2891 results about "Fiber bundle" patented technology

The invention discloses a brain disease classification method and system. Precise diagnosis is realized through multi-modal data fusion and dynamic modeling. The method comprises the following steps: collecting multi-modal brain image information and cognitive behavior information of a user; performing dynamic function connection analysis on the resting state functional magnetic resonance time sequence signal to obtain a time-varying brain network feature matrix, and performing white matter fiber bundle topology reconstruction on a structure connection matrix; constructing a four-dimensional correlation tensor by using the time-varying network features, the structural connection weights and the anatomical features through a neurodynamic model; performing multi-task learning on the four-dimensional correlation tensor based on a time-varying graph neural network model, and outputting a quantitative diagnosis result; and finally generating a clinical classification report integrating the individualized brain network remodeling target, the disease progress risk layering and the treatment response prediction. By dynamically fusing the structure and functional features, comprehensive characterization of the pathological mechanism of the brain disease is realized, and decision support with both accuracy and interpretation is provided for clinical diagnosis.

The invention relates to a method for establishing and optimizing a multi-scale prediction model for constitutive parameters of a fiber reinforced composite material. Comprising the following steps: constructing a fiber-matrix microscopic RVE model, applying a boundary condition and a load, determining a failure criterion, and calculating equivalent mechanical parameters of a fiber bundle; a fiber bundle-matrix mesoscopic RVE model is generated, fiber bundle equivalent mechanical parameters serve as material attributes of fiber bundles in the mesoscopic RVE, a viscoelastic model is adopted for a matrix, and fiber reinforced material unit cell equivalent mechanical parameters are calculated; constructing a macroscopic fiber reinforced composite material finite element model, endowing a macroscopic model with unit cell equivalent mechanical parameters, defining an orthotropic material card, simulating an explosion impact process by adopting an explicit dynamics algorithm, outputting structural displacement, a damage area and stress distribution, and comparing calculation and test data. And correcting the microscopic RVE model and the mesoscopic RVE model through reverse optimization iteration to obtain a final macroscopic prediction model. The explosion-proof performance of the fiber composite structure is remarkably improved.

The invention provides a cracking equipment data processing method combined with digital twinning, which comprises the following steps: acquiring initial state data and environmental data of a carbon fiber composite material in a cracking furnace, and performing time synchronization processing to obtain a time consistency data set; extracting pyrolysis characteristic parameters of interaction between the carbon fiber bundle and the matrix from the spatial registration data set, and calculating a reaction rate and pyrolysis behavior change of a microscopic scale of a fiber matrix interface to obtain a pyrolysis characteristic parameter set; if a deviation exists between the prediction result and a preset target carbon powder quality index, determining a heating power distribution adjustment amount and a change trend of an air inlet valve opening degree based on a deviation degree, and obtaining a control parameter adjustment set of the cracking furnace; and carrying out constraint and smoothing processing on the control parameter adjustment set to obtain a control set value, formatting the control set value into a closed-loop feedback instruction, and updating the closed-loop feedback instruction to a cracking furnace control system to obtain adjusted pyrolysis operation state data.

The invention provides a recycled carbon fiber quality detection method based on machine vision, and the method comprises the steps: obtaining a surface image of a carbon fiber bundle through a machine vision method, and carrying out the preprocessing of the image, including image denoising and enhancement; for the preprocessed surface image of the carbon fiber bundle, extracting the morphological characteristics of the fiber bundle, including fiber bundle surface texture and fiber orientation distribution, for representing the morphological change of the fiber bundle under the reciprocating bending stress; acquiring a scattered light intensity distribution image on the surface of the carbon fiber bundle, and extracting spatial distribution characteristics of scattered light intensity through an image segmentation method, including uniformity and continuity of scattered light intensity distribution; if the fracture risk exists, positioning the identified high-risk area, and collecting image data of the high-risk area; according to the high-risk area image data, scattered light intensity distribution characteristics are extracted, a quantitative relation between scattered light intensity space distribution and the fiber bundle fracture risk is established, and a quantitative index for evaluating the fiber bundle fracture risk is obtained.

