117 results about "Micro defects" patented technology

The invention relates to the technical field of composite material detection, in particular to a fiber-reinforced thermosetting thermoplastic composite structure interface quality detection method and system.The method comprises the steps that vibration excitation is applied to a target area of the surface of a to-be-detected sample, and the amplitude of the excitation is lower than the damage critical value of a weak bonding interface; a dynamic response signal perpendicular to the interface is collected in a vibration field non-diffusion area of the excitation point of the target area; performing frequency domain transformation on the dynamic response signal, and separating a fundamental frequency component and at least one high-order harmonic frequency component; according to the nonlinear enhancement effect of the high-order harmonic frequency component relative to the fundamental wave frequency component, whether the weak bonding defect exists in the target area or not is judged. According to the method, the technical bottleneck that the dynamic evolution process of the weak bonding defect of the composite material interface is difficult to capture in real time is effectively solved, sensitive response to the microdefect is realized through a nonlinear harmonic characteristic enhancement effect, and the recognition precision of traditional ultrasonic detection is improved.

The invention discloses a transparent element tiny defect double-stage detection method and system. A double-stage defect detection network framework generated based on pseudo labels is designed. In the first stage, pseudo-label generation of transparent element data is carried out, an unsupervised detection method and a pseudo-label extraction strategy are adopted, and a spatial pyramid balance feature fusion-adaptive dynamic modulation convolutional network is provided in the aspect of the unsupervised detection method. The network is combined with pyramid balance feature fusion and adaptive dynamic modulation convolution, so that the feature extraction capability of an unsupervised detection network on a multi-scale target and the effectiveness and flexibility of coping with more complex data features are enhanced. In the aspect of a pseudo label extraction strategy, a pseudo label dynamic mining strategy based on fusion of threshold segmentation and RPN proposal is provided, and pseudo labels of various defects can be directly generated from an unsupervised network detection result. And the second stage is defect detection based on a pseudo label. According to the network, the performance of the supervised defect detection network is remarkably improved.

A crosslinked polyethylene cable is widely applied to a modern power grid, but in the manufacturing and laying process, certain microdefects are inevitably caused in the cable, the cable is corroded by power frequency voltage and different substances in soil during operation, and the microdefects are eroded by water to gradually induce water branch defects. Some water branches grow along the direction of the electric field force and gradually derive into electric branches under the action of overvoltage, and finally the cable insulation layer is broken down. An existing microcapsule type self-repairing material is limited by a triggering mode, is single in function and harsh in triggering condition, cannot perform self-repairing on various defects such as mechanical damage, electric tree branches, water tree branches and micropores, and only can perform single-time repairing, namely, the problems that multiple-time repairing cannot be performed, the repairing efficiency is low and the like exist. Therefore, it is necessary to develop a microcapsule / crosslinked polyethylene composite insulating material with multiple and multiple self-repairing capabilities, and a method for fundamentally exploring and prolonging the service life of the insulating material is provided.

The invention provides a defect prediction and quality control method for high-strength aluminum alloy welding based on numerical simulation. The defect prediction and quality control method comprises the steps that a welding process finite element model is established according to the actual situation; inputting accurate heat source parameters, simulating a molten pool flow field, and revealing an influence rule of metal flow in the micro molten pool on formation of micro defects through visual simulation; phase field simulation and stress distribution simulation are conducted on the solidification behavior of the molten pool, the grain structure condition of a weld zone is obtained, and crack tendencies under different processes are evaluated in combination with stress distribution; post-welding deformation of the whole component is simulated, stress deformation of a key part is obtained, and post-welding deformation is inhibited by means of reversible deformation, pre-pressing and the like. The method belongs to the field of welding numerical simulation, and can help to adjust the welding process, reduce the crack occurrence rate during welding of the high-strength aluminum alloy and inhibit post-welding deformation.

