196results about How to "Avoid blindness" patented technology

The invention discloses a multi-source heterogeneous data fusion processing and intelligent analysis method, device and equipment, and relates to the field of data fusion processing.The method comprises the steps that firstly, data in data sources of corresponding types are collected through different collection strategies; performing data preprocessing on the collected data to obtain standard data in a unified format; performing data fusion on the standard data based on the structural features of the data to obtain a fused data set; and determining a target analysis model according to the data analysis target, and performing data analysis on the fused data set. According to the method, various types of data formats can be processed, multi-source heterogeneous data fusion is realized, and through data semantic understanding and a feature-based fusion algorithm, the accuracy and quality of data fusion are improved, and correct data association is established on the semantic level.

The invention provides a multi-sealing method and system for a high-vacuum die-casting die based on topological optimization, and relates to the technical field of die structures.The multi-sealing method comprises the steps that a sealing structure parameterized model is established, geometric parameters and boundary conditions of a cavity wall face are obtained, an initial design domain is constructed, and grid units are divided; carrying out topological optimization calculation based on a multi-objective function considering contact stress distribution, and iteratively optimizing the relative density of grid cells by adopting an SIMP method; and according to the obtained topological configuration of the sealing structure, multiple sealing structure design is carried out, a three-dimensional entity model is constructed, and the sealing performance is verified through finite element analysis.

The invention relates to the technical field of screen printing, in particular to a PCB screen printing ink layer thickness uniformity control method, system and device and a medium. The method comprises the following steps: firstly, collecting ink layer actual thickness data and screen tension data of a PCB screen printing area, then analyzing the relevance between the two data to obtain an ink layer uniformity analysis result, further determining proper compensation parameters through process compensation analysis, finally dynamically adjusting screen printing pressure, scraper angle and printing speed, bringing screen tension into a control system, and finally, controlling the screen printing uniformity. Compared with the prior art, the method has the advantages that the adaptability and the reliability are higher, and the product yield can be improved.

The invention provides a near-wind-field power transmission line hardware fitting operation state intelligent diagnosis method and system, and relates to the technical field of power transmission line operation monitoring. Comprising the steps of calculating a first influence factor and a second influence factor of a transmission line fitting use state; determining an initial diagnosis threshold of the use state of the power transmission line fitting; calculating a power transmission line hardware fitting use state diagnosis threshold value influence factor, and determining a power transmission line hardware fitting use state diagnosis threshold value; and acquiring a transmission line fitting operation characteristic data set, calculating a fitting operation characteristic evaluation value, and judging whether the transmission line fitting use state is qualified in combination with the transmission line fitting use state diagnosis threshold. According to the method, a comprehensive, dynamic and accurate power transmission line fitting use state diagnosis threshold value with a customized property is determined from the three aspects of environment microclimate, fitting characteristic data and near wind field wind power characteristics of the power transmission line fitting, and more scientific and reasonable fitting maintenance is realized.

The invention discloses a method for improving plant polyploidy induction rate and obtaining polyploidy based on leaf bud primordium cell cycle synchronization. The method comprises the following steps: carrying out pre-differentiation culture on an explant induction material; performing cell cycle synchronization excitation treatment on the leaf bud primordium cells obtained by the pre-differentiation treatment; and performing chromosome doubling treatment on the explant induction material subjected to the cell cycle synchronization excitation treatment. According to the method disclosed by the invention, an EdU staining labeling method and a flow cytometry are used for accurately judging the time for carrying out cell cycle synchronization excitation treatment on leaf bud primordium cells of an induction material, and carrying out synchronization excitation and doubling induction on the induction material in time; the dosage of a cell cycle inhibitor for synchronous excitation treatment is accurate, the treatment opportunity is accurate, the treatment duration is proper, and the polyploidy inductivity of the plant is remarkably improved; the obtained polyploidy plant is good in stability, and the method is high in repeatability.

The invention discloses a method and a system for screening crab cactus varieties. The method comprises the following steps: receiving respective character data information of crab cactus germplasm resources input by a user; the character data information comprises each character and an attribute value corresponding to each character; based on the deployed evaluation model and the character data information, scoring each character of the germplasm resources of the crab cactus to obtain a scoring result; obtaining a weight corresponding to each character based on each layer weight of a sub-target layer, a constraint layer and a standard layer of the evaluation model; and screening good varieties in the germplasm resources of the crab cactus according to the weight and the scoring result to obtain a target germplasm resource of the crab cactus. According to the method, screening blindness is avoided, and the accuracy of screening excellent germplasm resources of the crab cactus is improved.