The invention relates to the technical field of text feature fusion, in particular to an adaptive text guide fiber bundle feature fusion method and system based on a large language model. The method comprises the steps of performing multi-scale potential attention fusion based on features after fiber bundle feature fusion, including potential multi-scale feature embedding, inter-scale attention modeling, multi-scale fusion and residual enhancement, and attention regularization and scale consistency constraint; performing pseudo token sequence generation and aggregation based on features after multi-scale potential attention fusion, including pseudo token embedding representation, token serialization and slice mapping, semantic consistency and context modeling, and sequence aggregation and decodable interface generation; and processing the multi-modal fusion features subjected to pseudo token sequence generation and aggregation by using a large language model to generate natural language output. The invention provides an adaptive text-guided fiber bundle feature fusion method based on a large language model, which realizes efficient collaboration and semantic interpretable fusion of multi-modal information.

The invention discloses an electrocorrosion protection device for a motor bearing and a motor comprising the electrocorrosion protection device, and the electrocorrosion protection device comprises an annular or fan-annular PCB substrate which is divided into a radial inner edge region, a radial outer edge region and a middle region between the radial inner edge region and the radial outer edge region; conductive fiber bundles are fixed in the tubular conductive components; a plurality of substrate conductive contacts located in the radial outer edge area and configured to be electrically connected to a housing or a ground terminal of the motor; the substrate conduction circuit is arranged on the surface of the first main body and allows the voltage at the exposed end of the conductive fiber bundle to be released to a shell or a grounding end of the motor through the substrate conduction circuit and the substrate conductive contact; the specific function component is arranged in the middle area or in the gap area between the tubular conductive components in the radial inner edge area. According to the invention, the requirements of miniaturization design of the servo motor, operation monitoring of the servo motor, bearing protection and the like can be met.

The invention relates to a method and a machine for producing a fibrous web, preferably a tissue, paper or cardboard web or a nonwoven web, with a low-water raw material preparation of cellulose-containing fibers, preferably virgin pulp as bales and / or recycled fibers, into individual fibers and / or fiber bundles; wherein the individual fibers and / or fiber bundles are formed and solidified in an air stream into a planar fiber layup on a, preferably permeable, forming belt by a dry forming process; and wherein a fluid, preferably water and / or a water-additive mixture, is applied to the, preferably planar, fiber layup and the fibrous web is dried. The invention is characterized in that the total amount of fluid applied is distributed over at least two application steps.

The invention discloses a preparation method of an ultra-thin high-density fiberboard with ultra-low formaldehyde emission, which is characterized by comprising the following steps: peeling wood by using a peeling machine, chipping to obtain wood chips, washing the wood chips with water, cooking in a cooking cylinder, feeding into a defibrator, and adding molten paraffin for treatment to obtain fibers; meanwhile, formaldehyde is taken to be mixed with sodium bentonite, triethylene diamine and polyvinyl alcohol, then urea is added in five times, melamine is added in two times, a reaction is conducted, and melamine modified urea-formaldehyde resin is prepared; taking fibers, applying an adhesive formed by mixing melamine modified urea-formaldehyde resin, nano titanium dioxide and an ammonium chloride curing agent, drying and dehydrating the fibers uniformly mixed with the adhesive, sorting to remove micelles, fiber agglomerates and fiber bundles, and paving and forming to obtain a plate blank; and the plate blank is taken to be subjected to the hot pressing procedure to obtain a plate, and after the plate is cooled, the ultra-thin high-density fiberboard with the advantages of being high in strength, low in formaldehyde emission and the like is obtained after sanding.

The invention discloses a preparation method of a natural fiber prepreg with an improved impregnation effect, and relates to the technical field of composite material preparation, the method comprises the following steps: carrying out synergistic modification through fiber surface plasma activation and silane grafting, and combining a gradient pressure-temperature coupling impregnation system and ultrasonic-assisted permeation to prepare the natural fiber prepreg with the improved impregnation effect. And gradient filling and interface chemical bonding strengthening of the resin in the fiber bundle are realized. The core process comprises the following steps: pretreating fibers to improve surface energy and roughness, introducing a reactive diluent and a block copolymer into a resin system to regulate and control viscosity and transport capacity, constructing a pressure gradient by a multi-stage compression roller to drive resin to permeate into a bundle core, promoting uniform impregnation by infrared temperature control and ultrasonic cavitation, and finally obtaining uniform resin distribution and porosity lt. The interlayer shear strength is gt; and the high-performance prepreg is stable in batch under the pressure of 45 MPa. Reliable technical support and process guarantee are provided for large-scale engineering application of the high-performance natural fiber composite material.

