11363 results about "3D printing" patented technology

The invention relates to the technical field of 3D printing models, in particular to a 3D printing model slice feature compensation method and system and a medium. The method comprises the following steps that a 3D printing model is collected, a model feature skeleton is split, transverse slice features are generated, then a 3D printing environment is collected, virtual simulation is carried out, environment stress analysis is carried out on the skeleton slice features to obtain environment stress data, then deformation scale deduction and thermal deformation prediction are carried out based on the environment stress data, and a thermal deformation model is obtained. On the basis, reverse deformation simulation is carried out, deformation repair requirements are evaluated, a deformation compensation path is planned, finally, compensation simulation of a model feature skeleton is achieved, non-target deformation is analyzed, a compensation path is adjusted, and therefore the feature compensation method is optimized. According to the 3D printing model slice feature compensation method, the accuracy and quality of the 3D printing model are integrally improved.

The invention provides an enhanced 3D printer. The enhanced 3D printer comprises a workbench, and a transmission mechanism with a printing platform is installed on the workbench; an internal thread piece with an internal thread hole is detachably mounted on the printing platform, and the reinforcing screw rod is screwed in the internal thread hole of the internal thread piece; the printing platform is provided with a driving device used for driving the reinforcing screw to rotate. The model is bonded on the printing platform, and a reinforced hole is formed in the model; under the driving of the driving device, the reinforcing screw rod can do reciprocating motion in the vertical direction, and the reinforcing screw rod is screwed into the reinforcement hole or withdrawn from the model; the scraper in the trough can move from one side to the other side to push solid particles deposited at the bottom of the trough from the working area to the non-working area. The invention further provides an enhanced 3D printing method. According to the method, the situation that cracks and even fractures occur to the model due to the gravity influence and the binding force effect of the release film in the printing process can be effectively reduced or even avoided.

The invention discloses a rapid metal printing system and method based on machine vision feedback, and belongs to the technical field of 3D printing. The system comprises a data acquisition module used for determining the surface height difference, the temperature gradient and the density fluctuation of all preset areas in the first layer of the rapid metal printing object; the defect probability prediction module is used for obtaining the defect probability of each preset area in the first layer of the rapid metal printing object; the adjustment scheme determination module is used for determining a defect type and an adjustment scheme of a target preset area by taking the preset area corresponding to the defect probability exceeding a preset defect probability threshold value as the target preset area; and the printing adjustment module is used for performing printing adjustment on the first layer of the rapid metal printing object. According to the scheme, through accurate defect prediction, real-time adjustment and automatic control, the metal printing quality and efficiency can be improved, resource waste can be greatly reduced, the cost is reduced, and the flexibility and the intelligent level of the production process are enhanced.

The invention discloses a 3D printing process intelligent control method and system based on real-time feedback, and relates to the technical field of 3D printing, a data acquisition module collects a printing layer surface image and printing data in real time, constructs an image data set and a printing data set, and performs cleaning and standardization processing on the data in a preprocessing module; the image analysis module analyzes surface defects of a printing layer by using a convolutional neural network, generates a defect score D, compares the defect score D with a preset defect score threshold D1, evaluates the state of the printing layer and triggers early warning, and the comprehensive evaluation module calculates a crack generation probability Z by combining printing data and the defect score; and the intelligent control module compares the crack generation probability Z with a preset crack generation probability threshold value Zl, evaluates the printing state and feeds back and controls printing parameters according to a result, so that crack and structure defects in the printing process are effectively prevented and reduced, and the printing precision and the finished product quality are improved.

The invention discloses an airspace engine 3D printing deformation compensation method. The method comprises the following steps that S1, a three-dimensional CAD model is constructed, and a printing layer set is generated; s2, obtaining residual stress tensor fields of the current printing layer and the historical printing layer; s3, constructing a stress shadow mapping tensor; s4, inputting the stress shadow mapping tensor and the current printing layer parameter into the reverse stress propagation neural network model, and outputting a deformation prediction vector field; s5, performing geometric compensation processing on the geometric area of the printing layer according to the deformation prediction vector field; s6, generating a printing code according to the compensated geometric model; and S7, carrying out error comparison on the actual deformation vector field and the overall prediction deformation vector field, if the error is greater than a preset tolerance threshold value, feeding back error information to the step S5, and repeatedly executing the steps S5 to S7 until the error vector field does not exceed the tolerance threshold value. According to the method, residual stress modeling and the reverse stress propagation neural network are fused, and 3D printing deformation compensation of the airspace engine is achieved.