The invention relates to a vulnerability analysis method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring a first data packet generated based on a network protocol to be analyzed in a cloud network, and analyzing the first data packet to determine a second data packet generated based on an unknown protocol in the first data packet; observing a message header field of the second data packet based on a hidden Markov model, and constructing a state machine model of the unknown protocol according to a plurality of observed states; generating a protocol format description file of the unknown protocol according to the content recorded by the state machine model; and generating a test case according to the protocol format description file, and analyzing vulnerabilities in the unknown protocol based on the test case. By adopting the method, vulnerability analysis of the self-developed proprietary protocol of the cloud computer can be realized, so that the use security of the cloud computer is improved by utilizing the vulnerabilities.

The invention discloses a Fluent-based numerical simulation and experimental design method for shaking of liquid in a tank of a tank truck, and belongs to the technical field of numerical simulation of fluid dynamics (CFD). The method includes the steps that the hole opening position of the wave-proof plate serves as an independent variable, multiple hole opening position schemes are designed, liquid shaking related indexes are determined to serve as dependent variables, a geometric model is established according to the actual structure of a tank truck tank body, a fluid mechanics model and boundary conditions are set, a solver is configured, output parameters and numerical simulation initial values are set, and an experiment is executed. The liquid shaking process of a certain swash plate trepanning scheme is simulated, acting force data, namely shaking index data, between liquid shaking and the inner wall of the tank body is recorded, the advantages and disadvantages of each trepanning position scheme are evaluated based on the shaking index data, and the optimal scheme is determined. According to the method, a real object experiment is replaced by CFD numerical simulation, parameter setting is carried out, the experiment cost and the experiment risk are remarkably reduced, the experiment efficiency is improved, and data support can be provided for industry design.

The invention discloses a port microgrid energy storage and transfer vehicle capacity configuration method and system. The method mainly comprises three aspects: firstly, feature extraction of port electricity load data is realized by a K-means clustering analysis method based on SVD and KL divergence; and establishing a transfer vehicle working model according to the operation characteristics of the port transfer vehicle. And finally, establishing a double-layer optimization model of energy storage and transfer vehicle capacity configuration by taking the minimum operation cost of the port micro-grid as an upper-layer optimization target and the maximum utilization rate of the port new energy as a lower-layer target. The method has the outstanding advantages of being good in optimization effect, environmentally friendly, high in efficiency, high in reliability and the like.

The invention discloses a physical wind tunnel pressure measurement test optimization method based on CFD-AI and a storage medium. The method comprises the following steps: completing wind load measurement point arrangement after segmentation based on a parameterized modeling platform, and completing curved surface partitioning; establishing a CFD numerical wind tunnel calculation model, performing CFD full wind direction angle calculation, and extracting building surface measuring point wind pressure and local shape coefficients corresponding to all wind direction angles; in combination with the local shape coefficient and the three-dimensional building model, performing machine learning clustering analysis on the measuring points to form an optimized measuring point arrangement scheme; curved surface partitions are updated based on an optimized measuring point arrangement scheme and a Thiessen polygon, and a physical wind tunnel test is carried out; and integrating wind load analysis results of the physical wind tunnel and the CFD numerical wind tunnel, marking a wind pressure hyper-standard region, and calculating and outputting an overall shape coefficient in combination with a curved surface partition area and a local shape coefficient. The objective of the invention is to improve the problems of high pressure test cost, too long test data processing time and incapability of achieving engineering practical application of test efficiency and data accuracy in a physical wind tunnel test.