The invention relates to the technical field of coating materials, and discloses a pure titanium micro-arc oxidation coating for a vacuum cup and a preparation method thereof.The preparation method comprises the following steps that surface pretreatment is conducted, specifically, a pure titanium vacuum cup inner container workpiece is sequentially subjected to degreasing, acid pickling and ultrasonic cleaning; preparing an electrolyte, namely adding 15-25 parts by weight of a silicon-containing compound, 5-12 parts by weight of metal salt, 3-8 parts by weight of an antibacterial agent and 1-5 parts by weight of a stabilizer into deionized water, and controlling the pH value to be 8.5-10.5; and performing micro-arc oxidation treatment. According to the invention, a silane compound in the micro-arc oxidation electrolyte contains a high-activity silanol group which is subjected to condensation reaction with titanium hydroxyl on the surface of a pure titanium substrate under the action of an electric field to form stable covalent bonding, so that the bonding strength of the coating and the substrate is enhanced; metal ions generated by metal salt electrolysis are co-deposited with titanium ions through plasma discharge, a composite oxide structure is constructed, and micro defects on the surface of a titanium substrate are sealed.

The invention discloses a microdefect-containing high-temperature structure damage regulation and control method based on a dual-scale modeling method and a related device, and relates to the technical field of structural integrity evaluation and optimization of high-temperature alloy materials, and the method comprises the following steps: obtaining a plurality of alloy experiment samples subjected to standard heat treatment; the method comprises the following steps: establishing a macroscopic-microscopic dual-scale model based on an alloy experimental sample; mapping the macroscopic displacement field to a microscopic model in the macroscopic-microscopic dual-scale model, calculating a local plastic slippage cumulant, and taking a cumulative plastic slippage critical value as a fatigue failure criterion; based on the local plastic slippage cumulant and the cumulative plastic slippage critical value, defect parameter sensitivity evaluation is conducted on the alloy experiment sample, and the influence of the defect shape, the defect size and the defect position on the fatigue life is obtained; and carrying out surface gradient microstructure strengthening on the high-sensitivity area, optimizing a defect form through plastic deformation and transferring a damage accumulation position. The service life of the high-temperature structural part is remarkably prolonged.

The invention discloses a preparation method of a steel pipe, which comprises the following steps: carrying out powdering treatment and surface modification on high-purity chromium powder, nickel powder, molybdenum powder, manganese powder, silicon powder, titanium powder, niobium powder, copper powder and iron powder according to a mass ratio, and uniformly mixing to obtain alloy powder; the alloy powder is subjected to compression molding and directional local strengthening, and a blank is obtained; carrying out sintering and multi-stage heat treatment on the green body to obtain a sinter; the sinter is subjected to multi-pass drawing and upsetting treatment, and a steel pipe is formed; straightening and rounding the steel pipe and polishing the inner and outer surfaces; the microstructure and performance of the alloy are optimized, defects and impurities in the alloy are reduced, and the uniformity and compactness of the alloy are improved, so that heat is transferred more effectively; stress concentration points and microdefects are reduced by changing the lattice structure and the chemical bond type in the alloy; compared with the prior art, excessive stress concentration of part of the prepared steel pipe is reduced, the uniformity of the alloy is improved, and the stress distribution of the steel pipe is more uniform.

The invention relates to the technical field of high-end equipment, and discloses a real-time micro-defect intelligent control method and system for precision metal parts, and the method comprises the steps: obtaining historical defect detection data, and carrying out the preprocessing of the data to obtain a structured defect data set; determining a defect statistical mode through time sequence analysis and clustering analysis; generating a geometric feature set, a statistical feature set and an associated data set based on the defect statistical mode, and storing by adopting a dynamic retrieval database to form a queriable defect feature library; new defects are detected and matched with the feature library to judge types and potential positions; predicting time points and position coordinates of defects in combination with process parameters; adjusting process parameters according to a prediction result to obtain optimal configuration; optimizing and updating the defect feature library in combination with new defect information; and continuously monitoring and dynamically adjusting process parameters based on the improved feature library, and generating stable production control parameters. According to the method, real-time prediction and dynamic control of microdefects in the precise metal part production process can be achieved, and the product yield is increased.