The invention belongs to the technical field of aerogel materials, and particularly relates to antistatic aerogel for 3D printing as well as a preparation method and application of the antistatic aerogel. The preparation method comprises the following steps: (1) dispersing inorganic nanoparticles modified by a silane coupling agent containing epoxy groups and an aniline monomer in an acidic solvent to obtain a monomer mixed solution; (2) stirring and dissolving polyamide in the monomer mixed solution; (3) initiating a reaction to obtain a polyaniline modified polyamide solution; and (4) freeze-drying to obtain the antistatic aerogel for 3D printing. By controlling synthesis conditions, a core-shell structure of acid-doped polyaniline coated inorganic nanoparticles is formed, and a good conductive path is formed in polyamide with a small addition amount of polyaniline. The antistatic aerogel for 3D printing can be applied to technologies such as photocuring molding and fused deposition of polyurethane resin in a 3D printing technology, and the antistatic property and the mechanical property of a 3D printed product are improved.

The invention belongs to the technical field of aerogel materials, and particularly relates to high-performance antistatic aerogel for 3D printing as well as a preparation method and application thereof. According to the invention, inorganic hollow nanoparticles are selected as a nucleating modifier for in-situ polymerization of aniline monomers in a polyamide solution, so that polyaniline-coated inorganic hollow nanoparticles are uniformly dispersed in polyamide, and the aerogel composite material with polyamide as a continuous phase and polyaniline-coated inorganic hollow nanoparticles as a conductive and reinforced phase is formed. The use of the hollow inorganic nanoparticles avoids the problem that the solid inorganic nanoparticles lose the characteristics of the inorganic nanoparticles due to high specific gravity and high surface energy, and easy agglomeration or adsorption with other substances in the preparation process of the solid inorganic nanoparticles. The inorganic hollow nanoparticles are adopted as a nucleating modifier, so that the problems of agglomeration of solid nanoparticles and dispersion in a polyamide matrix are well solved.

The invention provides a photocuring material performance prediction method based on deep learning, and relates to the technical field of photocuring 3D printing, and the method comprises the steps: collecting the multi-modal data of a photocuring material in real time; performing data cleaning, de-noising and standardization processing on the acquired multi-modal data, fusing the processed multi-modal data, and extracting key index values and printing process parameters of a material formula; constructing an initial deep learning neural network model by using key index values in the extracted multi-modal data; printing process parameters are used for training the initial neural network model, gradient descent is adopted for optimizing the model weight, performance evaluation and optimization are conducted on the model through cross validation, and a material performance prediction model is obtained after verification; and predicting the performance of a to-be-predicted photocuring material based on the material performance prediction model. By comprehensively analyzing the formula, illumination conditions and printing parameters of the photocuring material, the performance of the material under different conditions is accurately predicted.

The invention relates to the field of progressive stamping die manufacturing, in particular to a stamping die manufacturing control method and system for a new energy motor iron core, and the method comprises the following steps: analyzing the material performance and the stamping effect through artificial intelligence, and intelligently recommending an optimal material combination; the die is quickly verified by using digital design and 3D printing, and the design is optimized by combining virtual simulation; developing an intelligent control system, dynamically adjusting the position of the mold, and ensuring accurate alignment of procedures; a big data platform is established, and punching parameters are automatically optimized through machine learning; online detection is integrated, and mold parameters are adjusted in real time to correct deviation; and mold health monitoring and predictive maintenance are implemented, so that shutdown is reduced. The steps jointly achieve intelligentization and self-adaptive optimization of stamping die manufacturing.