The invention provides a diabetic patient life management method and system in combination with traditional Chinese medicine knowledge, and relates to the field of medical health data processing, the method comprises the following steps: obtaining multiple groups of sample data, the sample data at least comprising personal information of sample patients and diabetic traditional Chinese medicine syndromes, and the personal information of the sample patients at least comprising diabetes index data; based on the multiple groups of sample data, multiple key traditional Chinese medicine syndrome discrimination units are determined, and a diabetes traditional Chinese medicine syndrome diagnosis scale is generated; based on the multiple groups of sample data, determining music types matched with different diabetes mellitus traditional Chinese medicine syndromes; determining the diabetic traditional Chinese medicine syndrome of the current user based on the personal information of the current user and the filling information of the diabetic traditional Chinese medicine syndrome diagnosis scale; based on the diabetic traditional Chinese medicine syndromes of the current user and the music types matched with different diabetic traditional Chinese medicine syndromes, music, traditional Chinese medicine health maintenance skills and traditional Chinese medicine recipes are recommended, and the method has the advantage of improving the quality of life management of diabetic patients.

The invention relates to a regulation and control method and system for mine fireproof doors, a terminal and a medium, and belongs to the technical field of mine fireproofing. The regulation and control method comprises the steps that sensing data sent by sensors around each fireproof door are received; according to the multiple sets of sensing data, whether a fire occurs in the mine or not is judged; if yes, determining a target fireproof door according to the fire spreading area; acquiring personnel position information of workers around the target fireproof door; based on the personnel position information, whether a worker is on a fire spreading path and is located between the target fireproof door and a fire spreading boundary is judged; if yes, the closing degree of the target fireproof door is controlled according to the spreading speed of the fire; if not, the closing degree of the target fireproof door is controlled according to the fire behavior of the fire. The intelligent monitoring management system has the beneficial effect that intelligent monitoring management of the fireproof door can be conveniently realized according to the field environment.

The invention relates to the technical field of oil and gas field yield increase and transformation, in particular to a tight reservoir vertical well group fracturing optimization design method which comprises the following steps: collecting geological data and engineering data of a fracturing target block; a vertical well fracturing crack stress disturbance mathematical model is established, and reservoir disturbance stress distribution is simulated; establishing a crack support crack width attenuation mathematical model, and simulating a change rule of the support crack width along with time; combining engineering data with the stress disturbance mathematical model to determine a well group combination mode and a multi-well fracturing sequence of vertical well group fracturing; and based on the result of the fourth step, the fracturing time interval between the vertical wells in the well group is designed by combining the supporting seam width attenuation mathematical model. According to the method, the problems of well group combination mode, multi-well fracturing sequence, fracturing time interval and the like during tight reservoir vertical well group fracturing construction design are effectively solved, steering extension of fracturing cracks is achieved, the fracturing transformation effect of a reservoir is improved, and therefore the oil and gas yield of a single well is increased.

The invention provides a cooperative path planning method for searching and tracking an underwater target by a multi-USV unmanned cluster, and the method comprises the steps: introducing a pose-control quantity-time to carry out the three-dimensional double-chain coding of a population in an improved genetic algorithm, enabling a control instruction and an accurate execution timestamp to serve as a genetic gene, and enabling the control instruction and the precise execution timestamp to serve as a genetic gene in the crossover and mutation operation, timestamps, control quantities and poses are transmitted synchronously, and it is ensured that offspring individuals can inherit an excellent cooperation mode of a parent; during population initialization, USV is guided to preferentially cover a high-value region through region division and weighted Gaussian distribution, so that blindness caused by random initialization of a traditional genetic algorithm is overcome, and invalid search is avoided; a target for avoiding secondary search is designed in a fitness function, and repeated access to recently searched areas is quantified by introducing a concept of confidence time intervals, so that an algorithm actively explores unexplored water areas, waste of search resources is avoided, and accuracy and planning efficiency of multi-USV collaborative path planning are improved.

The application discloses a sludge biological drying multi-target proteinase regulation method based on bacterial chemotaxis, relates to the technical field of sludge resource disposal, and comprises the following steps: S1, constructing a microfluidic detection system based on the chemotaxis of thermophilic bacteria, and monitoring and quantifying the metabolic preference degree of the thermophilic bacteria to different amino acids in a sludge biological drying process; S2, selecting and proportioning proteinases with a targeted degradation function according to the metabolic preference degree of the thermophilic bacteria; and S3, decomposing refractory proteins into specific amino acids preferred by the thermophilic bacteria through multi-target regulation of the proteinases. The application optimizes the metabolic environment of the thermophilic bacteria to improve the utilization rate of protein organic matter and accelerate the sludge biological drying process.

