key behavior data under a multi-factor coupled action, quantitatively analyze a wear, a corrosion, a wear-corrosion interaction, a stress-wear interaction.

The invention discloses a high-purity quartz sand reinforced chlorination purification method, and belongs to the technical field of inorganic non-metallic material processing. The method comprises the following steps: putting a quartz sand raw material containing crystal structure impurities into a roasting furnace, and synchronously introducing a gas chlorinating agent and a gas reducing agent into the roasting furnace for roasting to obtain purified quartz sand. According to the method, on the basis of conventional chloridizing roasting purification, a gas reducing agent is introduced to regulate and control the reaction atmosphere, efficient dissociation and chlorination of crystal structure impurities difficult to remove are promoted, and deep efficient purification of quartz sand is achieved. The method has the advantages of simple process equipment, high raw material applicability, high impurity removal efficiency and the like, and can be widely applied to production of 4N5-grade and above high-purity quartz sand.

The invention belongs to the technical field of material and coating corrosion tests, and relates to a whole sea area atmospheric environment comprehensive simulation test system, which adopts an integrated structural design, and performs integrated coupling of various environmental test simulation capabilities on the basis of a single-function test box. The device has the test capabilities of metal material corrosion acceleration test, organic composite material and coating aging evaluation and the like, can simulate the global marine atmospheric environment and coupling of multiple factors such as air temperature, humidity, salt mist and ultraviolet irradiation, can perform comprehensive test evaluation on the whole-sea-area marine atmospheric environment of typical materials, avoids the problem of inconvenient operation of corrosion tests, and has a wide application prospect. The device can be used for corrosion and ultraviolet aging tests of conventional marine atmospheric environment corrosion media, polar regions, tropical regions and other extreme marine atmospheric environments, and material corrosion tests for simulating marine splash zones, tidal range zones and the like. The device is simple in structure and convenient to operate, and coupling of multiple factors of high and low temperature, humidity, salt mist, ultraviolet illumination and periodic infiltration can be achieved.

The invention provides a parameter control method and system in the friction stir welding process, and relates to the technical field of welding equipment of metal materials. The method comprises the steps that before friction stir welding is started, working condition information of a to-be-welded workpiece is input into a welding process simulation model for virtual test welding; screening out a plurality of groups of standard process parameter combinations meeting preset welding quality requirements; in the friction stir welding process, the change trend of all the technological parameters is determined according to the real-time technological parameter combination within the first preset time period; and if it is determined that the deviation risk exists in the current welding state within the second preset time period in the future according to the change trend, the standard technological parameter combination with the maximum similarity with the real-time technological parameter combination in the standard technological parameter library is determined as the target technological parameter combination to conduct parameter control adjustment on the welding equipment. By implementing the method, the welding defects caused by sudden change of the process window can be overcome, and the stability of the welding process and the consistency of the welding seam quality are improved.

The invention belongs to the field of metal materials, and particularly relates to a high-strength hot-rolled pickled steel plate for an automobile chassis and a production method thereof. The steel plate is mainly suitable for manufacturing automobile chassis structural parts. The steel comprises the following chemical components: C, Si, Mn, Al, V, Ni, Cu, Cr, Pt and Y, P is limited to be less than or equal to 0.015%, S is limited to be less than or equal to 0.005%, N is limited to be less than or equal to 0.006%, and the balance is Fe and inevitable impurities. The yield strength of the steel plate ranges from 498 MPa to 552 MPa, the tensile strength ranges from 608 MPa to 643 MPa, the transverse elongation A ranges from 33% to 38%, the steel plate is qualified after transverse cold bending by 180 degrees D = a, the surface quality is good, oxide scale stripes and chromatic aberration defects are avoided, the surface roughness Ra ranges from 1.10 micrometers to 1.35 micrometers, and the steel plate has excellent corrosion resistance.