The present invention relates to the technical field of composite materials and forming thereof, and specifically relates to an efficient and green method for preparing a polyether ether ketone composite material reinforced by nano-modified polyether arone sized fiber cloth. The method comprises: first, preparing a nano-modified polyether arone water-based sizing agent; sizing fiber cloth by using the sizing agent; and finally, preparing a polyether ether ketone composite material reinforced by the nano-modified polyether arone sized fiber cloth by means of a slurry method. The sizing agent is free of decomposition and failure with heat in a high-temperature forming process of the composite material; moreover, a polyether arone component in the sizing agent is similar to polyether ether ketone in structure and has good compatibility with same; anchor points with a mechanical locking effect are provided by means of the introduction of nanoparticles, such that fibers and a resin are connected together by means of the mechanical locking effect; in addition, a polyether ether ketone powder is dispersed into a cosolvent / water mixed solvent and then brushed onto the fiber cloth, and polyether ether ketone more easily infiltrates fiber bundles by means of a solution, such that an infiltration path of the melt resin is shortened, and the interface performance of the composite material is also improved to a certain extent.

The invention relates to the technical field of cables, and discloses an anti-torsional fatigue and corrosion-resistant wind power cable and a manufacturing process thereof, the anti-torsional fatigue and corrosion-resistant wind power cable comprises a three-phase cable core main body, a dynamic compensation anti-torsion layer, a multifunctional corrosion-resistant barrier layer and an outer sheath, the three-phase cable core main body comprises a stranded conductor, a filling inner layer and an insulating layer; the dynamic compensation anti-torsion layer comprises an incongruous spiral supporting layer and a shape memory alloy compensation layer, and the incongruous spiral supporting layer comprises aramid fiber bundles and a nickel-cobalt alloy wire woven mesh; the multifunctional anti-corrosion barrier layer is arranged on the outer side of the dynamic compensation anti-torsion layer and sequentially comprises an anti-corrosion barrier bottom layer, an anti-corrosion barrier middle layer and an anti-corrosion barrier bottom layer surface layer from inside to outside. Through the gradient composite structure design, the problem of failure of a traditional wind power cable under long-term dynamic load and severe environment is effectively solved, and the torsional fatigue resistance, the corrosion resistance and the environmental adaptability are remarkably improved.

The invention discloses a white matter fiber bundle structure-function connection coupling method based on a distance function. The method comprises the steps that brain imaging data are collected and preprocessed; extracting white matter fiber bundle structure attributes and function signals of the preprocessed brain imaging data; constructing a structure connection matrix and an individualized function connection matrix according to the white matter fiber bundle structure attributes and the function signals; measuring the connection weight similarity between corresponding columns of the structure connection matrix and the function connection matrix through a distance function, and carrying out white matter fiber bundle structure-function connection coupling according to the connection weight similarity; through the method, the relationship of the white matter fiber bundle structure and function of the brain can be quantified, and the method is suitable for brain structure and function analysis based on the white matter fiber bundle and research on brain development and mental diseases.

The invention discloses a unidirectional graphene fiber carbon / carbon composite material as well as a preparation method and application thereof, and belongs to the technical field of carbon / carbon composite materials. The preparation method comprises the following steps: adding phenolic resin powder into absolute ethyl alcohol to prepare a phenolic resin dipping solution; adding the graphene fiber bundle into a phenolic resin impregnation solution for impregnation under the conditions of normal temperature and normal pressure to prepare a pre-impregnated graphene fiber bundle; carrying out stepped heating curing on the pre-impregnated graphene fiber bundle, and then carrying out carbonization to prepare a pre-treated graphene fiber bundle; the pretreated graphene fiber bundles are arranged in parallel and stacked in the thickness direction, pressure is applied for fastening, and a one-way prefabricated body is obtained; and carrying out heat treatment on the unidirectional preform, densifying by adopting an isothermal chemical vapor infiltration process, and then carrying out graphitization treatment to obtain the unidirectional graphene fiber carbon / carbon composite material. The graphene fiber is pretreated to fill pores of the graphene fiber, so that the densification efficiency of the graphene fiber preform is improved, and finally, the heat conduction and mechanical properties of the composite material are enhanced.

