39results about How to "Excellent performance index" patented technology

The invention discloses a Yungang grotto environmental parameter prediction method and system based on an artificial neural network, and relates to the field of neural network prediction algorithms, and the method comprises the steps: collecting and preprocessing external and internal environmental parameters of a grotto through a sensor, and constructing a data sample set through the preprocessed data; constructing a CNN-LSTM network prediction model according to the sample set, establishing hyper-parameters of the prediction model, setting a combination interval of the hyper-parameters to be optimized, and executing a BO algorithm on the hyper-parameters; and selecting a next group of hyper-parameters to carry out a new round of training according to a probability model acquisition function until the number of iterations is reached, and outputting a predicted value. According to the method, the BO-CNN-LSTM model is combined with the Bayesian optimization algorithm, hyper-parameter optimization is remarkably improved, more excellent performance indexes are achieved, the BO-CNN-LSTM model has remarkable advantages in prediction of the internal environment parameters of the Yungang grotto, microclimate changes in the grotto are effectively captured and predicted, an actual environment parameter sample is accurately predicted, and the prediction efficiency is improved. And a comprehensive and accurate prediction result is provided for the internal environment parameters of the Yungang grotto.

The invention discloses an engine flow control method and device, electronic equipment and a storage medium, the method determines a flow control mode of an engine, and the flow control mode comprises a first throttle valve control mode, a second throttle valve control mode, a third throttle valve control mode, a first supercharger control mode and a second supercharger control mode; only the throttle valve is controlled in the first throttle valve control mode, the second throttle valve control mode and the third throttle valve control mode, the front pressure of the throttle valve in each throttle valve control mode is different, and the throttle valve and the supercharger are simultaneously controlled in the first supercharger control mode and the second supercharger control mode. The opening degrees of deflation valves of the superchargers in all the supercharger control modes are different; and the flow of the engine is controlled according to the flow control mode of the engine, so that the engine operates according to the priority that the torque requirement is prior to the air quantity requirement, and the air quantity requirement is prior to the throttle valve requirement and the supercharger requirement, and a better performance index is achieved.

The invention discloses a polyvinylidene fluoride (PVDF) super-hydrophobic membrane and a preparation method thereof.The preparation method comprises the steps that firstly, methyl sodium silicate, perfluorodecyl triethoxysilane (PFDTES) and tetraethoxysilane (TEOS) serve as catalysts / reactants, fluorinated hydrophobic modification is conducted on hydrophilic silicon dioxide (SiO2) nanoparticles, a nanoparticle non-solvent composite spraying synergistic phase inversion method is provided, and the polyvinylidene fluoride (PVDF) super-hydrophobic membrane is prepared. F-SiO2 is successfully introduced into the surface of the membrane, a multi-scale micro-nano structure is formed on the surface of the membrane, and the hydrophobicity and the surface roughness of the membrane are greatly improved. The prepared membrane is applied to vacuum membrane distillation testing, the flux and the salt rejection rate are very excellent, the maximum salt rejection rate reaches 99.99%, the flux is kept at 18.21 kg.m <-2 >. H <-1 > or above, the performance of the super-hydrophobic membrane is superior to that of a base membrane and a membrane prepared through a traditional non-solvent induced phase separation method, and the super-hydrophobic membrane has good anti-pollution performance and is very good in recovery effect after being washed with water.

The invention provides a crane anti-swing control method and device based on an LQR algorithm, and belongs to the technical field of crane control. The crane anti-swing control method based on the LQR algorithm comprises the following steps: S1, obtaining a state-space equation of a crane system; s2, an LQR controller u =-Kx based on the LQR algorithm is designed based on the state-space equation, K is a feedback matrix, a K value of an optimal solution is obtained through calculation based on the Riccati equation and a cost function, and the K value is substituted into the LQR controller to obtain an optimal control variable u through calculation; and S3, substituting the optimal control variable u into the state-space equation so as to carry out anti-swing control on the crane system. According to the method, a state-space equation of a crane system is established, an LQR controller based on an LQR algorithm is applied to calculate and obtain a K value of an optimal solution, an optimal control variable u is calculated and obtained according to the K value of the optimal solution, the optimal control variable u is substituted into the state-space equation, output of the crane system is influenced, and rapid anti-swing and anti-swing are achieved.

