52results about How to "Retain structure" patented technology

The invention discloses an advertisement compliance knowledge question-answering method, device and equipment for foreign enterprises, and the method comprises the steps: obtaining advertisement compliance data of a global data source, carrying out the document structuring and knowledge extraction of the advertisement compliance data, and constructing an advertisement compliance knowledge graph; converting text data in the advertisement compliance knowledge graph into vectors to obtain vector data; semantic analysis is conducted on a query question input by a user, construction is conducted in combination with the vector data, prompt words are obtained, the prompt words are input into a preset large language model, and target answers are obtained; and outputting the target answer based on the advertisement compliance knowledge graph, and visually displaying the target answer in a corresponding answer query graph. And comprehensive and efficient compliance information query and answer services can be provided, so that compliance review requirements of foreign enterprises on advertisements in a multi-language and cross-regional environment can be met.

The invention discloses a preparation method of a pre-fibration polymer solid electrolyte as well as a product and application of the pre-fibration polymer solid electrolyte. The method comprises the following steps: demulsifying and drying polytetrafluoroethylene (PTFE) emulsion to prepare pre-fiberized PTFE dry powder, then mixing sulfide lithium phosphorus sulfur chlorine (Li6PS5Cl) electrolyte and fiberized PTFE in a proper proportion, and directly preparing the sulfide solid electrolyte composite membrane through a room temperature rolling solvent-free dry process. The pre-fiberized solid sulfide electrolyte film avoids high-cost and high-energy-consumption operations such as ball milling, hot pressing and the like, and the preparation energy consumption and the equipment cost are reduced. The material can be effectively applied to the field of preparation of solid-state batteries, and the structure and performance of an electrolyte material are fully reserved. The method is a solid electrolyte film forming technology with an application prospect, and has an important application value for the development of a solid-state battery.

The invention discloses a maleamic acid-tragacanth copolymer as well as a preparation method and application thereof, and the maleamic acid-tragacanth copolymer is prepared from the following raw materials in parts by weight: 3-7 parts of maleic anhydride, 90-110 parts of an absolute ethyl alcohol solvent, 10-15 parts of polyethyleneimine, 8-10 parts of polyethylene polyamine and 40-60 parts of an alcohol-water solution, and 15-30 parts by weight of a tragacanth modified derivative. A tragacanth modified derivative is introduced into maleic anhydride amidation in a ring-opening grafting blending manner, so that two adsorption materials have a synergistic effect, the characteristics of biodegradability, a macromolecular porous structure and the like are retained, and a large number of functional groups such as hydroxyl, carboxyl, amido, carbon-carbon double bonds and the like are introduced; toxic substances such as heavy metals, medical intermediates, dyes and pesticides in the wastewater are removed by virtue of comprehensive effects of electrostatic force, hydrogen bonds, Van der Waals force, inclusion and the like.

The invention relates to the technical field of semantic segmentation, in particular to a night semantic segmentation method based on low illumination enhancement and edge optimization, and the method comprises the steps: inputting an image into a low-light enhancement repair network based on the Retinex theory, local contrast enhancement and adaptive feature fusion, obtaining a denoised and enhanced intermediate image, and carrying out the edge optimization of the intermediate image; inputting the intermediate image into a semantic segmentation network to obtain a category distribution diagram of each pixel; inputting a discriminator embedded with a channel attention module according to the category distribution diagram of each pixel, and optimizing a generator composed of a low light enhancement repair network and a semantic segmentation network through a multi-task joint optimization loss function; and inputting a night image to be detected and segmented into the optimized generator, and outputting a segmentation result. By adopting the method, the low-light enhancement repair network is combined with a local contrast enhancement and channel feature fusion mechanism, so that the overall brightness of the image is improved, the details and edge structures of the image are reserved, and the perception capability and robustness of the model are improved.

The invention discloses a polarization degree and light intensity image fusion method based on bidirectional cross attention. The method belongs to the technical field of polarization imaging, computational imaging and image processing. The technical problems that in the prior art, dynamic balance between structural detail keeping and polarization saliency enhancing is generally difficult to achieve, and particularly under the condition of a complex background or a low signal-to-noise ratio, texture missing or noise artifacts are prone to occurring in a fusion result are solved. A fusion mechanism capable of establishing a two-way information interaction relationship between a light intensity image and a polarization degree image is provided, and further processing is carried out aiming at a noise problem, so that more stable and more reliable polarization fusion imaging is realized.