The invention relates to the technical field of data processing, and particularly provides a manufacturing industry energy-saving and efficiency-increasing scheme generation method, system and equipment and a storage medium, and the method comprises the steps: collecting the operation state data, energy consumption data and real-time working condition data of industrial equipment in real time through an equipment monitoring module; preprocessing the collected data, establishing an energy efficiency reference, calculating a key energy efficiency index based on the energy efficiency reference to judge the energy efficiency state of the equipment, and executing multi-dimensional root cause analysis when the energy efficiency state is abnormal; according to the energy efficiency state and a root cause analysis result, matching and filtering applicable technical schemes from a technical unit library, and performing quantitative evaluation and comprehensive sorting on the technical schemes to generate a preferential transformation scheme list; and an energy efficiency analysis result is fed back to the equipment monitoring module for state early warning, and a customized proposal is generated based on the transformation scheme. According to the invention, the systematization and automation of industrial energy-saving management are realized by constructing a full-link closed loop generated by data perception, intelligent diagnosis and decision.

The application relates to the technical field of teaching instruments, and discloses an interactive teaching instrument and a use method thereof, which comprise a supporting assembly, the top of the supporting assembly is provided with a fixing assembly, the top of the fixing assembly is provided with an adjusting assembly, one side of the adjusting assembly is provided with a display assembly, the display assembly is provided with a light-shielding assembly, the supporting assembly comprises a base, pressure sensors are arranged at the lower ends of the four corners of the base, the fixing assembly comprises a fixing plate, the adjusting assembly comprises a rotating motor arranged at the bottom of the fixing plate, the application can flexibly adjust the angle position, effectively reduce the reflection, avoid affecting the teaching effect, actively remove dust from the display component, improve the display definition, timely intervene when the whole is in an unstable state, improve the stability of the whole, effectively protect the display component when the whole is tilted, and prevent the display component from being damaged.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle target classification matching strike control method and system based on deep learning, and the method comprises the following steps: S1, collecting the original environment data of an unmanned aerial vehicle flight region, carrying out the preprocessing of the original environment data, and generating multi-mode perception data; and S2, inputting the multi-modal sensing data into a pre-constructed deep learning classification network, extracting multi-level depth features of the target through the deep learning classification network, carrying out classification identification on the target based on the multi-level depth features, and outputting target category information and target position information of the target. The multi-modal sensing data is input into the deep learning classification network for target recognition, the multi-modal fusion sensing mode can give full play to the complementary advantages of different sensors, high target recognition accuracy can still be kept in complex environments such as night, low illumination and severe weather, and the adaptive capacity of the system to environment changes is remarkably improved.

This invention relates to the field of ultra-high performance concrete (UHVPC) curing technology, and more particularly to an intelligent temperature-controlled curing method for UHVPC. The method includes the following steps: generating preliminary temperature-controlled curing data for concrete based on UHVPC mix proportion parameters and temperature-controlled curing requirements data; analyzing the distributed temperature field characteristics of the pouring nodes using UHVPC pouring node data to generate distributed temperature field characteristic data for the pouring nodes; analyzing the temperature evolution and hydration state of the pouring node temperature field based on the distributed temperature field characteristic data and the preliminary temperature-controlled curing data to generate temperature evolution and hydration regulation state data; and performing dynamic temperature-controlled curing analysis on the preliminary temperature-controlled curing data to generate dynamic temperature-controlled curing data for the concrete. This invention achieves intelligent temperature-controlled curing by combining the application of UHVPC.

The application relates to a wireless communication same-frequency interference detection method based on a CNN-SVM and a particle swarm optimization, which comprises the following steps: performing short-time Fourier transform on a received baseband signal to generate a log power spectrum time-frequency graph; automatically extracting a deep space feature vector through a convolutional neural network; performing global self-adaptive optimization on a penalty parameter and a kernel parameter of a support vector machine through a particle swarm optimization algorithm; and training the support vector machine with optimal parameters to perform binary classification judgment on a to-be-detected feature. Through a triple coordination mechanism, the application overcomes the problems of fixed parameters, poor robustness and the need for a large amount of labeled data in traditional methods, and realizes high detection probability and low false alarm rate under different signal-to-interference-and-noise ratios and bandwidth conditions.