The invention relates to waterborne polyurethane and a preparation method thereof.The method comprises the steps that polyhydric alcohol and isocyanate are subjected to a prepolymerization reaction, and when the content of isocyanate groups of a prepolymer reaches a target value, the prepolymer is diluted to obtain a prepolymerization solution; adding a chain extender into the pre-polymerized solution to carry out chain extension reaction, and dispersing and emulsifying with water after the reaction is finished to obtain waterborne polyurethane; the reaction characteristic index is controlled to be-5lt in the preparation process; slt; r is the molar ratio of the isocyanate group to the hydroxyl group when the raw materials are put, E is the mass fraction of the chain extender in the prepolymer, t is the water adding dispersion time, T is the chain extension reaction temperature, and delta p is the pressure drop rate during water dispersion. According to the method, the problem of coordinated regulation of multiple process parameters is solved, and the waterborne polyurethane product with the dispersion particle size of 130-210 nm can be stably prepared.

The invention relates to an industrial internet data compensation method, which comprises the following steps of: monitoring industrial internet data, performing real-time data anomaly detection by utilizing a machine learning algorithm, and processing at a data source in combination with an edge computing technology, so that delay and bandwidth consumption are reduced; an algorithm for adaptively adjusting a compensation strategy according to data characteristics and historical trends is developed, the compensation accuracy and efficiency are improved, multi-dimensional integrity verification is carried out on data in combination with methods of checksum, hash functions and digital signatures, and more comprehensive safety guarantee is provided; according to the data compensation method provided by the invention, the overall change trend of real data and the accuracy of a single data point can be accurately restored, enough precision is provided, and meanwhile, the method can be applied to a plurality of industrial internet scenes and shows good performance.

The application discloses a C-band tuning-free duplexer and belongs to the technical field of microwave filters. The tuning-free duplexer comprises an upper conductor and a lower conductor, and the upper conductor and the lower conductor are buckled one above the other to form a waveguide cavity. The upper conductor is provided with a combining port in the middle of the top, and the lower conductor is provided with a low-frequency input / output port and a high-frequency input / output port at the bottom. The waveguide cavity from the low-frequency input / output port to the combining port constitutes a low-end filter, and the waveguide cavity from the high-frequency input / output port to the combining port constitutes a high-end filter. The main bodies of the high-end filter and the low-end filter are both a plurality of waveguide resonant cavities arranged along a straight line, the middle positions of each waveguide resonant cavity are provided with cavity loading, and adjacent waveguide resonant cavities are connected through inter-cavity coupling. The tuning-free duplexer adopts a symmetrical structure and a center loading mode, realizes tuning-free assembly, has the characteristics of high power bearing capacity, low transmission loss and excellent signal isolation, and is suitable for a C-band communication system.

The invention provides a two-axis turntable control method for improving ADRC, and solves the problems that in the prior art, in a complex environment, a two-axis servo turntable is easily interfered by uncertain factors such as friction interference, mass imbalance and a time delay phenomenon, and the stable tracking performance of the turntable is interfered; the invention provides a two-axis turntable control method for improving ADRC, and the method comprises the steps: obtaining a state signal of a target axis of a turntable in real time through building a two-axis servo turntable model; establishing an active disturbance rejection controller based on the two-axis servo turntable model, and generating a control signal of the target axis; comprising the steps of optimizing a tracking differentiator based on a particle swarm optimization algorithm, adjusting parameters of an extended state observer by using a radial basis function neural network, establishing feedback connection based on an active disturbance rejection controller model, feeding back and outputting a control signal of a target axis to a two-axis servo turntable model, and improving the stable tracking performance of the two-axis turntable.

The present invention provides a reference source structure optimization method based on multi-population hierarchical assisted evolution, including S1, dividing the module to be evolved and the fixed function module in the circuit structure, and generating the topological structure of the module to be evolved by using the improved tracking coding method; S2, optimizing the topological structure of the circuit of the module to be evolved by using multi-population hierarchical assisted evolution to obtain the optimal topological structure of the module to be evolved; S3, taking the optimal topological structure of the module to be evolved as the optimal individual, transmitting its parameter information to the fixed function module, and using multi-population hierarchical assistance from local optimization to global optimization to obtain the optimal circuit topological structure. The circuit performance parameters generated by the present invention can reach the level of artificially designed analog integrated circuits. The present invention has the advantages of high time efficiency, strong integrated integrity, automatic design of circuit structure, screening and optimization of circuits, and excellent final circuit performance indicators.