The invention belongs to the technical field of carbon material fibers, and discloses a preparation method of a carbon nanofiber reinforced carbon material fiber fabric, which comprises the following steps: fixing a weakly twisted carbon material fiber tow on an electrostatic spinning nano yarn machine; forming a carbon nanofiber membrane by utilizing electrostatic spinning, uniformly wrapping the carbon nanofiber membrane on a carbon material fiber bundle subjected to weak twisting, then rolling into a shaft, then weaving the rolled fibers into a fabric, and sequentially performing hot pressing and carbonization treatment on the fabric to prepare a carbon nanofiber reinforced carbon material fiber fabric; the weak twisting means that the twisting degree is 5-13 twists per meter. According to the invention, the carbon nanofiber is coated on the carbon material fiber, so that the interface bonding strength between the nanofiber and the carbon material fiber is improved, and then the fabric prepared from the carbon nanofiber is subjected to hot pressing and carbonization treatment, so that the mechanical property, the electrical conductivity and the heat-conducting property of the fabric are further improved; therefore, the composite material has a huge application prospect in the fields of high-performance composite materials, intelligent textiles and the like.

The invention discloses an intelligent detection system and method for the fracture specific strength of cotton fibers, and relates to the technical field of cotton fiber detection, and the intelligent detection system for the fracture specific strength of the cotton fibers comprises a sampling module, an image acquisition module, a resistance measurement module, a strength measurement module and a central control module. The sampling module is used for sampling on a cotton fiber sample and constructing the sample into a to-be-detected cotton fiber bundle; the image acquisition module is used for acquiring image information of a to-be-detected cotton fiber bundle; the resistance measurement module is used for measuring resistance information of the to-be-detected cotton fiber bundle; the strength measurement module is used for snapping the to-be-detected cotton fiber bundle from a fracture area of the to-be-detected cotton fiber bundle and recording real-time tension information and displacement information of the fracture area; the central control module is in communication connection with the image acquisition module, the resistance measurement module and the strength measurement module. According to the invention, the detection of the cotton fiber fracture specific strength in a non-standard laboratory environment can be realized.

The invention discloses a vacuum-assisted pultrusion preforming device for a composite material. The vacuum-assisted pultrusion preforming device comprises a yarn threading plate, a gum dipping tank, a gum extruding roller and a vacuum-assisted preforming mold which are sequentially arranged in the pultrusion direction, wherein fiber bundles penetrate through the yarn threading plate in a layered mode, the gum dipping tank is used for containing resin, and the gum extruding roller is used for extruding redundant resin. The vacuum auxiliary preforming mold is provided with a preforming mold cavity, a vacuum cavity is formed in one section of the preforming mold cavity of the vacuum auxiliary preforming mold, an air exhaust hole is formed in the upper portion of the vacuum cavity, and a semi-permeable membrane allowing gas to pass through but blocking resin to pass through is arranged at the air exhaust hole. And the air exhaust hole is externally connected with a vacuumizing device. The vacuum-assisted pultrusion preforming device can effectively discharge microbubbles in resin and fiber bundles, effectively control uniform distribution of the content of the resin and remarkably promote full infiltration of high-viscosity resin to fibers.

The invention discloses a structural XCT fiber bundle identification and segmentation method based on improved U-Net, which is used for identifying fiber bundles in XCT slices of a woven CMC structural member, and the network is applied to the CMC field for the first time. According to the method, the down-sampling operation of the original U-Net network is greatly modified, the characteristic extraction capability of the model on the fiber bundle is improved, the parameter quantity of the model is reduced, and the network model can be trained more stably, so that the efficiency of segmenting and identifying the fiber bundle by the model is improved. Wherein an Inception structure is adopted, so that the visual field of the model is widened, and the recognition and segmentation capability of the model on fiber bundles with different sizes and boundaries thereof in CT is enhanced. And residual connection is added in an original model by adopting a ResNet structure, so that gradient propagation in training is ensured, the depth of the improved U-Net is deepened, and the accuracy of segmentation recognition is improved. And the bottleneck structure is adopted, so that the parameter quantity of the whole model is greatly reduced, the training time is shortened, and the recognition and segmentation speed is increased.