This application discloses a method for calculating the vibration isolation of ship vibration isolation devices based on isolator type spectrum data, relating to the field of ship vibration isolation design. The method includes: acquiring the type spectrum data and impedance test data of the target isolator; determining the stiffness and damping parameters of the target isolator based on the type spectrum data and impedance test data; constructing a finite element model of the ship vibration isolation device; inputting the stiffness and damping parameters of the target isolator into the finite element model for calculation, and obtaining the vibration isolation calculation results of the target isolator. This method can efficiently utilize isolator type spectrum data to conduct vibration isolation calculation and evaluation of ship vibration isolation devices during the ship design phase, avoiding resonance between the natural frequency of the vibration isolation device and the excitation frequency of the equipment, and improving the vibration isolation effect.

The invention provides a dynamic pricing method for opponent prices and relative sorting based on big data, and the method comprises the following steps: the current selling price of a current product to be priced is known as P0, and the current selling prices of a plurality of known opponent products of the same type (n is greater than or equal to 3) are selected to form the real-time selling price of a group; sorting the selected current product and the products of the same type of the n opponents according to the sequence of the product selling prices from large to small; and according to the relative order of the prices of the current product and the products of the same type of the n opponents and the selling prices, obtaining a dynamic price P'of opponent prices and relative sorting based on the big data. The pricing efficiency of a user can be improved, and the total income of the user is improved.

The invention discloses a strip mine transportation management method and device, electronic equipment and a storage medium, the method and device are applied to the electronic equipment, and specifically, three-dimensional coordinate information and mine car information of at least one mine car are obtained based on a positioning auxiliary system and a communication system arranged in a strip mine; processing the three-dimensional coordinate information based on preset reference information to obtain a real-time running state of the mine car; and displaying the real-time running state and the mine car information to a dispatcher. By displaying the real-time running state and the mine car information to the dispatcher, the dispatcher can master the real-time running state of the mine car in real time, so that the blindness and hysteresis of dispatching command are avoided, and the production efficiency and the economic benefit of the mine can be further improved.

This invention provides a method for assessing the capacity value of wind farm clusters based on the Johnson distribution system. The method comprises the following steps: Step 1: Establishing a wind farm cluster fluctuation model through power output analysis using a first-order Markov chain algorithm; Step 2: Establishing relevant models for different wind farm clusters through time-series power output analysis using the Johnson distribution system; Step 3: Conducting a reliability assessment of the power system based on the given load level and wind farm capacity, according to the power adequacy index; Step 4: Using a bisection method to adjust the load of the wind farm system to search for the reliable capacity of the wind farm cluster. This invention is designed for large-scale wind turbine integration into the power system and can scientifically and accurately assess its capacity value.

The invention discloses a lithology identification method based on a neural network, and the method comprises the steps: obtaining a logging curve, recognizing a missing value in the logging curve, taking the parameter data in the logging curve as sequence data, inputting the sequence data into an established neural network model, carrying out the prediction through the neural network model, obtaining the complementation data corresponding to the missing value, and obtaining the lithology of the logging curve. Filling missing values in the logging curve by using the completion data to obtain a complete logging data set, namely a first data set; based on the first data set, performing equalization processing on lithology classification samples in the first data set to obtain an equalization logging data set, namely a second data set; a whale optimization algorithm is adopted to optimize hyper-parameters of the classification model, target hyper-parameter configuration is obtained, and the classification model is configured; and inputting the second data set into the classification model, and identifying and outputting the lithology category. The method is high in missing value filling precision, excellent in sample equalization effect, remarkable in model performance optimization and high in system practicability.

Aiming at the problems of inaccurate sediment monitoring, extensive sludge discharge control, low dosing accuracy and the like of the traditional sedimentation tank, the invention provides a visual monitoring and model-driven sediment prediction and sludge discharge control method and system for a sedimentation tank. The method comprises the following steps: visual monitoring: collecting images of a sedimentation tank through an underwater camera device, identifying interface characteristics of bottom mud, and constructing a bottom mud thickness distribution thermodynamic diagram in combination with an inverse distance weighted interpolation method; parameter acquisition: acquiring operation parameters such as water inlet flow, raw water turbidity, pH value and the like in real time; model-driven prediction: establishing a BP neural network model coupled with multiple variables, a mud yield model and a multi-dimensional coupled bottom mud distribution prediction model; and intelligent sludge discharge control: generating an optimization instruction of sludge discharge frequency, quantity and area based on a prediction result, and controlling sludge discharge operation. According to the invention, bottom mud monitoring automation and mud discharge control refinement are realized, the precipitation efficiency is improved, and the operation cost is reduced.