The present invention discloses a kit for detecting squamous cell carcinoma antigens, the kit comprising reagent R1, reagent R2, calibrators and quality control products; the reagent R1 comprises: antibody-coated magnetic particles, buffer, electrolyte, surfactant, stabilizer, preservative; the reagent R2 comprises: acridinium ester compound or alkaline phosphatase labeled antibody, buffer, electrolyte, surfactant, stabilizer, preservative. The kit provided by the present invention has a wide linear range of 0.2ng / mL to 70ng / mL, within the linear range, the kit correlation coefficient r≥0.99, and has high precision and stability.

The application discloses a kind of reparameterization and stereoscopic coding brain disease classification method and system, it is related to computer medical image analysis technical field, including: S1.data acquisition step;S2.data processing step;S3.Establish RepBoTNet network model;S4.Establish RepBoTNet-CESA network model;S5.model training step;S6.classification step.The RepBoTNet-CESA network model constructed in the application combines the advantages that CNN network is good at capturing local information and transformer network is good at integrating global information, while obtaining excellent performance indicators, reduces the calculation cost;By constructing RepBoTNet-CESA network model, more rich and effective features can be extracted, and the region of interest is less likely to be lost, and when analyzing the whole brain structure, the accuracy of disease classification can be effectively improved.

The application discloses a bad segment automatic detection method and system of electroencephalogram based on contrast self-supervised learning. The method comprises the following steps: denoising, segmenting and labeling the electroencephalogram data sequence; performing multi-resolution mapping on the electroencephalogram segment, and aggregating the feature vector to capture multi-level features; modeling the time dependence within a single electroencephalogram segment and between continuous multiple electroencephalogram segments, thereby further highlighting the difference between bad segments and normal electroencephalogram segments in dynamic evolution; training a multi-level morphological representation module in a contrast self-supervised manner to fully learn the domain-invariant characteristics of the electroencephalogram segment, and then fine-tuning the model to the bad segment detection task through limited labeled data to alleviate label dependence. The application can effectively distinguish normal electroencephalogram and bad segments by fully representing the potential deep characteristics of the original electroencephalogram signal, and the self-supervised learning method can effectively alleviate the performance degradation of bad segment detection caused by limited labeled data.

The utility model relates to aluminium composite board hot rolling technical field, and disclose an aluminium composite board hot rolling compound device, including outer machine case, the front and rear of outer machine case are thorough, and the inside bottom of outer machine case is installed with a plurality of lower roll from front to back in proper order, and the upper roller is provided in the just above of each lower roll, and the inside top of outer machine case is installed with a plurality of respectively connecting each upper roller's down pressure spare from front to back in proper order, and the down pressure spare is by front and rear down pressure force and gradually increases in proper order, and down pressure spare specifically includes mounting bracket, lifting platform, electric hydraulic cylinder and compression spring, and mounting bracket is as upper roller mounting structure, and electric hydraulic cylinder is installed in the top of outer machine case, and lifting platform is docked in the end of electric hydraulic cylinder piston rod, and compression spring has three corresponding installation in the left and right ends and the center position between mounting bracket and susong house lifting platform. Hot rolling compound device adopts the hot rolling technology of step by step increasing pressure through the innovative design, and effectively improves the deficiency of traditional single pressure hot rolling.

This utility model discloses a two-stage tension control device for yarn in a plying machine, belonging to the field of yarn plying technology. The device includes a yarn feeding frame equipped with a servo tensioner; a tension guide wheel located on one side of the feeding frame, equipped with a tension controller and a tension wheel connected to the controller; a yarn separating disc and a plying machine, sequentially arranged on one side of the tension guide wheel. The servo tensioner controls the feeding tension of each yarn and maintains consistent tension values ​​across all yarns, achieving the first stage of tension control. The tension controller further controls the yarn tension and detects the tension value, achieving the second stage of tension control. The ply yarn obtained through this two-stage tension control exhibits better appearance and superior performance indicators, as well as higher breaking strength and a longer service life.