The invention discloses an industrial particle 3D printer cavity temperature heat recovery system and a cavity temperature control method, and relates to the technical field of 3D printing, and the method comprises the following steps: establishing a three-dimensional geometric analysis model of a printing component, based on the structural morphology, thickness distribution and spatial topology characteristics of the component, extracting a spatial temperature control demand corresponding to each region, and calculating a three-dimensional geometric analysis model of the printing component; and determining an adjusting target of the hot air circulation system. According to the method, a space temperature control demand model is established based on geometrical characteristics of a component, oriented distribution of heat energy is realized by dynamically adjusting a hot air circulation system, a cooling characteristic curve is constructed in combination with real-time temperature and stress data, and a warping resonance sensitive area is identified and regulated. And a self-adaptive temperature control system is formed through fixed-point thermal compensation and parameter closed-loop correction. Compared with a traditional strategy, the method has the advantages that the temperature control precision and the response efficiency are remarkably improved, thermal stress resonance and structural deformation in the cooling process are effectively restrained, and the method is suitable for stable forming of high-precision complex components and has wide application prospects.

The invention discloses an injection molding temperature control method for rapid injection molding of an injection molded part, and relates to the field of injection molding temperature control, and the injection molding temperature control method comprises the following steps: performing main body division on a mold by scanning three-dimensional space data of the mold and combining geometric characteristics, and performing structural stability evaluation and gradient calibration on a main body division result; analyzing the surface curvature of a main body division area based on a main body division result, and setting a cooling channel local loop in combination with the heat distribution condition of an actual thermoplastic process; performing loop integration on the cooling channels of all the main body division areas, and setting the flow velocity of cooling liquid in the cooling channels based on the stress change of the injection molding part; based on the finally determined communication distribution of the cooling channels and the flow speed of the cooling liquid, the mold and the cooling channels are produced through 3D printing; according to the method, the injection molding period is remarkably shortened, the production efficiency and the quality and stability of injection molded parts are improved, and the method is suitable for rapid molding requirements of high-precision complex injection molded parts.

The invention discloses a 3D printing path planning method based on electric arc additive anisotropy and a stress field, and the method comprises the steps: constructing a CAD three-dimensional model of a part, and obtaining the stress field of the part through finite element simulation; determining a slice plane; mapping the stress field to a slice plane to form a force flow line; according to the obtained force flow line, rotation transformation regeneration is carried out according to the anisotropy of the used electric arc additive, and a reference trajectory considering the anisotropy of the material is obtained; under the principle of alternate arc starting and extinguishing, the corresponding printing sequence in the layers and between the layers is further planned, and the reference trajectory lines are connected end to end to be planned into a continuous path; and generating a code file, and printing according to the printing sequence. The comprehensive mechanical property of a printed piece is improved.

The invention discloses a method and a system for efficiently and rapidly detecting protein content and moisture content in a plant-based product based on near infrared spectrum and deep learning, and the method comprises the following steps: obtaining spectral data of a plant-based sample, and carrying out experimental determination on the protein content and the moisture content; in combination with multi-step data preprocessing and adaptive dimensionality reduction, feature signals highly related to target detection are extracted, and a deep learning model based on a convolutional neural network and a self-attention mechanism is utilized to construct a high-precision detection model; a final stable detection model is obtained through multiple times of verification and optimization of the model, and hardware integration is carried out on the final stable detection model and a portable spectrometer to form a detection system. The detection system comprises a 3D printing shell, a spectrum sensor, a conversion line and a data processing unit, the protein content and the water content of a sample can be rapidly and nondestructively detected through one-key operation, and the whole process does not need chemical reagent intervention. The method has the advantages of being high in detection speed, high in portability, easy and convenient to operate, wide in application scene and the like, and is particularly suitable for application occasions needing efficient and on-site real-time detection.