In one embodiment, a local convergence point terminal includes a shell including a cavity, an input connection port including a port opening, a plurality of output connection ports including a port opening extending from the outer surface of the shell into the cavity, an input cable including a first fiber bundle having a plurality of input optical fibers, where the input cable is at least partially disposed within the input connection port, and a plurality of splitter assemblies within the cavity, each splitter assembly including an optical splitter, a splitter input optical fiber and a plurality of splitter output optical fibers, where a number of splitter optical fibers for each splitter assembly is a multiple of a number of input optical fibers of the input cable such that each plurality of splitter output optical fibers is routed to an individual output connection port.

The invention relates to the field of thermal fault early warning of machine room inspection robots, in particular to a multi-modal sensing thermal fault early warning method of a machine room inspection robot, which comprises the following steps: acquiring infrared thermal image, acoustics, vibration and gas concentration data through a multi-modal sensor array, and generating voxelization temperature distribution; according to the method, temperature features are extracted through wavelet transform and a fractional Brownian motion algorithm and are fused into an equipment global temperature feature set; constructing noise, vibration and gas concentration tower extraction auxiliary features, and combining non-extensive entropy and a graph attention model to be fused into a high-dimensional fault feature pool; building a fiber bundle model by taking the machine room topology as a base space, and locating a thermal fault after optimizing parameters by a simulated annealing algorithm; and finally, a dynamic thermodynamic diagram and the like are generated through digital twinning, so that accurate early warning is realized.

The invention discloses a preparation method of a continuous graphene nanofiber bundle, and relates to the technical field of graphene fiber materials. The preparation method comprises the following steps: preparing and preparing a graphene oxide nanobelt solution, and adding a plasticizer to obtain a spinning solution; injecting the spinning solution into an electrostatic spinning device, performing near-field electrostatic spinning and air curing, and performing curing forming in a coagulating bath to obtain basic graphene oxide fibers; a plurality of fibers are assembled into nanofiber multifilaments in a coagulating bath, and then the nanofiber multifilaments enter a subsequent multi-stage combined drafting process to prepare a GO fiber aggregate; the GO fiber aggregate is immersed in a Lys-Dopa solution for a reaction, and finally the GO fiber aggregate is collected through a twisting process; reducing the collected GO fibers with hydroiodic acid to obtain reduced graphene fibers, and then performing high-temperature graphitization treatment to obtain a graphene nanofiber bundle product; the graphene fiber preparation process is improved from multiple aspects of raw material preparation, spinning and drafting, Lys-Dopa bath, twisting and the like, a new mechanical property improvement scheme is provided, and development of the graphene fiber field in the future is promoted.

The invention discloses a numerical simulation method for simulating resin flow in a molding process of an intelligent composite material with an embedded optical fiber. The method comprises the following steps: generating a fiber bundle model through a Monte Carlo random algorithm; establishing a mesoscopic model for embedding optical fibers inside or outside the fiber bundle; establishing a resin flow control equation based on a phase field method in the finite element model; applying pressure load to an inlet and an outlet of the model, and submitting finite element calculation; the velocity field and the pressure field obtained through simulation are checked, and the influence rule of the optical fiber on the resin infiltration fiber bundle is analyzed. The method has good guiding significance for optimizing the intelligent composite material forming process and reducing forming defects.