The invention relates to the technical field of logistics management, in particular to an in-transit supervision method for large-size transportation on an expressway. The method comprises the following steps: acquiring transportation speed data and transportation vibration data; carrying out transportation speed feature extraction on the transportation speed data to obtain transportation speed feature data, and carrying out transportation vibration feature extraction on the transportation vibration data to obtain transportation vibration feature data; performing feature map construction on the transportation speed feature data and the transportation vibration feature data to obtain transportation speed vibration feature map data; abrupt change feature collection and change degree extraction are carried out according to the transportation speed vibration feature map data, and transportation abrupt change feature data and transportation change degree data are obtained so as to carry out large piece transportation anomaly detection operation. According to the invention, the safety and the management level of the large-piece transportation process are effectively improved.

The application discloses a Bayer image denoising method, which comprises the following steps: obtaining a Bayer image and performing a demosaicing operation to obtain an RGB image; converting the format of the RGB image to obtain a YUV image; performing image denoising on the Y channel of the YUV image to obtain Ynr; performing downsampling on the Bayer image to obtain four chrominance subgraphs R1, Gr1, Gb1 and B1; performing downsampling on the Ynr image to obtain four luminance subgraphs YR1, YGr1, YGb1 and YB1; performing guided filtering on the chrominance subgraphs by using the luminance subgraphs to obtain four chrominance filtered images R1nr, Gr1nr, Gb1nr and B1nr; performing guided filtering on each level of the luminance subgraphs and the chrominance subgraphs by using a Gaussian pyramid; and performing upsampling and weighted fusion on each level of the four chrominance filtered images and restoring the images to the original positions to output a Bayer denoised image. The application takes into account low-frequency and high-frequency signals, improves the image signal-to-noise ratio, and retains more image details.

The invention relates to the technical field of fabric recovery, in particular to a production process of cyclically regenerated polylactic acid and low-temperature spandex fabric. The production process provided by the invention overcomes the problems of high stress of polylactic acid and low-temperature spandex fabrics at low temperature and poor dyeing and fixation effects. Four different types of fabrics including polylactic acid fibers, cotton fibers, polyester fibers and spandex are subjected to recovery treatment and physical treatment and then treated with an organic solvent and a phosphoric acid solution, and the raw materials are treated with a prepared PLA decomposition catalyst and a lactide ring-opening catalyst. Vitamin B12, a chain extender and isocyanate are supplemented in the technological process, and the dyeing process of low-temperature treatment is adopted, so that the stress of the regenerated polylactic acid and low-temperature spandex fabric is reduced, the dyeing and color fixing effects are good, and the closed loop of recycling and reusing of the polylactic acid and spandex waste fabric is realized.

The invention discloses a head and neck tumor image segmentation method based on combined analysis of CT and PET, and the method comprises the steps: obtaining a head and neck tumor data set, and carrying out the preprocessing of the head and neck tumor data set; constructing a parallel common attention mechanism module; an improved UNet3D network model is constructed; optimizing the improved UNet3D network model by adopting a combined loss function; and inputting the preprocessed head and neck tumor data set into the optimized and improved UNet3D network model, and outputting a segmentation task result of the bimodal image. According to the method, a parallel common attention mechanism and a multi-scale feature fusion technology are introduced, multi-modal image information is efficiently combined, features of the tumor under different scales are captured, accurate segmentation is carried out on the features, the precision and efficiency of head and neck tumor segmentation are remarkably improved, the limitation that a single-modal image is difficult to comprehensively reflect the tumor features is overcome, and the accuracy and efficiency of head and neck tumor segmentation are improved. And the problem of scale diversity of the tumor in the image is solved.

This invention discloses a virtual immunohistochemical staining method and system based on relation generative adversarial networks (GANs) and sequence slide data, comprising the following steps: Step S1, constructing a sequence slide dataset, wherein each H&E-stained slide is followed by three consecutive Ki67-stained slides; Step S2, constructing a relation generative adversarial network (GAN) model, the model comprising two ResNet generators and two relation discriminators, used to train and evaluate the credibility of the sequence relationship between image pairs; Step S3, performing two-stage training on the relation generative adversarial network model, namely, basic style pre-training and Z-axis alignment relation adaptation. This invention fundamentally solves the Z-axis alignment problem, resulting in higher image fidelity and pathological accuracy, significantly improving clinical application value, and providing new research resources and evaluation paradigms.