According to the automobile material visual defect identification method and system provided by the invention, defect risk dynamic grading is realized through a three-dimensional weight matrix, and the safety protection capability is remarkably improved according to differentiated management and control of part positions and process importance. A material self-adaptive processing mechanism is adopted, reflection interference is restrained on the metal surface, tiny defect recognition is enhanced through non-metal fusion texture and frequency domain features, and multiple automobile materials are detected and accurately recognized; deformable convolution is adopted to dynamically adapt to the curvature change of the metal plate curved surface, complex structure defect features are accurately captured, and the false alarm rate is reduced. A block chain evidence storage and generative adversarial network collaborative closed-loop quality tracing system is constructed, defect full-life-cycle tracing and model autonomous evolution are realized, and the accuracy, reliability and system adaptability of defect identification in a multi-material mixed manufacturing scene are comprehensively 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 relates to a composite supporting plate forming process, a forming mold and a composite plate shoe sole processing technic.The composite supporting plate forming process comprises the following steps that a supporting plate is placed in the forming mold, the supporting plate is made of a metal material with the density smaller than 5 g / cm < 2 >, the supporting plate is provided with hollowed-out mesh holes, the hollowed-out proportion of the supporting plate is 50%-90%, and the hollowed-out mesh holes are formed in the forming mold; a forming gap is formed between the supporting plate and the interior of a mold cavity of the forming mold. And a TPU material is injected into the mold cavity, the supporting plate is wrapped with the TPU material to form a TPU film, and the composite supporting plate is obtained. The prepared composite supporting plate can replace a carbon plate to be used in a shoe sole, and the cost is greatly reduced.

The invention belongs to the field of metal materials, and particularly relates to a 448 MPa grade hot-rolled pickled steel plate for an automobile and a production method of the 448 MPa grade hot-rolled pickled steel plate. The steel plate is mainly suitable for manufacturing automobile chassis structural parts. The steel comprises the following chemical components: C, Si, Mn, Al, Nb, Ta, Zr and Y, P is limited to be less than or equal to 0.015%, S is limited to be less than or equal to 0.005%, N is limited to be less than or equal to 0.003%, and the balance is Fe and inevitable impurities. The yield strength of the steel plate is larger than or equal to 308 MPa, the tensile strength is larger than or equal to 448 MPa, the transverse elongation A is larger than or equal to 42%, the hole expansion rate is larger than or equal to 125%, transverse cold bending is conducted by 180 degrees, D = a, the steel plate is qualified, the surface quality is good, oxide scale stripes and chromatic aberration defects are avoided, the surface roughness Ra is 1.00-1.40 micrometers, and the steel plate has good corrosion resistance.

The invention belongs to the technical field of metal material surface treatment, and provides a self-hole-sealing and self-healing aluminum alloy corrosion-resistant coating and a preparation method thereof. The aluminum alloy is subjected to micro-arc oxidation treatment in the phosphate electrolyte containing cerium ions, the self-hole-sealing and self-healing micro-arc oxidation coating is prepared on the surface of the aluminum alloy, and the technical problems that in the prior art, an aluminum alloy micro-arc oxidation coating is poor in hole sealing effect and complex in process are solved. The beneficial effects of providing long-term active corrosion protection for the aluminum alloy and simplifying the process are achieved.

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 discloses a simulation method and system based on multi-field coupling and dynamic grid processing, and belongs to the field of computational simulation, and the method comprises the steps: building and solving a coupling physical field model: carrying out finite element spatial discretization on a solving domain, building and solving a coupling partial differential equation set which at least comprises a temperature field, a displacement field and a stress field, and carrying out the finite element spatial discretization; obtaining numerical solutions of the physical fields in the current state; carrying out progressive unit removal based on a physical criterion; and finally, grid data structure updating and solver synchronization are executed. According to the method, the metal material can be gradually removed when the physical quantity reaches the critical condition, and the grid change is dynamically and robustly processed in the process.

The utility model relates to the technical field of metal material welding, in particular to a black metal smelting rolled product welding device which comprises a base, two metal pipes horizontally placed above the base and with the two ends aligned, and a welding head arranged at the upper end of the base. The first motor is driven to drive the second gear to rotate on the rack, so that the welding positions of the metal pipes abut against each other, the metal pipes with different length specifications and outer diameter specifications are extruded, fixed and welded, it is guaranteed that the welding positions of the metal pipes are kept in a stable abutting state all the time when the metal pipes are welded, and the welding quality and efficiency are improved; and meanwhile, a second electric telescopic rod drives a first electric telescopic rod to stretch out and draw back to the welding position of the metal pipe, and then the first electric telescopic rod drives a welding head to abut against the metal pipe, so that the welding head conducts comprehensive welding work on all the welding faces of the metal pipe.