The invention belongs to the technical field of functional composite fibers, and discloses a wear-resistant nanofiber-reinforced protective graphene fiber and a preparation method and application thereof.The wear-resistant nanofiber-reinforced protective graphene fiber comprises a graphene fiber tow and nanofibers, the nanofibers coat the graphene fiber tow in a three-dimensional porous network mode, and the nanofibers coat the graphene fiber tow in a three-dimensional porous network mode. Forming a stress buffer layer; wear-resistant particles are uniformly loaded in the three-dimensional porous network; the preparation method comprises the following steps: fixing the graphene fibers subjected to surface pretreatment on an electrostatic spinning nano-yarn machine, forming a nano-fiber membrane by utilizing electrostatic spinning, uniformly wrapping the graphene fibers subjected to surface pretreatment with the nano-fiber membrane, then rolling into a shaft, and then carrying out hot-pressing roller treatment on the rolled fiber bundle, so as to obtain the graphene nano-yarn. The wear-resistant nanofiber reinforced protective graphene fiber is prepared; the graphene fiber is used for weaving to obtain the graphene fiber fabric. The fiber prepared by the invention and a fabric woven by using the fiber have excellent mechanical properties, wear resistance, electric conductivity and heat conductivity.

The invention discloses a waste textile splitting and recycling method, which is used for splitting waste textiles which are cut into sheets into short fibers and then carrying out classified recycling, and comprises the following three steps of: fermenting, opening and carding: carrying out padding and dipping treatment on pretreated sheet fabrics by adopting an auxiliary agent, so that the auxiliary agent is fully permeated into the fabric fibers; the cohesive force of fabric yarns and fibers is reduced; the fermented flaky fabric is subjected to splitting, opening and impurity removal treatment, wherein in the splitting procedure, warp and weft yarns of the flaky fabric are loosened, so that the beating force of opening equipment is reduced; in the opening process, the flaky fabric is flexibly opened, fiber blocks in raw materials are torn and released into small fiber bundles, the small fiber bundles are regenerated into a single fiber state, and conditions are created for smooth cotton carding; the small cotton bundles obtained after opening treatment are further decomposed and carded into a single fiber state through a carding machine by means of needle face movement, and qualified fibers are sucked into a packaging machine through a draught fan by means of an air duct to be automatically packaged.

The invention relates to a papermaking wastewater fiber recovery device which is characterized in that a main water distribution channel positioned at a high position is butted and communicated with a plurality of branch water channels below through a main water distribution hole in the bottom, two rows of vertical water distribution lattice walls are arranged in each branch water channel along the length direction and divide the branch water channel into a middle chamber, a left chamber and a right chamber, and the main water distribution hole is opposite to the middle chamber; the bottom of the water distribution lattice wall is provided with an overflowing channel, the middle cavity is communicated with the left cavity and the right cavity, the weir crest portions on the two sides of the water distribution canal are provided with vertical water uniformizing plates, the outer side of the weir crest is provided with a net frame inclining downwards, inclined net cloth is laid on the net frame, and the bottom end of the net frame is provided with a horizontal chute bottom plate in the length direction. A vertical chute baffle is arranged on the extending outer side of the chute bottom plate in the length direction, and a collecting groove used for collecting fiber agglomerates is formed. Wastewater uniformly flows through the water passing surface of the inclined net, fibers are efficiently intercepted on the inclined net surface and form fiber bundle clusters to roll down under the action of inlet water washing and gravity, and slurry-water separation is realized through the action of gravity in the whole process.

The invention relates to the technical field of fiber sizing treatment, and discloses an aramid fiber sizing device and method.The aramid fiber sizing device comprises a yarn unwinding device, a sizing tank, a yarn spreading and drying device and a winding device, the yarn spreading and drying device comprises a primary yarn spreading assembly, a drying roller and a secondary yarn spreading assembly, and the yarn spreading assembly comprises a first vibration roller, a conveying roller and a second vibration roller; the vibrating roller vibrates in the direction perpendicular to the fiber conveying direction. After being unreeled, fibers are sized through the sizing tank and fed into the yarn spreading and drying device to be subjected to wet broadening, mechanical damage to fiber bundles is reduced, and broken filaments are reduced. During primary yarn spreading, the vibrating roller vibrates at high frequency to enable fiber bundles to be dispersed and widened under the action of transverse friction force, extrusion mechanical damage of the fiber bundles is reduced, broken filaments are reduced, redundant size is removed, drying is facilitated, and adhesion between monofilaments is reduced. During secondary yarn spreading, fiber bundling force applied by surface tension of slurry does not need to be overcome, secondary spreading of fiber bundles is achieved under high-frequency vibration of the vibrating roller, and good monofilament dispersity is guaranteed.