This invention discloses a specular removal method based on grouped enhanced convolutional attention feature fusion, belonging to the field of image processing technology. The method constructs a specular removal model based on a CycleGAN network, which consists of a generator, a discriminator, and a loss function optimization module. The generator includes detail enhancement depth downsampling, upsampling, and grouped enhanced convolutional attention fusion modules, effectively capturing image details, reducing checkerboard artifacts, and enhancing feature fusion and capture capabilities. The discriminator uses a PatchGAN structure to improve local detail capture capabilities. The optimized loss function integrates multiple losses to improve model performance. Experimental results show that compared with various traditional and deep learning methods, the method of this invention outperforms in PSNR and SSIM metrics, exhibits strong adaptability, and can provide high-quality image data for subsequent detection of elevator door components.

The application discloses a rumor detection framework based on adaptive data enhancement and adversarial training, and aims to overcome the problems that the prior art only considers structure and ignores features when facing data noise problems, and does not consider the influence of adversarial attacks on rumor detection problems. The steps of the method are as follows: 1. processing the data set; 2. using an adaptive data enhancement method to weaken the influence of noise; 3. using a graph convolutional neural network to generate a graph representation; 4. using an adversarial generation module to generate an adversarial representation to improve the robustness of the model; and 5. constructing a joint loss function to optimize the rumor detection task.

The present application relates to a kind of based on carbonized wood natural structure dopamine electrochemical sensor and its preparation method and application, the working electrode of the electrochemical sensor is modified with carbonized wood-ZnO nanowire-ZIF-8.The electrochemical sensor of the present application uses carbonized wood as substrate, after cutting carbonized wood whole piece, using conductive carbon paste is pasted on working electrode, while ensuring conductivity, also retain the three-dimensional structure of nanomaterial not be destroyed, guarantee the performance of sensor, with good application prospect.

The present application relates to a kind of processing method for prescription data, electronic equipment and storage medium, it is related to data processing technical field, including the following steps, to electronic prescription data is carried out semantic entity extraction, obtain prescription sensitive data, and prescription sensitive data is carried out risk classification mark, obtain sensitive feature label;Prescription sensitive data is carried out random difference disturbance calculation based on sensitive feature label, obtain disturbance numerical sequence;Based on prescription sensitive data, disturbance numerical sequence is carried out feature cross and non-linear mapping, obtain confused prescription data;Confused prescription data is carried out node comparison based on pre-set drug knowledge graph, obtain graph matching node;Confused prescription data is carried out risk assessment and numerical update based on graph matching node, obtain target prescription data, it solves how to protect the technical problem of the premise of prescription data privacy, guarantee the availability of data to support risk assessment and knowledge graph association as main problem.

The invention relates to the field of data visualization, in particular to a scatter diagram visualization task-oriented data sampling quality evaluation method and system. The method comprises the following steps: giving a high-dimensional data set, and generating a high-dimensional data subset by using a data sampling method; obtaining a low-dimensional data subset according to the high-dimensional data subset; randomly extracting clusters of the high-dimensional data set to obtain high-dimensional space sub-clusters; obtaining a low-dimensional space sub-cluster according to the high-dimensional space sub-cluster; measuring the difference between the high-dimensional space sub-cluster and the low-dimensional space sub-cluster to obtain the difference between different dimensional space sub-cluster pairs; obtaining a global error according to the difference of the sub-cluster pairs in the different dimension spaces; and evaluating the sampling quality of the high-dimensional data through the global error. According to the method, by comparing the sub-clustering differences of different dimension spaces and measuring the retention conditions of different sampling methods after data projection, the authenticity of the high-dimensional data in the projection scatter diagram is effectively evaluated.

This invention relates to the field of polishing equipment technology, and discloses a multi-faceted polishing fixture for watch cases, including a processing box. A silicone mesh plate is located in the center of the inner side of the processing box, and a placement seat is provided on the silicone mesh plate. Multiple processing chambers for individually processing the watch case are equidistantly arranged on the placement seat. By adding and setting a front-end processing mechanism, which uses alkaline cleaning water immersion combined with ultrasonic vibration and a circulating filtration structure, various oil stains and impurities such as cutting fluid and release agents remaining on the surface and crevices of the watch case can be thoroughly removed, eliminating polishing slippage and surface dulling caused by oil residue. Secondly, relying on constant-temperature liquid immersion, the thin-walled watch case is heated evenly throughout, thoroughly and evenly releasing residual metal stress from previous processing, avoiding subsequent polishing deformation caused by uneven stress release. Simultaneously, it optimizes the polishing process, reduces grinding head vibration, and eliminates wavy lines and light / dark layer defects on the watch case surface.