The invention relates to a method for preparing a perovskite wafer based on physical hot pressing and application thereof. According to the method, physical hot pressing assistance and conductive polymer modification methods are adopted, that is, in the process of preparing the FAPbI3 wafer through a mechanical pressing method, an external heating field and conductive polymer modification are synchronously introduced. And the crystallinity of the wafer is improved by the thermal field with proper temperature, and finally the compact perovskite wafer with high crystallinity is obtained. The wafer obtained by the invention can be used for a high-sensitivity near-infrared (NIR) photoelectric detector, and shows excellent photoelectric properties in a near-infrared light band.

The present application belongs to the field of human-computer interaction, and relates to a human-computer trust real-time measurement method and system based on heart rate variability. The present application performs principal component analysis on multiple time domain, frequency domain and nonlinear heart rate variability characteristics, and constructs a human-computer trust real-time measurement model on this basis; in application, user electrocardio signals are collected, heart rate variability characteristics are extracted from the user electrocardio signals; the heart rate variability characteristics are input into a load matrix, and a principal component matrix is calculated according to the load matrix; the principal component matrix is input into the human-computer trust real-time measurement model, and human-computer trust real-time measurement results are obtained. The present application is based on user heart rate variability characteristics, can realize real-time measurement of human-computer trust, and overcomes defects in measurement cost, accuracy, stability and anti-interference.

The application discloses an interactive integrated image restoration and fusion method and device, and the method comprises the following steps: constructing an interactive restoration and fusion module based on a multi-modal feature injection module, which is used for injecting image information of an infrared mode into a network with a pre-trained latent diffusion model as a backbone, so as to realize integrated interactive multi-modal image restoration and fusion; and constructing a fusion image structure restoration module, which is used for refining the structure and details of the restoration and fusion result by using original image information in the iterative denoising process of the latent diffusion model. The device comprises a processor and the processor. The application solves the problem of structure and detail loss caused by latent space fusion, so as to generate a fusion image with richer information and higher visual quality.

The present application relates to the field of powder metallurgy, and particularly relates to a preparation method of a perforating charge liner, which comprises the following steps: preparing iron-coated tungsten powder by using iron pentacarbonyl and tungsten powder, putting the iron-coated tungsten powder into a prepared copper salt reaction solution, obtaining copper-coated tungsten composite powder from the copper salt reaction solution with the iron-coated tungsten powder, reducing the copper-coated tungsten composite powder, mixing the reduced copper-coated tungsten composite powder with graphite and machine oil to obtain mixed materials, and spinning and pressing the mixed materials to form the liner. The technical scheme is based on the displacement principle of iron and copper, and the copper-coated tungsten powder is prepared on the basis of the iron-coated tungsten powder. After drying and reduction, the finally obtained copper-coated tungsten composite powder has excellent performance indexes, the particle size distribution of the copper-coated tungsten powder is reasonable, and the loose bulk density can reach 5.9 g / cm 3 The powder body has good flowability, good powder uniformity and good formability.

The present application relates to the field of computer vision language and image recognition, and particularly relates to a semantic description and question-answering system establishment method and system for remote sensing disaster detection, which generates text language description capable of accurately responding to task requirements image under the premise of adding text constraints by using image features, and establishes a mapping relationship between the pixel-level segmentation result and the question-answering system, and extracts high-level semantic information, and establishes a question-answering system, which can accurately output answers to disaster inquiry questions. The present application can complete three sub-tasks of semantic segmentation, sentence description and question-answering system by using a set of network models, thereby saving computer memory space and improving response speed, and providing technical support for improving the automation, intelligent level and rapid response capability of the remote sensing disaster detection system.

The invention relates to the technical field of heat treatment, and particularly discloses a heat treatment method for improving the obdurability of a ZL205A alloy, which comprises the following steps: step 1, pretreatment: heating the ZL205A alloy to 320-350 DEG C, preserving heat for 1.5-2.5 hours, and then slowly cooling to room temperature at a rate of 10 DEG C / min to reduce the residual stress in the alloy and improve the effect of subsequent heat treatment; step 2, solution treatment; step 3, intermediate annealing; step 4, primary aging treatment; step 5, secondary aging treatment; and 6, subzero treatment is conducted. By means of the innovative heat treatment technology, the performance of the ZL205A aluminum alloy is improved, the application range of the ZL205A aluminum alloy is expanded, high-quality and reliable material selection is provided for users, and technology progress and industry development are promoted.