The present disclosure relates to a high-precision multilayer PCB and a 3D printing preparation method thereof. The method includes: S1, forming a 3D circuit layer on an upper surface of a substrate; S2, forming a metal pillar at a preset position of the current 3D circuit layer by stacking; S3, forming an insulating layer on an upper surface of the current 3D circuit layer, and leading the corresponding metal pillar out of the formed insulating layer in advance by drilling a hole in the insulating layer and filling the drilled hole with the nanoscale metal slurry; S4, forming a pad layer on an upper surface of the current insulating layer and executing step S5 if the current insulating layer is a top layer; repeatedly executing steps S1 and S2 by using the current insulating layer as a new substrate and executing step S6 if not; S5, connecting the corresponding metal pillar or leading it out in advance and connecting to the pad layer, to complete the preparation of the multilayer PCB; and S6, connecting the corresponding metal pillar or leading it out in advance and connecting to the current 3D circuit layer, and returning to step S3. According to the present disclosure, the high-precision multilayer PCB with high interconnect precision can be prepared.

The invention provides a gradient crosslinking process of photosensitive resin for photocuring 3D printing, and relates to the technical field of photocuring 3D printing materials. The gradient crosslinking process of the photosensitive resin for photocuring 3D printing comprises the following steps: S1, based on double-initiator system design, adopting molecular dynamics simulation screening, respectively adding a 405nm sensitive type TPO-L initiator and a 365nm sensitive type I TX initiator into an epoxy acrylate prepolymer, and verifying initiation energy barrier matching through quantum chemistry calculation, and generating a pre-initiation gradient resin formula. Through molecular dynamics simulation, initiator combinations are screened, energy barrier matching is verified, the ratio of dual-wavelength sensitive initiators is optimized, and accurate triggering of surface layer and deep layer cross-linking reaction is ensured. And a three-roller grinding and dispersing process is combined with ultrasonic oscillation to eliminate nanoparticle aggregation, so that the mechanical uniformity and light scattering effect of a resin system are improved.

The invention discloses a multi-laser multi-material laser cladding 3D printing method and system, and relates to the technical field of 3D printing, and the method comprises the steps that according to a three-dimensional model of a target component, a printing path and a lap joint point position are determined; carrying out regional division on the working face; a sensor is used for detecting the thickness of each layer in real time, and the printing speed and the laser power are adjusted according to detection data; laser welding is carried out on a lap joint area between the printing layers, and laser annealing is carried out to release residual stress; and according to component requirements, different materials are dynamically switched in the printing process. The multi-printing-head and multi-laser-device cooperative work, path optimization and dynamic feedback control, material dynamic switching and laser annealing treatment technologies are adopted, and the problems of size limitation, insufficient interlayer binding force, complex material switching, path conflict and thermal stress in the large forming part manufacturing process are fundamentally solved. Compared with a traditional process, the printing efficiency, the finished product quality and the production flexibility are remarkably improved.

The invention relates to the technical field of 3D printing error compensation and precision control, and particularly discloses a printing comprehensive precision measurement method for 3D printing equipment, which comprises the following steps: designing a standard test piece containing various typical geometrical characteristics, and combining non-contact three-dimensional optical scanning and contact probe measurement means to measure the printing comprehensive precision of the 3D printing equipment. Spatial distribution data of printing errors are obtained in a controlled environment, a three-dimensional error field model with direction and amplitude information is constructed through point cloud registration and feature comparison, and based on error distribution features, the local resolution is dynamically adjusted by adopting a multi-level self-adaptive grid division strategy, so that a three-dimensional error field model with direction and amplitude information is constructed. A local error compensation model is established by combining tightly-supported radial basis function interpolation and a linear fitting method, a boundary consistency matching algorithm is introduced to realize multi-level model fusion, a unified global error compensation field is formed, an error offset vector field is embedded into a slicing process, point-by-point dynamic correction of a nozzle path is realized by using a trilinear interpolation algorithm, and the nozzle path is dynamically corrected. And the forming precision and the surface quality of the key structure are improved.