The invention discloses a welded joint treatment method based on laser remelting and ultrasonic shot peening synergistic strengthening, and relates to the technical field of additive manufacturing. An optical fiber laser is adopted for conducting remelting treatment on the welding seam, the laser power ranges from 800 W to 1500 W, the scanning speed ranges from 0.5 m / min to 2 m / min, the light spot diameter ranges from 0.5 mm to 2 mm, microdefects are eliminated, and grains are refined; and then surface impact strengthening is conducted on the remelting area through ultrasonic shot peening equipment, the diameter of a shot ranges from 0.8 mm to 2 mm, the frequency ranges from 20 kHz to 40 kHz, the amplitude ranges from 30 micrometers to 80 micrometers, and a gradient pressure stress layer is formed. According to the method, through the alternating effect of ultra-fast laser low-heat input remelting and gradient particle size bullet impact, a nanocrystalline layer is formed on the surface layer of the material, the microhardness is improved, meanwhile, an ultra-fine grain structure is reserved in a transition area, gradient performance matching of hard outside and tough inside is achieved, and the method is particularly suitable for high-performance manufacturing of high-strength aluminum alloy (such as 7075-T6 and 2024-T3) welding components for aerospace.

The invention discloses a PCB microdefect detection method, device and system and a medium, and the method comprises the following steps: dividing a to-be-detected PCB into a plurality of to-be-detected areas according to PCB graphic characteristics, and obtaining the center coordinates of the to-be-detected areas on a to-be-detected PCB detection graph; obtaining a corresponding detection image block according to the area size of each to-be-detected region; dividing the detection image block into a plurality of to-be-detected sub-images, converting the plurality of to-be-detected sub-images into a high-dimensional matrix, inputting the high-dimensional matrix into a pre-trained defect detection model, and outputting a micro-defect classification result; according to the method, the image is acquired from the local area, so that the image resolution is higher, and the microdefect detection capability is stronger; and the detection model is used for automatically carrying out micro-defect detection on the image, so that the problem of possible missing of personnel is solved compared with manual microscope visual inspection.

The invention relates to the technical field of image data processing, in particular to an aluminum honeycomb panel core layer structure fault defect detection method which comprises the following steps: acquiring a thermal infrared image of an aluminum honeycomb panel; determining an obvious defect area in the aluminum honeycomb panel; acquiring a thermal infrared image set under each pressure value; determining a reserved position point in the aluminum honeycomb panel; determining a representative image under each pressure value; acquiring a temperature difference distribution diagram corresponding to the representative image; determining an abnormal position point in the reserved position points; acquiring a temperature increment atlas; obtaining a relatively large amplification point in the temperature amplification diagram, and determining a relatively large area in the temperature amplification diagram; acquiring a convex hull region corresponding to the larger-amplitude region, and determining the larger-amplitude region reserved in the temperature increase amplitude graph; and determining a tiny defect area in the aluminum honeycomb panel. By applying pressure to the aluminum honeycomb panel step by step and monitoring the change of the thermal infrared image in real time, the detection effect on the tiny defects of the aluminum honeycomb panel can be improved.

The invention is suitable for the technical field of milling cutter machining, and provides a hard alloy milling cutter cutting edge passivation process which comprises the following steps that a passivation solution containing Fe < 3 + > and Zn < 2 + > is prepared, and the passivation solution comprises abrasive particles and a nanometer reinforcing phase; the tool is immersed in a passivation solution to be subjected to chemical-mechanical composite treatment; the cutting edge is subjected to plasma impact treatment; a cutting edge grain boundary is reconstructed through laser irradiation, and atomic-scale reconstruction of the hard alloy cutting edge and multi-scale optimization of structure strengthening are achieved through combination of a chemical-mechanical-energy field composite effect, a metal ion passivation reaction and plasma / laser modification and cooperation of metal ion selective passivation, grain boundary engineering regulation and control and nanometer enhancement. On the basis of chemical passivation, the mechanical performance of the cutting edge of the milling cutter is improved through a composite passivation film generated through Fe < 3 + > / Zn < 2 + > reaction, plasma impact and laser reconstruction are coupled through an energy field, the problems of microdefects and grain boundary weakening are solved respectively, and the strength of the cutting edge is further improved through the synergistic effect of the three.