The present invention belongs to the technical field of petrochemical industry, and discloses a road asphalt and a preparation method thereof. The road asphalt of the present invention comprises the following components by weight: 60-70 parts of vacuum residue oil, 25-30 parts of propane deoiled asphalt, and 6-10 parts of furfural refined extracted oil. The road asphalt of the present invention meets the requirements of Class A and Class B road asphalt with a grade of 70 or 90 specified in the "Technical Specifications for Highway Asphalt Pavement Construction of the Ministry of Transport" (JTG-F40 2004). Compared with the asphalt prepared by blending the same raw materials with similar performance indicators, the amount of extracted oil used in the present invention is less than the currently used extracted oil, which can reduce the amount of extracted oil. Under the same amount of extracted oil, the performance index of the asphalt sample blended with the extracted oil is better than that of the currently used asphalt sample blended with the extracted oil, which can improve the quality of the asphalt product.

The present application provides a combined antenna and an intelligent parking management system, wherein the combined antenna comprises an antenna housing, a WIFI omnidirectional antenna, a GPS / BDS active antenna, and a 4G omnidirectional antenna; the antenna housing is provided with an antenna outlet hole and a mounting structure; the WIFI omnidirectional antenna, the GPS / BDS active antenna, and the 4G omnidirectional antenna all comprise a circuit board, a cable, and a connector; the inner conductor at one end of the cable is electrically connected to the feed connection of the circuit board, the outer conductor is electrically connected to the ground connection of the circuit board, and the other end of the cable is electrically connected to the connector.

The invention discloses a method for graded utilization of all components of bagasse based on lactic acid, and belongs to the technical field of bio-refinery. The method comprises the following steps: hydrolyzing bagasse in a dilute lactic acid solution to obtain a filter residue I and a filtrate I, and concentrating and drying the filtrate I to obtain xylooligosaccharide; then the filter residues I are pretreated with a high-concentration lactic acid solution, filtrate II and filter residues II are obtained, and lignin nanoparticles are recycled from the obtained filtrate II through an anti-solvent precipitation method; and finally, the filter residue II is subjected to a bleaching pulping process to obtain the dissolving pulp. The lactic acid grading method is simple in operation process, has high economic feasibility and environmental friendliness, can recycle lactic acid, and is suitable for green grading and efficient conversion of large-scale biomass.

The application discloses a gas shield solid wire rod and welding wire for improving full-position welding arc stability, which contains Fe and inevitable impurity elements, and the following chemical elements with mass percentage: C: 0.05-0.12%; Si: 0.7-1.4%; Mn: 1.0-1.9%; S: 0.008-0.02%; Ti: 0.08-0.19%; Al: 0.01-0.08%; Zr: 0.01-0.06%; Ni: 0.1-0.8%; Mo: 0.09-0.25%; Y: 0.02-0.07%; O: 0.003-0.008%. The welding wire can realize uniform distribution and spreading of the bead surface layer slag to both sides of the weld and self-stripping after welding, and avoids the problem of arc instability caused by a large amount of slag gathering in the center of the weld.

The application provides a lithium iron phosphate positive electrode material and a preparation method and application thereof, and the preparation method comprises the following steps: (1) mixing a vanadium source, cellulose nanofiber, graphene oxide dispersion liquid and a reducing agent, heating and reacting to obtain a composite hydrogel, drying the composite hydrogel into a composite aerogel, and then performing sintering treatment on the composite aerogel to obtain a precursor material; (2) mixing the precursor material, an iron source, a phosphorus source, a lithium source and a solvent after pretreatment of the precursor material, and performing heat treatment to obtain a lithium iron phosphate precursor; and (3) performing calcination treatment on the lithium iron phosphate precursor to obtain the lithium iron phosphate positive electrode material. The application constructs a porous skeleton structure of nanofiber and aerogel and a synergistic effect of vanadium element doping, so that the diffusion rate of lithium ions and electrolyte can be improved, the electrical conductivity of the lithium iron phosphate positive electrode material can be improved, and the overall electrochemical performance of the lithium battery can be improved.