The invention discloses a coronavirus appearance imitating hyperelastic memory alloy rod triggering type spherical robot. The robot is mainly composed of a rod end contact, a hyperelastic memory alloy rod, a tough wire, a rod sleeve, a spherical shell, a micro camera, a hexagonal connecting prism, a straight-through connector, a take-up and pay-off device, a dodecahedron inner core, a control panel and a nine-axis attitude sensor. The take-up and pay-off device drives a winding reel to rotate through a motor so as to take up the tough wire, an elastic rod on the outer surface of the spherical robot deforms, then the tough wire is rapidly released, the bent elastic rod rebounds to provide power for movement of the robot, meanwhile, the take-up and pay-off device and the elastic rod reset, and continuous movement of the robot is guaranteed. The bending degree of the elastic rod can be controlled by changing the position of the knot on the toughness line, and the ejection period is controlled by the control system. The robot is unique in structure, novel in principle, composite in function, high in man-machine interaction and sensing capacity and high in movement flexibility and stability, and has important theoretical significance and practical value for research of spherical robots.

The present application discloses an image migration method, an image migration device, an image migration equipment, a storage medium and a computer program product, and relates to the technical field of computer vision. In the present application, a fine-grained image migration method based on a diffusion model is proposed. By performing semantic matching and appearance migration in the pixel space of the diffusion model, the detail consistency between the original image and the target image is effectively maintained, and detail loss is avoided, thereby improving the image migration accuracy; through the deviation correction method of the latent space based on feature offset processing, it is ensured that the structure and semantic features of the image are effectively retained during the migration process, achieving a high-fidelity image migration effect, and enhancing structural integrity and information fidelity.

The application discloses a preparation method of enteric sustained-release defensin mesoporous silica nanoparticles. The enteric sustained-release defensin mesoporous silica nanoparticles prepared by the method have good defensin loading capacity, good responsiveness to trypsin and good enteric targeting and sustained-release defensin performance.

The invention relates to the technical field of protein peptide films and preparation methods thereof, and discloses a muscle fatigue relieving protein peptide film and a preparation method thereof. Comprising the following components in percentage by weight: 10%-20% of polyvinyl alcohol, 5%-10% of propylene glycol, 2%-5% of butanediol, 1%-3% of glycerol, 2%-5% of polysorbate-80, 0.5%-2% of ginger root extract, 0.1%-1% of betaine, 1%-3% of polyvinylpyrrolidone, 0.5%-2% of phenoxyethanol, 0.1%-0.5% of menthol, 0.1%-0.5% of essence, 1%-3% of acrylic copolymer, 0.1%-0.5% of borneol and the balance of water. The invention discloses a muscle fatigue relieving protein peptide membrane which comprises the following components in percentage by weight: 0.5%-2% of hydrolyzed conchiolin protein, 0.1%-1% of common wheat peptide, 1%-4% of pearl powder, 0.1%-1% of ethylhexylglycerin and the balance of water, the muscle fatigue relieving protein peptide membrane is prepared by adopting a freezing solidification method, and the activity and the structure of effective components and protein can be better reserved, so that a more efficient relieving effect is provided.

The invention provides antibacterial and insect-proof silk paper for calligraphy and painting and a preparation method of the antibacterial and insect-proof silk paper, and relates to the technical field of papermaking. Comprising the following steps: S1, putting flat silk into warm water, adding lauryl sodium sulfate, urea and Ca (ClO) 2, preserving heat, standing and stirring; then adding NaOH, standing and rubbing, then fishing out the flat silk, soaking and cleaning with water, spreading and drying; s2, soaking the dried flat silk in an antibacterial insect-resistant solution, fishing out and airing, repeatedly soaking and airing for 2-3 times, paving, and drying; s3, soaking the flat silk dried in the step S2 in a whitening and softening solution, and then fishing out, flatly laying and drying; and then spraying antibacterial nanocapsules on one or two surfaces of the silk paper, and drying to obtain the silk paper. The silk paper prepared by the method is high in white cleanliness and beneficial to storage, and has antibacterial and corrosion-resistant properties.