The invention discloses a method for predicting corrosion resistance of a magnesium-lithium alloy based on machine learning, and belongs to the technical field of metal material design. Metal elements participating in prediction comprise Mg, Li, Al, Zn, Si, Ca, Sn, Y, Nd, Gd, Ce, Zr, La, Mn and Er, and the prediction method comprises the following steps: training model parameters by using a training set in an established database based on a machine learning algorithm; and evaluating the model by using a test set, and predicting Ecorr and icorr values of different alloys formed by elements with different contents in the magnesium-lithium alloy. According to the method, the electrochemical corrosion behavior of the alloy with different components formed by multiple different element contents of the magnesium-lithium alloy is predicted through a machine learning algorithm, so that the corrosion resistance of the alloy is effectively judged; and meanwhile, the method plays an important auxiliary role in research on the corrosion resistance of the magnesium-lithium alloy and design of the corrosion-resistant magnesium-lithium alloy in the future, and the problem that the corrosion resistance of the material is rapidly and accurately evaluated at present is effectively solved.

The invention provides a titanium plate performance analysis method and system, and relates to the technical field of metal material detection.The method comprises the steps that an optical scanner is adopted to establish a three-dimensional structure on the surface of a titanium plate, and test areas are divided; synchronously acquiring stress, hardness and conductivity data of a test point by using a multi-probe collaborative detection device; constructing a dual-branch feature extraction network, wherein the dual-branch feature extraction network comprises a surface topography feature branch and a physical feature branch; performing statistical integration on the features in the test area, calculating distribution features and determining a weight coefficient; and generating a performance analysis result through feature fusion and a multi-task output layer, and finally determining the performance grade of the titanium plate. According to the method, deep fusion of morphology information and physical characteristics is realized, and the accuracy and reliability of titanium plate performance evaluation are improved.

The invention relates to the technical field of metal material welding, and discloses a welding method for a precise heat dissipation tooth-shaped plate. The method comprises the following steps: carrying out primary welding on a precise heat dissipation tooth-shaped plate, collecting multi-source original sensing data of a welding joint, and carrying out multiple preprocessing and three-dimensional structure reconstruction and image enhancement on the welding joint; performing defect partition segmentation on the obtained three-dimensional defect fusion data, extracting various defect characteristic parameters from a welding abnormal region, performing comprehensive calculation and defect type judgment, performing heat conduction path calculation and thermal resistance value evaluation based on the obtained fine welding defect characteristic type and spatial position information, and predicting the heat dissipation performance. Generating a primary welding quality report; and according to the welding quality report and the associated database, welding process control parameters and welding optimization control are adjusted, and the heat dissipation tooth-shaped plate with the target welding quality is obtained. Accurate detection of welding defects of the heat dissipation tooth-shaped plate and closed-loop optimization of technological parameters are achieved, and the heat dissipation performance and the welding reliability are improved.

The utility model relates to a device for quickly removing residual stress of a strong compression-resistant steel plate, which belongs to the technical field of metal material processing and comprises a fixing frame, bearing plates are fixed at the left end and the right end of the upper surface of the fixing frame, and a same top plate is fixed on the upper surfaces of the bearing plates. A vibration mechanism used for applying high-frequency vibration to the steel plate is arranged on the upper surface of the top plate, a fixing mechanism used for fixing the steel plate is arranged at the bottom of the right side of the fixing frame, and a controller is arranged on the left side of the fixing frame. And the fixing mechanism comprises a driving motor, a bidirectional screw rod, two screw sleeves, two connecting plates, two telescopic columns and two linkage blocks. According to the device for rapidly removing the residual stress of the high-compression-resistance steel plate, the technical problem of rapidly and efficiently removing the residual stress of the high-compression-resistance steel plate can be solved through the arranged fixing mechanism and vibrating mechanism, and meanwhile it is guaranteed that the performance of the treated steel plate is not affected; and the accuracy and the reliability of the processing process are ensured through the arranged real-time monitoring and controlling device.