The present invention relates to a thermoelectric material having a matrix represented by the compositional formula A2B3, in which A is one or more elements selected from the group consisting of Bi and Sb, and B is one or more elements selected from the group consisting of Te, Se and S. Oxide particles are deposited inside crystal grains of the matrix and / or at the boundary of the crystal grains of the matrix. The present invention relates to: a metal oxide containing one or more elements selected from the group C containing Zn, Nb, and Al; and telluride particles containing one or more elements selected from group C, the oxide particles having a long diameter of 1 nm to 1000 nm, the oxide particles having a short diameter of 1 nm to 500 nm, the telluride particles having a long diameter of 0.4 [mu] m to 40 [mu] m, and the telluride particles having a short diameter of 0.4 [mu] m to 20 [mu] m.

The invention discloses a rotating speed analysis method based on a skeletal muscle microcosmic bionic multi-stage series rolling bearing, and relates to the technical field of mechanical transmission, and the method comprises the steps: dividing a three-layer series rolling bearing into two double-layer rolling bearings, the two double-layer rolling bearings are respectively a first double-layer rolling bearing formed by combining a first-stage bearing and a second-stage bearing and a second double-layer rolling bearing formed by combining the second-stage bearing and a third-stage bearing; the revolution speeds of the inner ring rolling bodies and the outer ring rolling bodies of the two double-layer rolling bearings and the relative speeds relative to respective middle rings are calculated; according to the mechanical principle of the rolling bearings, moment balance equations of the two double-layer rolling bearings are constructed and solved, and the rotating speed distribution relational expression of the two double-layer rolling bearings is obtained. By means of the method, analysis of the rotating speed relation and the distribution rule between all stages of bearings of the three-layer series rolling bearing is achieved.

The invention discloses an integrated processing system for full life cycle review of a track signal system, and the system comprises a database platform which is used for carrying out the unified archiving and use management of data in output objects of all departments in a life cycle stage; the operation module is used for establishing a review form, designing internal and external review emphasized items, covering a complete life cycle of the item, reviewing an output object and obtaining review feature data; the test module is used for testing test data in output objects of all departments in the life cycle stage, archiving and analyzing obtained test results, and designing and reviewing test cases; and the statistical comparison module is used for counting the review feature data and the test result, and comparing the review feature data and comparing the review feature data with the test result. The invention further discloses an integrated processing method for full life cycle review of the track signal system. Defect prediction and prevention in the engineering development and implementation process are achieved.

The present application relates to the technical field of electrolytic aluminum production, and discloses a kind of hanging chain online type anode steel claw robot automatic welding process.The present application is by adding welding work station in existing hanging chain conveying system, integrates flame cutting, robot feeding and automatic welding and flux recovery function, realize the on-line repair welding of anode steel claw;The present application adopts robot automatic feeding and full section welding technology, cancels the transfer link of traditional offline welding, greatly improves operation efficiency, welding quality and safety;The present application solves the pain points of the existing offline manual welding, such as high labor intensity, low efficiency, high cost and high safety risk, and can provide key support for cost reduction and efficiency improvement in the process of electrolytic aluminum production.

The invention discloses a wireless signal intensity intelligent multi-step prediction method based on WOA-CNN-GRU, and relates to the technical field of wireless communication. The method comprises the following steps: firstly, constructing a CNN-GRU wireless signal strength multi-step prediction model, then searching optimal hyper-parameters of the CNN-GRU wireless signal strength multi-step prediction model in various application scenes through a whale optimization algorithm WOA, and constructing a WOA-CNN-GRU wireless signal strength multi-step prediction model according to the optimal hyper-parameters. The WOA-CNN-GRU wireless signal intensity multi-step prediction model is trained and verified, and finally the WOA-CNN-GRU wireless signal intensity multi-step prediction model is analyzed and verified in different application scenes. The WOA-CNN-GRU wireless signal strength multi-step prediction model can be rapidly converged in the training process, the rationality of the optimal hyper-parameter is verified, the prediction performance of the model is visually evaluated, and the WOA-CNN-GRU wireless signal strength multi-step prediction model has good prediction performance in different scenes and has good superiority in prediction effect and performance index.