According to the liquid cooling heat dissipation cold plate based on the TPMS structure and the implementation method of the liquid cooling heat dissipation cold plate based on the TPMS structure, a model file of a three-dimensional TPMS porous structure is generated through K3DSurf software based on a parameter equation of a heat exchange unit, and after a complete liquid cooling cold plate model based on the TPMS structure is assembled and constructed, the liquid cooling heat dissipation cold plate based on the TPMS structure is obtained through laser 3D printing. Single-phase or two-phase flow heat exchange can be carried out, and the heat dissipation capability of electronic equipment with high heat flux density can be remarkably enhanced.

The invention discloses a processing method and system for abnormal operation of photocuring 3D printing. The method comprises the steps that parameter values of all operation parameters in the printing process of photocuring printing equipment are collected; according to the parameter values, abnormal operation parameters in all the operation parameters are searched for; if the abnormal operation parameters are not found, inputting all the operation parameters and parameter values thereof into a pre-trained AI-based first printing fault prediction model, and predicting a potential printing fault type and a fault degree thereof; according to the printing fault type and the fault degree of the printing fault type, the parameter value of each operation parameter is adjusted, so that the predicted printing fault type is free of faults, and abnormal operation parameters do not exist in the operation parameters. By utilizing the embodiment of the invention, the timeliness and accuracy of fault detection can be improved by acquiring the real-time operation parameters, identifying abnormal conditions and predicting the fault type and degree based on the AI model, the automatic adjustment of the printing parameters is realized, and the stability and reliability of the printing process are ensured.

The invention belongs to the technical field of personalized insole manufacturing, particularly relates to a personalized insole manufacturing method and system based on three-dimensional motion capture and 3D printing, and aims to solve the problem that most existing insoles are generally manufactured and lack targeted design for consumers. The method comprises the following steps: preprocessing foot data of a target to obtain preprocessed foot data; performing feature extraction on the preprocessed foot data to obtain each foot feature; constructing a comprehensive feature vector of each foot feature based on the data source feature of each foot feature; performing mechanical analysis on the target based on the data source features to obtain a mechanical analysis result; performing multi-modal fusion on each comprehensive feature vector by using an algorithm to obtain a foot biomechanical model; and performing 3D printing of the insole based on the mechanical analysis result and the foot mechanical model. According to the method, scientific and objective data support is provided for comprehensive quantitative analysis of the motion state of the foot, and manufacturing of personalized insoles is guided.

The invention provides a personalized functional nutritional tea point rich in tea polyphenol and resveratrol and a 3D printing manufacturing method. The personalized functional nutritional tea point comprises a shell and an inner core, wherein the shell and the inner core are respectively a shell gel material and an inner core gel material; the inner core gel material comprises a water-oil double-gel material rich in tea polyphenol and resveratrol; wherein the water-oil double-gel material is prepared by the following steps: adding chitosan, betaine and vanillin into a mixed solution of corn starch, chickpea protein and water, heating and incubating to obtain hydrogel; and dissolving the tea polyphenol in the hydrogel to obtain the tea polyphenol hydrogel. The oleogel is obtained by melting and mixing beeswax and linseed oil, and then dissolving resveratrol in the oleogel; the personalized functional nutritional tea point is high in content of active ingredients of tea polyphenol and resveratrol and has heat stability, illumination stability and storage stability; the 3D coaxial printing technology is utilized, the functional components are further stabilized, tea points of various patterns and shapes can be obtained, and the method has personalized food preparation and application value.

The invention discloses a small automatic seeder for hole sowing crops, which consists of a mechanical system and a control system, the mechanical system comprises rear wheels, an electric box, a first steering engine, a seed-metering device movement turntable, a translation rod, a seed box, a second steering engine, a front wheel, a first motor, a hose, a seed-metering device, a seed-metering device connecting rod, a second motor, a shell, a steel wire, a seed-metering device fixing ring, an infrared sensor and a frame; the control system comprises a sensing input system and a motion system. According to the device, seeds are tidied before seed metering, and the seed falling number is accurately controlled; the three-petal type seed-metering device is adopted, so that the device can be used for soil with relatively high hardness, and integration of hole digging, seed burying and soil covering is realized; the porous seed tray is manufactured through 3D printing, the design is more reasonable, manufacturing is more convenient and faster, multiple purposes can be achieved by replacing the seed tray, and planting of different crops and different planting requirements are met; path planning is performed according to the initial design, and the seeding depth and spacing are adjusted, so that manpower and material resources are saved, and a scheme is provided for realizing large-scale integrated planting.