The invention relates to the technical field of stereotactic surgery, and discloses a neurosurgery stereotactic surgery positioning system based on multi-modal image fusion, which comprises a multi-modal image acquisition module, an intelligent registration fusion module, a three-dimensional modeling module, a surgery navigation engine, an augmented reality interface and a dynamic calibration module, a cross-modal elastic registration module is arranged, when multi-modal image fusion is carried out, the spatial matching degree of a functional image and a structural image is detected in real time through a nonlinear deformation compensation algorithm, and when registration deviation exists between white matter fiber bundles and tumor boundaries, an elastic deformation compensation field is dynamically generated by a system, so that the positioning accuracy of a neural functional area is improved; and by arranging the dynamic drift correction module, the brain tissue displacement change is perceived in real time based on laser surface scanning during deep target navigation, precise correction of the pose of the surgical instrument is realized, and the positioning reliability of the deep target is ensured.

The invention provides a real-time yarn width detection method for carbon fiber prepreg yarn production, and relates to the technical field of carbon fiber manufacturing, and the method comprises the steps: arranging a binocular camera and a structured light projection unit on a production line, collecting an image sequence, extracting edge features, calculating a fiber bundle contour, and combining depth information to establish a three-dimensional point cloud model; the point cloud model and the calibration reference plate are projected to a standard plane fitting contour curve after being subjected to space registration; real-time width features and tension features are extracted, and an adaptive control limit value is constructed; and judging the defect type through trend analysis and deviation evaluation. According to the invention, high-precision real-time monitoring of the width of the prepreg yarn is realized, and the product quality stability is improved.

The invention relates to a mechanical property prediction method for a woven composite material structure, and the method comprises the steps: obtaining a microscopic CT image of the woven composite material structure; carrying out image preprocessing on the CT image; segmenting a fiber bundle in the preprocessed image to obtain a segmented fiber bundle image; extracting a fiber bundle trend center line from the segmented fiber bundle image; establishing a macroscopic geometric model of the woven composite material structure, and performing unit grid division on the geometric model; establishing a relation between a fiber bundle trend center line and a geometric model unit; calculating mechanical property parameters of each unit one by one; and calculating the macromechanical response of the composite material structure. According to the method for predicting the mechanical property of the woven composite material structure, the grid division independent of the microstructure characteristics is adopted, so that the modeling efficiency can be improved, the modeling difficulty can be reduced, and the method is easy to implement.

The utility model relates to a shaft grounding ring convenient to install, which comprises an annular shell, an upper support plate, a lower support plate and a conductive fiber bundle, one end of the conductive fiber bundle is provided with an installation piece, the lower support plate is provided with at least two grooves, the installation piece is arranged in the grooves, the upper support plate is arranged on the upper side of the lower support plate, and the lower support plate is arranged on the lower side of the annular shell. The upper supporting plate and the lower supporting plate are both arranged in the annular shell, the annular shell is provided with a fixing part protruding inwards, and the fixing part abuts against the upper supporting plate. The problems that an existing carbon fiber grounding ring is inconvenient to install and not firm in structure are solved.

The invention discloses a model construction and simulation method and device for a woven composite material and a storage medium, and the method comprises the steps: endowing a fiber bundle model and a porous matrix model with material performances at a microscopic scale, then applying a multi-physical field load, and extracting a thermal-mechanical response; homogenizing the microscopic model into material performance and transmitting the material performance to the microscopic model; constructing a woven composite material model through structural parameters on a microscale, and endowing the performance of the homogenized fiber bundles and the homogenized porous matrix; the periodic boundary condition of the service condition of the macrostructure and the multi-physical field load are applied to the mesoscopic model to obtain the thermal-mechanical response and performance degradation condition of the mesoscopic model and the fatigue damage condition under the cyclic load, and progressive failure analysis is completed; the actual response of the macrostructure in the multi-physical field is obtained; low-cost and high-precision numerical simulation and performance prediction of multiple scales and multiple physical fields are realized.