The invention discloses a fiber ceramic-based catalytic filter element for denitration of industrial flue gas and a preparation method of the fiber ceramic-based catalytic filter element, and belongs to the technical field of catalytic filter elements. According to the preparation method, firstly, a chelating agent is introduced in the preparation process of TiO2 sol to improve the dispersity and particle size uniformity of TiO2 nanoparticles, the chelating agent can effectively adjust the hydrolysis rate of butyl titanate by means of the strong coordination acting force of the chelating agent and titanium ions, and high-dispersity and small-particle-size TiO2 sol is constructed; then, the fiber ceramic base material is immersed in the TiO2 sol, a firm TiO2 coating is formed after calcination, the firm TiO2 coating serves as a carrier with a high specific surface area, and the binding force between the firm TiO2 coating and the base material is enhanced; the preparation method comprises the following steps: firstly, preparing a TiO2 coating, then dipping a solution containing vanadium and tungsten precursors onto the composite carrier, and calcining to form a main active component V2O5 and a cocatalyst WO3 which are highly dispersed on the surface of the TiO2 coating to form selective catalytic reduction active sites, thereby finally obtaining the fiber ceramic-based catalytic filter element which is good in blocking resistance, water-resistant, sulfur-resistant and high-temperature-resistant and can be used for industrial flue gas denitration.

This utility model belongs to the field of UAV power motor technology, and discloses an external rotor structure, a brushless motor, and a UAV. The external rotor structure is composed of a shaft, a fan, a housing, a cage, and magnets. The cage is ring-shaped and fixed inside the housing, with multiple protrusions extending downwards on its lower side to hold the magnets in place. The fan has a top plate on its upper side and fan blades on its lower side. The top plate of the fan is fixed to the top surface of the housing, and the shaft is fixed inside the housing via a shaft mounting part. This external rotor structure achieves the installation of the shaft and magnets through the assembly structure of the fan, housing, and cage. Furthermore, the structure of the fan, housing, and cage is relatively simple, allowing the cage and fan to be manufactured using injection molding, and the housing to be manufactured using deep drawing, effectively reducing manufacturing costs and improving the production efficiency of the UAV. At the same time, the fan structure is retained to ensure the motor's heat dissipation performance.

The present application provides a kind of sparse gradient enhanced edge preserving image smoothing method, comprising: introducing structure fidelity term on the basis of existing global optimization model containing data fidelity term, in structure fidelity term, the gradient of input image is preprocessed using the way of combining mapping function and bilateral filtering;And introduce sparse gradient enhancement term on the basis of structure fidelity term, in sparse gradient enhancement term, L2 norm and L1 norm are used to constrain the gradient of output image to enhance sparsity, L1 norm is iteratively solved by combining subgradient method, fast Fourier transform and alternating direction multiplier method, or L p norm is used to constrain the gradient of output image, and L p Norm is converted to L1 norm for solving by iterative reweighting method, and preconditioned conjugate gradient method is used to improve calculation efficiency in solving process.The present application can retain complete semantic information while showing sparse smoothing effect when processing simple and complex non-texture images and texture images.

The invention belongs to the technical field of automobile manufacturing, and particularly relates to a luggage rack device carrying an unmanned aerial vehicle and a front mounting method. Comprising a platform baggage holder, an unmanned aerial vehicle parking apron is arranged in the middle of the platform baggage holder, first baggage holders are arranged on the two sides of the platform baggage holder respectively, and a wind blocking frame is arranged at one end of the platform baggage holder; two rows of first mounting holes are reserved in the mounting positions of the two first luggage racks on the roof; the first luggage rack comprises a group of bases and connecting rods; the top of the base is fixedly connected with the connecting rod, a first bolt is installed in the base, and the first bolt penetrates through the first installation hole to be fixed to a car roof; assembly line assembly of the automobile luggage rack in an automobile factory is achieved.