The invention discloses a method for detecting tiny defects of a high-density integrated circuit packaging substrate. The method comprises the following steps: acquiring image data of the surface of the high-density integrated circuit packaging substrate; processing the acquired images in sequence by adopting a mean filtering method, morphological dilation and a texture operator; processing the image by adopting an image binarization processing technology to obtain a binarized image; dividing the binary image into a plurality of energy regions, and calculating an entropy difference through the divided energy regions; performing processing operation on the image data through a discrete cosine transform technology to obtain a DCT coefficient, dividing the DCT coefficient into a high-frequency component and a low-frequency component, and performing calculation to obtain a ratio of a low-frequency coefficient mean value to a high-frequency coefficient mean value; the feature extraction model extracts defect shape features based on the entropy difference and the ratio; comparing a similarity measurement index calculated according to the defect shape characteristics of the packaging substrate with a preset threshold value, and judging whether the packaging substrate has a shape defect or not; and precise detection of small defects of the high-density integrated circuit packaging substrate is realized.

The invention discloses a preparation method of a MgO-MgA12O4-ZrO2 nano ceramic eutectic composite material. The preparation method comprises the following steps: S1, preparing powder; s2, flash firing preparation; and S3, high-temperature melting preparation. According to the invention, two technologies of flash sintering and high-temperature melting are combined, the problems of high sintering temperature, easy growth of crystal grains, difficult densification and the like of the traditional eutectic ceramic are solved, and an excellent composite material with a nanoscale eutectic structure is finally obtained; a nanocrystalline blank obtained through flash sintering is crushed and then subjected to high-temperature melting, microdefects and air holes possibly existing in the flash sintering blank are eliminated, the chemical components and the microstructure of a final product are more uniform, and compared with traditional selective laser melting, the method is more convenient and faster to implement and lower in cost.

The invention belongs to the technical field of PCB detection, particularly relates to a PCB ceramic substrate appearance laser measuring instrument, and aims to solve the problem that tiny cracks hidden on a substrate are difficult to find when the substrate is not stressed in the actual detection process, the following scheme is provided: the PCB ceramic substrate appearance laser measuring instrument comprises a counterweight seat, support rods are fixed on the upper surface of the counterweight seat close to four corners, and the support rods are fixed on the upper surface of the counterweight seat; the top ends of the four supporting rods are fixedly provided with the same workbench, the middle of the workbench is rotationally connected with a vertical supporting pipe, the top end of the supporting pipe is fixedly provided with an arch-shaped supporting plate, and the two ends of the arch-shaped supporting plate are provided with bearing modules which are of the same structure and are symmetrical to each other respectively. According to the invention, the ceramic plate body can be extruded before surface defect detection, so that the residual stress of the ceramic plate body can be amplified to a certain extent, some potential surface micro-defects are forced to be amplified, a laser probe can find the surface micro-defects more easily, and potential quality defects of the ceramic plate body can be detected.

The invention relates to the technical field of processing, testing or inspection of aircraft parts, and provides an accelerated test method for aging of an aluminum alloy aircraft plate. The method comprises the following steps: carrying out a cyclic alternating test of ultraviolet irradiation and solution soaking on an aluminum alloy sample with an epoxy coating, and simulating a multi-factor coupling aging process in an aviation service environment. And regularly observing and recording micro-defects such as micropores, cracks and spalling on the surface of the coating in a test period, and evaluating the development of the micro-defects of the coating through qualitative and quantitative analysis. And after the test is finished, measuring the residual thickness of the sample, and establishing a relation model between the coating thickness degradation and the change of microdefect development along with the aging time in combination with the microdefect development state. According to the method, the actual aviation service environment can be simulated, the ultraviolet aging and corrosion coupling effect is considered, and accurate prediction and accelerated simulation of the aging behavior of the aluminum alloy aircraft plate with the epoxy coating are achieved.