The invention discloses a metal fatigue life prediction method under laser shock peening, and relates to the technical field of metal material fatigue life prediction. The invention discloses a metal fatigue life prediction method under laser shock peening. The metal fatigue life prediction method comprises the following steps of roughness model construction, roughness evolution simulation, roughness value calculation, material attribute endowing and fatigue life prediction. According to the method, the real surface is subjected to laser shock peening, the roughness evolution condition of the metal surface subjected to laser shock peening is accurately predicted, and then the fatigue life is predicted by adopting a method of combining a Basic-Manson-Coffin formula and continuous damage mechanics. The method fully considers the local complex stress-strain state under the evolution of the roughness surface microstructure after laser shock peening, truly simulates the fatigue progressive damage process of the sample after comprehensive consideration of laser shock peening, and can effectively improve the prediction precision of the fatigue life of the metal after laser shock peening.

The invention relates to the technical field of semiconductors, in particular to a device integrated with a deep trench isolation structure and a preparation method of the device. The preparation method comprises the steps that a semiconductor structure is provided, the semiconductor structure comprises a substrate, a gate material layer stacked on the surface of the substrate and a mask layer stacked on the gate material layer, and a functional element of the semiconductor device is formed in the substrate; forming a deep trench in the semiconductor structure, wherein the deep trench penetrates through the mask layer and the gate material layer and goes deep into the substrate; the deep trench is filled to form a deep trench isolation structure, the deep trench isolation structure comprises a filling structure, the filling structure is not higher than the surface of the substrate, and the material of the filling structure is a conductive non-metal material; patterning and etching the gate material layer to form a gate structure; and removing the mask layer. According to the invention, the preparation process of the deep trench isolation structure can be integrated into the standard process for preparing the gate structure of devices such as a BCD, the integration process of deep trench isolation is simplified, and the preparation cost is reduced.

The invention belongs to the field of metal materials, and particularly relates to high-elongation and high-forming passenger car steel and a production method thereof.The steel plate is mainly suitable for manufacturing passenger car structural parts, the steel comprises the following chemical components of C, Si, Mn, Al, V, Ta, Bi, Sb, Ni, Pt and Y, P is limited to be smaller than or equal to 0.015%, S is limited to be smaller than or equal to 0.005%, N is limited to be smaller than or equal to 0.006%, and the balance Fe and inevitable impurities. The steel plate is obtained by adopting hot rolling, EPS, continuous annealing and finishing processes, the processes of pickling and cold rolling are reduced, the production process is simplified, the production cost is reduced, and the environment is not polluted.

The present application relates to a construction method for a corrosion-resistance degree-mechanical property analysis model of a metal material, and the use thereof. The construction method for the analysis model comprises the following steps: using a metal material as a test object, and acquiring corrosion test experimental data sets at different equivalent corrosion time points under corrosion test conditions and mechanical property test experimental data sets at different corrosion degrees corresponding to the different equivalent corrosion time points; and respectively establishing an empirical relational expression of corrosion parameters changing with an equivalent corrosion time and an empirical relational expression of mechanical parameters changing with the equivalent corrosion time.

The invention relates to the technical field of metal material heat treatment quality detection, in particular to a metal material rapid annealing effect detection method based on acoustic response, which comprises the following steps: step 1, acoustic excitation and synchronous acquisition; step 2, multi-physics field coupling compensation: calculating the phase compensation amount of the vibration signal based on the temperature distribution data and the acoustic characteristic temperature dependence of the material; the method comprises the following steps: acquiring an environment vibration frequency spectrum through a production line mechanical vibration monitoring device, and separating an excitation response component from an original vibration signal by adopting adaptive filtering; 3, annealing sensitive feature extraction; 4, dynamic quality mapping and control: inputting the real-time feature vector into a pre-trained machine learning model, and outputting a recrystallization proportion and a grain size; and when the output parameter exceeds the process threshold value, the control parameter adjustment of the annealing furnace is triggered. Through a non-destructive and accurate acoustic monitoring technology, the annealing effect of the metal material can be efficiently and accurately monitored in a high-speed, high-noise and strong-interference industrial environment.