The invention discloses a multi-mode sensing electromechanical actuator fault prediction system and a control method thereof, and relates to the field of intelligent maintenance of electromechanical integrated equipment. Comprising the following steps: S1, multi-mode sensor deployment and signal acquisition: cooperatively deploying a vibration sensor, a current sensor and a temperature sensor at a bearing, a motor winding and a driver of an electromechanical actuator; and S2, bionic pulse coding and time synchronization: converting the three-mode signal into a sparse pulse stream with time synchronization through a self-adaptive integral distribution model with dynamic threshold adjustment. Through bionic multi-mode sensing, brain-like edge calculation and dynamic fault-tolerant control, real-time health management of the high-precision electromechanical system is realized, the equipment reliability is remarkably improved, and the operation and maintenance cost is reduced. The method is suitable for industrial application with precise assembly requirements such as automobile welding lines, aerospace machining and metal 3D printing.

The invention discloses a double-layer microneedle patch and a preparation method thereof.The preparation method of the double-layer microneedle patch comprises the following steps that firstly, 3D printing is conducted through polydimethylsiloxane, and a PDMS mold similar to a machining microneedle is obtained; dispersing the medicine into the sericin solution to serve as an outer layer solution; dispersing germanium nanoparticles into the polycaprolactone solution to obtain an inner layer solution; and finally, adding the outer-layer solution into the needle-shaped groove of the PDMS mold, so that the needle-shaped groove is filled with the outer-layer solution, drying, adding the inner-layer solution, drying, and demolding to obtain the double-layer microneedle patch. When the double-layer microneedle patch is used for drug delivery, drugs can be dissolved and released in a short time, the inner layer is polycaprolactone (PCL) carrying photo-thermal agent germanium nanoparticles, degradation is slow, a photo-thermal effect is generated under irradiation of 808nm near-infrared light, residual tumor cells are induced to die immunogenicity, an immune microenvironment is programmed in a time sequence, and the double-layer microneedle patch has the advantages of being high in sensitivity, high in sensitivity and good in stability. Postoperative recurrence and metastasis of tumors are efficiently inhibited, and meanwhile operative wound repair is promoted.

Provided is an integrated probe pin that includes an upper plunger having a first tip adapted to come into contact with a circuit to be inspected to transmit and receive electrical signals to and from the circuit to be inspected; a lower plunger having a second tip adapted to come into contact with an inspection circuit to transmit and receive the electrical signals to and from the inspection circuit; and an elastic part located between the upper plunger and the lower plunger to elastically support the upper plunger and the lower plunger, wherein the upper plunger, the lower plunger, and the elastic part are manufactured as an integral body using 3D printing and made of one or more metal materials.

The invention belongs to the technical field of ceramics and slurry thereof, and particularly relates to fiber-reinforced ceramic photocuring slurry, a preparation method and a reinforced ceramic material. The slurry provided by the invention consists of ceramic powder, ceramic composite short fibers, light-cured resin, a photoinitiator, a dispersing agent, a plasticizer and the like, wherein the ceramic composite short fibers are zirconium oxide and silicon oxide composite fibers; the light-cured resin contains a photosensitive resin monomer and a prepolymer; and the photoinitiator is compounded by a short-wavelength initiator and a long-wavelength initiator. The preparation method comprises the following steps: modifying the ceramic composite short fibers with a silane coupling agent, mixing the modified ceramic composite short fibers with all the materials, and carrying out ball milling and defoaming. The obtained slurry is subjected to 3D printing photocuring molding and degreasing sintering, and a reinforced ceramic material can be prepared. The slurry can be used for manufacturing a high-performance ceramic material through composite short fiber synergistic enhancement, long and short wavelength initiator synergistic curing and fiber surface modification, and the curing depth, the three-point bending strength and the fracture toughness are remarkably improved.