The invention provides a method for repairing the surface of a hammer head of a precision forging machine through laser cladding of iron-based composite powder. The method comprises the following steps: firstly, performing flaw detection treatment on a hammer head with a damaged surface to determine a to-be-repaired hammer head, correcting the to-be-repaired hammer head, and then cleaning and drying; and then, preset laser cladding powder and the optimal repairing parameter range are selected to conduct laser cladding on the hammer head, finish machining is conducted on the hammer head subjected to laser cladding, and the repaired hammer head is obtained. According to the method, the structural design of an original hammerhead can be kept unchanged, the iron-based high-temperature alloy repairing layer is cladded on the surface of the hammerhead of the precision forging machine, the coating effect that the structure is compact, microdefects are few, and the metallurgical bonding strength of the cladding layer and the base material is high is obtained, surface repairing can be conducted on the damaged faces such as abrasion, deformation and pitting corrosion of the hammerhead, and the service life of the hammerhead is prolonged. And compared with the original hammerhead, the repaired hammerhead has the advantages that the wear resistance, the impact resistance and the like are obviously improved, the production cost and the time cost of an enterprise are reduced, and the production efficiency is effectively improved.

The invention belongs to the technical field of gallium oxide crystals, and particularly relates to a gallium oxide crystal electrical property improving method based on microdefect analysis, which comprises the following specific steps: step 1, sample preparation: firstly, selecting or preparing a gallium oxide crystal sample to be analyzed, and ensuring that the surface of the sample is clean, flat and free of obvious macroscopic defects; according to the method, various defect types and distribution thereof in the gallium oxide crystal can be accurately identified and quantified through detailed microdefect analysis. Based on the analysis results, follow-up treatment schemes (such as annealing, doping, polishing, corrosion, ultraviolet irradiation and the like) are specifically formulated and implemented, and defects such as dislocation, lattice distortion, surface roughness and the like which are unfavorable for electrical properties can be effectively reduced or eliminated. The electrical performance indexes such as the electrical resistivity, the carrier concentration and the mobility of the gallium oxide crystal are remarkably improved through the treatment measures, and a reliable material basis is provided for preparing a high-performance gallium oxide-based electronic device.

The invention discloses a flexible circuit board defect detection method and device, a medium and equipment, and relates to the technical field of defect detection. In order to solve the problem of inaccurate detection of small defects of a flexible circuit board, an attention mechanism module is added to the output end of a backbone network SPPF module in an original YOLOv8 network, and a convolution module of a c2f module connected with a minimum-size detection head in a neck network is replaced with a deformable convolution module. Therefore, the detection accuracy of the tiny defects of the flexible circuit board is improved. The attention mechanism enhances semantic information related to defects and transmits accurate and prominent defect semantic information to the neck network; the neck network carries out fusion based on the enhanced defect semantic information so as to transmit more comprehensive scale information of the tiny defects to the head network; the deformable convolution module assists the anchor frame generated by the minimum-size detection head to be matched with the position and the scale of the tiny defect more accurately, and a more accurate detection result is obtained.

The invention discloses an aluminum profile surface defect detection method and a storage medium, and the method comprises the following steps: S1, image preprocessing and data set construction; s2, improving the design of a YOLOv8 network structure; s3, model training and deployment; the image quality is optimized through wavelet transform denoising and histogram equalization, and the feature identification degree of the tiny defects is enhanced; a C2fFaster DCNv3 module and an ADFR module are adopted to enhance the multi-scale feature extraction and fusion capability; the newly added P2 layer detection head is specially adapted to tiny defects; the focus degree of a difficult sample is increased through weighting of a Focaler-IoU loss function, and the problems of missing detection and false detection of tiny defects are effectively solved; the Faster Block branch reduces the calculated amount, the TensorRT reasoning accelerates and optimizes the deployment efficiency, the real-time detection requirement of industrial production is met on the premise that the detection precision is guaranteed, and the dual purposes of high precision and high speed are achieved.

The present invention provides an image detection method and system for detecting minute defects and defective parts. In the object image recognition step, an object image is input into an image recognition model and a recognition result is output. When the recognition result is the first image, it is determined that the recognition result does not conform to the object image. When the recognition result is the second image, the following steps are executed. In the first feature extraction step, object feature values are extracted. In the second feature extraction step, a calibration image is input into the image recognition model and calibration feature values are extracted. In the feature comparison step, the object feature values are compared based on the calibration feature values to generate a similarity probability. In the recognition result judgment step, it is judged whether the recognition result conforms to the object image based on a threshold value. When the similarity probability is greater than or equal to the threshold value, it is determined that the recognition result conforms to the object image. Thereby, the accuracy rate of the recognition result is improved.