The application relates to the technical field of aqueous zinc ion batteries, and discloses a green preparation process of a positive electrode material of an aqueous zinc ion battery. The process realizes resource utilization by recovering a manganese source from waste batteries and extracting a vanadium source from vanadium slag. The process realizes carbon-coated, pre-intercalation and nitrogen-doped synergistic optimization by adopting a green complexing agent to replace a toxic chelating agent, and by integrating in-situ doping, carbon compounding and gelation procedures under low-temperature water bath conditions, combining ultrasonic-assisted low-temperature aging and 400-420 DEG C low-temperature carbonization, so that the total energy consumption of the preparation process is significantly reduced compared with a traditional high-temperature process. Finally, the finished product is obtained through ball milling mechanical activation and centrifugal washing, so that the whole process is free of strong acid, strong alkali and toxic waste liquid, the yield is greatly increased, and the positive electrode material prepared through the process has a hierarchical porous structure, a high specific surface area and a nanoscale particle size.

The invention discloses a gamma-ray energy spectrum data processing method and device, equipment and a medium, and belongs to the technical field of element analysis. The method comprises the following steps: acquiring original energy spectrum data; according to the channel address information of each data in the original energy spectrum data, carrying out dimension expansion on the original energy spectrum data to obtain two-dimensional energy spectrum data; performing position compensation on the two-dimensional energy spectrum data according to the position information of each element in the two-dimensional energy spectrum data to obtain target energy spectrum data; and processing the target energy spectrum data through a self-attention network model to obtain an element analysis result of the tested substance. According to the target energy spectrum data in the scheme, the structure of the energy spectrum data can be effectively reserved, data information is enriched, the influence of spectrum drift on system analysis is reduced, and the accuracy of gamma-ray energy spectrum data analysis is improved.

The invention relates to a functional decellularized tissue engineering tracheal graft compounded with a cervical latissimus flap lining, and belongs to the technical field of tissue engineering and regenerative medicine. The invention provides a functional decellularized tissue engineering tracheal graft compounded with a cervical latissimus flap lining, the graft comprises a cervical latissimus flap, a banded muscle and a decellularized tracheal stent, the cervical latissimus flap lining is arranged on the decellularized tracheal stent, the subcutaneous tissue side of the cervical latissimus flap is attached to the inner wall of the decellularized tracheal stent, and the banded muscle lining is arranged on the inner wall of the decellularized tracheal stent. The banded muscle wraps the outer side of the decellularized tracheal stent. The decellularized tracheal stent used by the graft is perforated at multiple points, is lined with the latissimus latipes flap and is externally covered with the banded muscle, so that the advantages of an autologous flap tissue trachea, allograft tracheal transplantation and a tissue engineering trachea are effectively combined, the structure and the function of an original trachea can be reserved, and the graft has good biomechanical properties and growth potential and is suitable for being used in the field of medical treatment. An immunosuppressive agent does not need to be used, and revascularization and internal and external blood transportation can be quickly realized.

The present application relates to a kind of flame and smoke detection method based on improved YOLO11, comprising: the image of target to be detected is collected, the image of target to be detected is input into improved YOLO11 model, and detection result is obtained;The improved YOLO11 model is obtained using training set training;The training set includes: original target image and flame and smoke label;The improved YOLO11 model includes: replace the conventional down-sampling layer in backbone network by detail-context collaborative down-sampling module, use dynamic double-feature fusion module to reconstruct feature interaction unit in feature fusion network, and use shared regression and asymmetric classification module to replace original unified classification detection head.The present application improves the performance of flame and smoke detection under complex environment.

The invention discloses a springback type composite sheet and a preparation method thereof, and belongs to the technical field of composite sheets. The sheet comprises an inner layer, a springback layer, a blocking layer and an outer layer which are sequentially arranged in a stacked mode. The base material of the rebound layer is polyester or polyamide, the tensile strength of the rebound layer is limited to be larger than or equal to 150 MPa, the elongation at break of the rebound layer is larger than or equal to 50%, the thickness of the rebound layer is 10-30 microns, meanwhile, the melt flow rate of the polyester under the condition of 275 DEG C / 2.16 kg is controlled to be 5-20 g / 10 min, and / or the melt flow rate of the polyamide under the condition of 235 DEG C / 2.16 kg is controlled to be 5-18 g / 10 min. The springback layer further comprises functional auxiliaries such as maleic anhydride grafted polyethylene and oxazoline grafted polyolefin, and polyester or polyamide is preferably subjected to two-way stretching treatment. The preparation method comprises the following steps: performing corona treatment on each layer of substrate film, sequentially compounding each layer at different temperatures and pressures by adopting a step-by-step dry-method compounding process, and finally performing curing treatment. The method is used for improving the rebound resilience of the composite sheet packaging.