The invention discloses a stamping process-oriented defect feedback and digital simulation closed-loop control system and method, and relates to the technical field of closed-loop control. The system comprises a working condition synchronous sensing and feature coding module, a digital simulation prediction module, a defect feedback and decision control module, a process parameter execution module and an online learning and model evolution module. According to the method, multi-source operation data are collected, a working condition feature packet is generated, material parameters are dynamically matched after a formed digital simulation model is input, initial disturbance is injected, and defect prediction parallel to physical stamping is achieved; calculating a prediction confidence coefficient by combining measured data, and generating a precise process adjustment decision by linking defect risk distribution and applying the decision to a next period; and based on actually measured and predicted errors, continuously updating a material parameter library and forming digital simulation model parameters through online learning. According to the method, the problems that traditional stamping simulation and reality are disjointed, and process adjustment is blind are effectively solved, the product defect rate is greatly reduced, and meanwhile the production efficiency and the quality stability are improved.

The invention provides a pesticide residue detection device and a detection method and application thereof.The device comprises a cleaning mechanism, a filtering mechanism, an elution mechanism and a detection module, multiple nucleic acid aptamers are fixed to a filter element, the sequences of the nucleic acid aptamers are optimized, the pesticide fixing and specific capturing capacity is improved, proper cleaning liquid and eluent are screened, and the pesticide residue detection efficiency is improved. And the cleaning and eluting effects of residual pesticides in agricultural products are improved. When the device is used for enriching and detecting pesticide residues, the pesticide residues in the agricultural products can be accurately detected through the detection module only by carrying out nondestructive cleaning, filtering and elution on the agricultural products to obtain a sample solution to be detected, and a test strip or an electrochemical detection part containing a nucleic acid aptamer probe in the detection module can be used for accurately detecting the pesticide residues in the agricultural products. Moreover, qualitative and quantitative detection of residual pesticide can be realized respectively, the structure is simple, the detection is convenient and efficient, and the accuracy of a detection result can be ensured.

The present invention discloses a distribution network closed-loop power regulation analysis method, device, equipment and medium, including: first determining a closed-loop point candidate set and an operable switch candidate set in the distribution network, wherein the switch state of each switch in these candidate sets can be adjusted. Then, constructing an objective function of an optimization algorithm based on preset safety goals and economic goals, iteratively fitting closed-loop alternative schemes through the objective function and the optimization algorithm until the number of iterations reaches a preset iteration number threshold, and obtaining a target closed-loop scheme, thereby achieving the optimal target closed-loop scheme based on safety goals and economic goals among these multiple closed-loop alternative schemes. The present invention is aimed at the processing process of closed-loop power regulation, based on optimization analysis technology, to achieve rapid and effective analysis of a large number of closed-loop alternative schemes, and to provide a preferred scheme therefrom, thereby overcoming the blindness of closed-loop power regulation based solely on operating experience, and the complexity of obtaining closed-loop power regulation laws.

The invention belongs to the technical field of burn wound analysis. According to the skin burn analysis method and system based on contrast agent blood perfusion, firstly, a fluorescence sequence after a contrast agent is injected is obtained, and a preprocessing sequence is generated through area cutting and down-sampling; a fluorescence intensity time curve of each pixel point is extracted, peak time is determined, and statistics is carried out to construct a peak time histogram; performing smooth denoising, extreme value detection and weak peak removal on the histogram, and adaptively selecting a threshold value for distinguishing normal and burnt tissues; generating an initial mask by using the threshold value, and performing connected domain analysis and morphological post-processing to obtain a target burn area mask; and finally, generating a pseudo-color image in combination with peak time. According to the method, the time dynamic characteristic of blood perfusion is fully utilized, the burn area can be accurately segmented and the microcirculation disturbance degree can be visually presented without depending on skin textures or a large amount of training data, and the objectivity and accuracy of burn depth evaluation are remarkably improved.