The invention relates to the field of precision optical detection, and discloses a device and a method for automatically identifying microcracks on the surface of quartz glass based on machine vision, and the device comprises a multi-dimensional image sensing module, a main control module and an AI identification module. The method utilizes a polarized light orthogonal imaging principle to adjust a polarization angle to be orthogonal with an inspection angle so as to suppress specular reflection interference on the surface of the quartz glass. An acquired image is enhanced by adaptive Gaussian filtering and then is input into an improved U-Net model integrated with a fine crack attention mechanism, and the mechanism combines channel and space attention to accurately capture micro crack features while suppressing noise. The system performs fitting on a crack skeleton based on a least square method so as to calculate geometric parameters, and intelligent retrieval and clustering of defects are realized by using cosine similarity and a K-means algorithm. The method effectively solves the problem that the surface microdefect of the transparent high-reflective material is difficult to detect, the detection precision and the automation level are remarkably improved, and the method is suitable for quality control of precise optical elements.

The invention belongs to the technical field of three-post insulator detection, and particularly relates to a three-post insulator microdefect detection device under a temperature and pressure stress field and an identification method thereof, and the three-post insulator microdefect detection device comprises a three-post insulator, an ultrasonic detection unit and a detection unit; wherein the three-post insulator is embedded in the gas-insulated metal-enclosed power transmission line, the ultrasonic detection unit comprises an ultrasonic transmitting probe and an ultrasonic receiving probe, and the detection unit comprises a temperature detection unit and a pressure detection unit on the inner side of the grounding shell; insulating gas with preset pressure intensity is filled in the gas insulated metal-enclosed power transmission line, a high-voltage guide rod in the gas insulated metal-enclosed power transmission line is heated and stretched based on high-voltage direct current, and an ultrasonic guided wave signal with three-post insulator state information is obtained based on an ultrasonic detection unit. The pressure and the temperature obtained by the detection unit are obtained in real time, whether the three-post insulator has micro-defects or not is judged by considering a temperature, pressure and stress scene, and detection of the micro-defects of the three-post insulator in the temperature and pressure stress field is completed.

A structural component made of a steel plate, the structural component having a flat plate portion 10a and a bent portion 10b, the bent portion 10b satisfying the following formulas (1), (2) and (3). 28≦√area≦45 (1) 0.17≦r / t≦6.90 (2) 0.22≦n' (3) however, √area is the square root of the projected area of ​​the micro defect on the inside of the bent part 10b [μm] r is the minimum value of the inner curvature radius of the bend 10b [mm] t is the thickness of the flat plate portion 10a [mm] n' is the interquartile range of the nano hardness of the flat plate portion 10a / mean nano hardness It is.

The invention relates to a novel small-sized receiving coil group electromagnetic ultrasonic sensor and a method for high-resolution detection of submillimeter-level tiny defects. The sensor comprises a permanent magnet, an exciting coil and a receiving coil group, the receiving coil group comprises at least two independent preset small coils; the receiving coil group is arranged above the effective receiving area of the exciting coil; the permanent magnet is placed above the effective receiving area of the receiving coil assembly, and the magnetic pole direction is perpendicular to the plane of the receiving coil assembly. The invention aims to solve the technical problems that an existing electromagnetic ultrasonic sensor is low in signal-to-noise ratio, depends on complex signal processing and is difficult to give consideration to high-resolution and high-reliability detection when detecting submillimeter-level tiny defects, and provides a small-sized receiving coil group electromagnetic ultrasonic sensor which is compact in structure and high in signal-to-noise ratio and a detection method. Under the condition of not depending on complex post-processing, high-resolution recognition of submillimeter-level tiny defects in the metal material can be achieved.