A nozzle embedded type 3D printing device for a thermosetting wood-plastic composite material belongs to the technical field of 3D printing, and comprises a rack, and an extrusion movement mechanism, a powder laying mechanism, a powder bed mechanism, a printing platform movement mechanism and a binder feeding system which are arranged on the rack, and the extrusion movement mechanism is fed through the feeding system. The printing efficiency of existing printing equipment can be improved, the manufacturing and maintenance cost of the existing equipment is reduced, the accuracy and consistency of a printing structure are ensured, and printing of a high-precision complex structure is achieved; the provided equipment combines the advantages of extrusion type printing equipment and a powder bed structure, the requirement of single extrusion printing for the formability of extruded materials is met, controllable printing of large-flow, high-viscosity and large-layer-thickness printing shapes and precision is achieved, the equipment is suitable for various types of binder materials, the variety and size range of powder bed materials is large, and the equipment is suitable for large-flow, high-viscosity and large-layer-thickness printing. And the rapid part forming machining requirements of wide material application range, large forming size and high part strength are met.

The invention relates to the technical field of denture manufacturing, and discloses a high-precision digital complete denture 3D printing method which comprises the following steps: obtaining an initial denture model of a target object; acquiring occlusal point adjustment data; acquiring actual adjustment data; adjusting the initial false tooth model based on the actual adjustment data, and converting the adjusted initial false tooth model into a 3D printing instruction for 3D printing; according to the method, stress distribution during occlusion is simulated through finite element analysis, a three-dimensional occlusion thermodynamic diagram is obtained and input into a constructed CNN network model, occlusion point adjustment data are obtained, adjustment data of effective occlusion contact points are mapped into a solid model, and actual adjustment data are obtained; three-dimensional data of the oral cavity of a patient is obtained through a scanner, digital analysis is conducted in combination with a neural network model, the denture manufacturing precision is improved, manufacturing is conducted in a 3D printing mode, the manufacturing efficiency is high, the patient feels comfortable when wearing the denture and occludes the denture well, and the problem of diet difficulty of the implant patient is solved in time.

The invention provides a 3D printing product sorting system based on a multi-cascade grabbing network framework. The 3D printing product sorting system comprises a control module, a sorting platform used for containing 3D printing products and a mechanical arm used for sorting the 3D printing products. A camera connected with the control module is arranged above the sorting platform; the method comprises the following steps of: acquiring an image of a 3D printing product through a camera, generating a high-resolution image through a super-resolution reconstruction technology, processing the image by using an improved YOLOv5 + E-A-SPPFCSPC + BiFPN instance segmentation algorithm, accurately positioning a target 3D printing product to be grabbed, and controlling the grabbing operation of a mechanical arm through an AFFGA grabbing detection network; the track of the mechanical arm is dynamically planned through the optimized particle swarm algorithm, it is guaranteed that the grabbing network finds the optimal path to reach the target grabbing position within limited time, and meanwhile the smoothness of the track is guaranteed; according to the method, dynamic planning optimization of the grabbing track of the mechanical arm is combined, all links of sorting of the 3D printing products can be comprehensively optimized, and high-definition imaging, accurate positioning and intelligent decision making are achieved.

The invention belongs to the field of electrode materials, and relates to a cement-based electrode material capable of 3D printing and a preparation method and application thereof. The cement-based electrode material comprises 500 to 600 parts of cement, 10 to 25 parts of aluminum sulfate, 70 to 84 parts of surface activated carbon black, 150 to 300 parts of surface modified quartz sand, 7.5 to 15 parts of carbon fiber, 500 to 600 parts of water and 6 to 10 parts of a water reducing agent. The material has excellent mechanical properties and electrical properties, can realize integration of energy storage and structural functions, has high practical application value, and is especially applicable to the fields of intelligent building materials and green energy storage. And through the 3D printing technology, complex structure customization of the cement-based material can be achieved, structural energy storage integration is expected to be achieved, and a new thought is provided for development of a smart energy system in the building field.