The invention discloses a multi-scale strain measurement method for a metal material at an ultralow temperature, and the method combines a DIC technology and HR-EBSD analysis, and achieves the precise strain measurement from a macro scale to a micro scale. Macroscopic strain distribution on the surface of a sample is accurately captured through a DIC technology, and HR-EBSD analysis is utilized to further go deep into a microscopic level, so that a microscopic deformation mechanism of a material in an ultralow-temperature environment is disclosed. The overall strain of the material is researched from the macroscopic perspective, the specific region of interest in the macroscopic strain state is further deepened, the microscopic strain distribution of the region of interest is explored, and the deformation behavior and the mechanical property of the material at the ultralow temperature can be more comprehensively understood. Besides, a non-direct contact type heat exchange mode is adopted, so that accurate temperature control is realized, and meanwhile, the influence of water mist or condensation and the like generated by evaporation and condensation of a cooling medium on a test result is avoided.

The invention discloses a polysiloxane elastic waterproof coating and a preparation method thereof, and the polysiloxane elastic waterproof coating comprises the following raw materials: 35-60 parts of methyl polysiloxane resin, 8-12 parts of acrylic resin, 15-20 parts of a filler, 2-5 parts of a thickener, 1-3 parts of a dispersant, 1-3 parts of a coalescing agent, 1-2 parts of an antifoaming agent, 1-3 parts of a leveling agent and 10-20 parts of water. The polysiloxane elastic waterproof coating is obtained by mixing and stirring all the raw materials according to a reasonable proportion, and the polysiloxane elastic waterproof coating is obtained after the coating is dried, and the polysiloxane elastic waterproof coating provided by the invention has excellent adhesion performance, waterproof performance, tensile performance and aging resistance; the waterproof paint can be widely applied to waterproofing of metal materials and building industries.

The invention provides a high-precision modeling method of a porous metal material based on a random algorithm and application of the high-precision modeling method in electrothermal mechanical performance simulation of a material, and relates to the technical field of artificial intelligence algorithms, and the method comprises the following steps: reconstructing and optimizing an initial reconstruction model of the porous metal material based on the random algorithm to obtain a three-dimensional reconstruction model; performing slice analysis on the three-dimensional reconstruction model, and determining whether an analysis result meets a precision error standard or not; and if yes, outputting a three-dimensional reconstruction model. By reconstructing and optimizing the initial model, the three-dimensional structure of the porous material can be accurately simulated, and high-precision modeling of the porous metal material is achieved. And pore seeds are generated through a random algorithm and grow, so that the randomness and authenticity of the model are ensured. And the reliability of the model is further improved by setting the precision error standard, and the precision of the porosity and the aperture is ensured. The error problem in the porous metal material modeling process is effectively solved, and a solid foundation is provided for high-precision simulation and material performance prediction.

A machine and associated method for laser processing of a metallic material, the method comprising the steps of: (a) controlling the emission of at least one pulse of a characterizing laser beam over a predetermined region of the material in a characterizing atmosphere in order to generate a metallic vapor and / or a plasma from the material; (b) acquiring spectral data representative of an optical emission spectrum of a metal vapor or plasma, the spectral data being indicative of the material being processed; (c) identifying one of a plurality of predetermined material classes or predetermined processing parameter classes corresponding to the acquired spectral data by means of an electronic processing and automatic discrimination device configured in a supervised learning phase by training a sample set of spectral data, the training spectral data sample set indicates a predetermined material category or a predetermined material processing parameter category; and (d) selecting a current processing parameter of the material according to the identified material category or processing parameter category.

The invention discloses a metallographic detection method and system based on image recognition, and belongs to the technical field of metallographic detection. The detection method comprises the following steps: image acquisition and preprocessing: acquiring a metal metallographic image by an optical microscope, performing median filtering and denoising, and extracting a grain boundary by adaptive binarization; and field-of-view and scale calibration: selecting a corresponding scale according to the shooting magnification. The multi-parameter automatic measurement comprises grain size analysis, grain size rating, second phase analysis and intelligent report generation, a report is automatically generated based on a preset template and comprises an original image, a binary image, measurement data and a histogram, and report fonts and layout can be adjusted in real time through a visual control. According to the detection method disclosed by the invention, the efficiency, the precision and the reliability of metallographic structure analysis of the metal material are remarkably improved through the full-process design of image acquisition standardization, preprocessing intellectualization, data analysis automation and report generation templating.