The application discloses an industrial product micro defect visual detection system and method, belongs to the product detection technical field, obtains the multi-source image data of the target industrial product under multiple detection angles and illumination conditions, and establishes an image information matrix; the image is subjected to region segmentation and texture enhancement, and a local texture direction inconsistency degree parameter is extracted; the pixel ratio is normalized and analyzed under different spectral channels, and a multispectral reflectance anomaly index is calculated; a deep convolution recognition model is constructed; the model is used for reasoning on the image, and a defect judgment result and a confidence score are output; whether it is a defect area is determined based on a dynamic threshold mechanism, and a detection report containing defect position information and a visualized heat map is output; the application realizes multi-dimensional fusion recognition of texture structure disturbance and spectral response anomaly, effectively improves micro defect recognition precision, has high robustness, automation and engineering practicability, and is suitable for high-precision quality control requirements in various industrial scenes.

The invention relates to the technical field of finishing grinding devices, in particular to a device and method for passivating microdefects of a cutting edge before cutter coating. The grinding device comprises a sand basin fixedly arranged at the top of a base, sand grains used for grinding the twist drill-shaped cutter are contained in the sand basin, a plurality of gathering assemblies used for gathering the sand grains are arranged in the sand basin, and each gathering assembly comprises a gathering cover capable of rotating; when the multiple driving columns rotate along with the gathering cover, the driving columns drive the lifting cap at the top of the main rod to ascend, the lifted lifting cap drives complete sand grains to get close to the bottom of a tool to be polished, meanwhile, the angular velocity difference between the static lifting cap and the rotating gathering cover disturbs gravel, and complete gravel and fine powder gravel are separated; the gap between the lifting cap and the side wall of the gathering cover always keeps discharging the fine powdery gravels, but the diameter of the gap is smaller than that of the gravels, so that the complete gravels are prevented from falling off.

The invention discloses an industrial aluminum material forming device and a forming method thereof, and belongs to the technical field of aluminum material extrusion forming. The device comprises a forming machine body, two side plates are fixedly connected to the top of the forming machine body, connecting plates are arranged at the tops of the two side plates, a pre-impurity-removing mechanism is jointly arranged between the two connecting plates, and an extrusion assembly, a forming assembly, a shearing assembly and a temperature control assembly are fixedly installed at the top of the forming machine body; when the extrusion assembly pushes the aluminum bar to penetrate through the mounting ring, the servo motor drives the gear to rotate, and the annular gear ring drives the mounting base and the first grinding brush to rotate in the circumferential direction through meshing. The mounting seat drives the first grinding brush to radially move under the action of the inclined surface of the guide plate and is always attached to the surface of the aluminum bar by matching with the synchronous adaptation mechanism. Under rotation and self-adaptive pressing, the first grinding brush evenly grinds the outer wall of the aluminum bar, oxide skin, oil stains and microdefects are effectively removed, a clean metal surface is obtained, and a high-quality blank is provided for follow-up extrusion forming.

The present application relates to a kind of electrochromic film defect analysis method and device, equipment, medium, it is related to electrochromic field, including: sample is carried out in darkroom and is marked defect by fading observation, obtain marked sample;The defect in the obtained marked sample is observed using optical microscope and determines defect category, obtain marked sample;The defect of marked sample is profiled, microanalysis, component analysis, obtains defect profile parameter, defect microtopography, defect component;The nature of defect is judged based on at least one of defect profile parameter, defect microtopography and defect component.The defect analysis method provided in the present application, by optimizing the defect analysis process for photochromic film, realize system, efficiently, accurately to the surface of electrochromic film Complex and varied macro, micro defect (such as scratch, halo point, pinhole-like white spot, white spot, blue dot, abnormal shape and color point etc.) Positioning, identification, characterization and root cause analysis.

The present application relates to the technical field of industrial vision detection, and discloses a hydraulic side plate surface micro defect identification method and system, the method comprising collecting a double light source image sequence, performing pixel level gray difference extraction, purifying defect feature maps, performing multi-scale Gaussian Laplace convolution and morphological screening to construct defect feature partial order lattices, calculating gray and spatial reference offset vectors to generate a composite drift correction operator to perform adaptive correction on the feature maps, inputting a convolutional neural network to determine the defect category and trigger a sorting instruction; the present application separates oil film artifacts by using optical response difference and quantifies imaging drift by combining partial order lattice structure, solves the problem of recognition precision decay caused by cutting fluid reflection interference, long-term operation light decay and micro vibration of the equipment, and realizes high-precision detection of micro defects under production line conditions without calibration.