25results about How to "Reliable assessment" patented technology

The invention relates to the technical field of intelligent evaluation and early warning methods, in particular to a nuclear radiation dose space distribution intelligent evaluation and early warning method and system, and the method comprises the following steps: obtaining multi-source monitoring data which comprises gamma radiation dose, alpha radiation dose and beta radiation dose measuring instrument data; performing fusion and enhancement processing on the multi-source monitoring data to obtain an enhanced radiation monitoring signal; based on the enhanced radiation monitoring signal, high-precision prediction of nuclear radiation dose spatial distribution is carried out through a deep probabilistic neural network model; according to the high-precision prediction result, in combination with a nuclear accident severity level standard, a radiation alert evaluation result and early warning information are generated, short-term radiation fluctuation can be captured, a long-term change trend can be identified, and the understanding ability of the system to a complex radiation field is greatly improved.

The invention discloses a method for evaluating the quality of a metal part, which comprises the following steps of: determining the laser type according to the characteristics of the metal part, obtaining various laser parameters for evaluating the quality of the metal part through an experimental method, and performing laser irradiation by adopting the accurately controlled laser parameters. In combination with real-time monitoring and regulation of instruments such as a power meter, a spectrograph, a roughmeter and an optical microscope, a laser parameter-grain boundary definition data set is formed, and finally a quality evaluation model is established to realize accurate evaluation of the quality of the metal parts. According to the method, the quality of the metal parts can be evaluated quickly and economically.

The invention discloses a model library-based spaceflight radio frequency signal quality multi-domain evaluation and compensation method, and belongs to the technical field of wireless communication. The implementation method comprises the steps of determining signal system parameters based on various CCSDS standards and a spaceflight protocol system, extracting related parameters of spaceflight standards in a time-frequency domain, generating standard time-frequency domain radio frequency signals, converting the standard time-frequency domain radio frequency signals into a related domain, a modulation domain, an energy domain and a polarization domain, and establishing spaceflight radio frequency signal sub-model libraries of the domains; obtaining a time-frequency domain measured signal through a receiver, integrating time domain information and frequency domain information, and constructing a time-frequency domain sub-evaluation model; constructing a multi-domain comprehensive evaluation model by adopting a parallel data transmission mode and a weight data processing method; calculating the weight of the evaluation result of each domain through an entropy weight method, and obtaining a comprehensive quality evaluation result of the spacecraft radio frequency signal; and based on the distortion coefficient, a robust signal equalization algorithm is adopted to process the signal, the influence of the distortion effect on the signal quality is compensated, and the robustness and the anti-interference capability of signal transmission are improved.

The invention discloses a listed company risk assessment method based on cross validation and Bayesian optimization, and the method comprises the following steps: 1, obtaining the comprehensive factor data of a listed company, carrying out the dimension reduction of the factor data through employing a principal component analysis method, obtaining a principal component factor, carrying out the effectiveness verification of the principal component factor through an IC and IR analysis method, and carrying out the calculation of the risk of the listed company; selecting a plurality of principal component factors as input features; 2, on the basis of the multi-factor model, constructing an ensemble learning index enhancement model by taking a decision tree and an AdaBoost algorithm as cores; 3, performing system optimization on parameters of the ensemble learning index enhancement model by adopting cross validation and a Bayesian method, and finally determining an optimal parameter combination to obtain a trained ensemble learning index enhancement model; and 4, evaluating the risk of the listed company by using the trained integrated learning index enhancement model. According to the method, the calculation resource consumption of the model can be reduced, the calculation efficiency is improved, and the over-fitting risk of the model can be reduced.

The invention relates to the technical field of modifiers, in particular to a plant shell powder modifier and a preparation method thereof.The preparation method includes the steps that walnut shell powder, phenolic compounds and amine compounds are added into a stirrer with a temperature control jacket, stirred to be uniform and dried in vacuum, and performance characterization parameters of the plant shell powder modifier are calculated to obtain the plant shell powder modifier. According to the method, the phenolic compound and the amine compound are added into the walnut shell powder to modify the walnut shell powder, the compatibility between the modified plant shell powder modifier and rubber is improved, the dispersing performance is improved, the process is simple, the cost is low, and the method is suitable for industrial production. The performance of the plant shell powder modifier and the performance of a rubber product prepared by adding the plant shell powder modifier are evaluated, and whether the performance of the plant shell powder modifier meets the standard or not can be reliably evaluated.

The invention relates to a circuit breaker operation state online monitoring device and method based on distribution automation, the device comprises a sensor and conditioning circuit, an A / D conversion and micro-processing module and a processor, the sensor and conditioning circuit comprises a sensor and a signal conditioning circuit connected with the output end of the sensor; the A / D conversion and micro-processing module comprises an analog-to-digital conversion module and a micro-processing module which are connected with the output end of the signal conditioning circuit; the sensors comprise a displacement sensor, an acceleration sensor, a Hall current sensor and a pressure sensor; the system has the advantages of efficient online monitoring, remote online monitoring, accurate and reliable evaluation and high precision.

The invention relates to the technical field of CO2 burying and storing amount calculation, in particular to an exhausted condensate gas reservoir CO2 structure burying and storing amount calculation method and device, electronic equipment, a storage medium and a computer product. The method comprises the following steps: constructing a depleted condensate gas reservoir CO2 buried substance balance equation; deducing the depleted condensate gas reservoir CO2 burying material balance equation, and constructing a depleted condensate gas reservoir CO2 structure burying amount calculation model; based on the depleted condensate gas reservoir CO2 structure burying stock calculation model, the depleted condensate gas reservoir CO2 structure burying stock is obtained. According to the method, the change of a mixed gas deviation factor after CO2 injection, the change of the saturation degree of residual stratum condensate oil in the CO2 injection process and the influence of deformation of rocks and bound water are considered. The calculation result of an example shows that the CO2 structure burying amount under different burying pressures in the new method is basically matched with the calculation result of a numerical simulation method, and the error is kept within 6.42%.

The application discloses a kind of beam bridge girder static load deflection prediction methods based on improved AVOA-GRNN network, comprising:1, establish vehicle bridge finite element model and add vehicle bridge uncertainty simulation bridge dynamic static load test, collect dynamic static load test data;2, the above data is selected using the characteristic of pearson linear correlation coefficient;3, using dynamic static load experimental data training GRNN neural network model, and construct the parameter of improved African vulture algorithm optimization GRNN, obtain the corresponding smooth factor when average absolute error is minimum;4, the dynamic load test data of prediction set is substituted into improved AVOA-GRNN network model and carries out static load deflection prediction.The application can use beam bridge girder dynamic load test data to predict corresponding static load deflection, so as to effectively solve the problems, such as high cost of predicting beam bridge static load test, great influence on traffic and easily causing damage to bridge structure.

The invention discloses an integrated sediment methanogenesis anaerobic culture bottle, and relates to the field of microorganism culture and detection.The integrated sediment methanogenesis anaerobic culture bottle comprises a bottle body and an integrated bottle cap assembly, the integrated bottle cap assembly comprises a main cap body, a barometer, an integrated guide pipe and a sampling one-way valve, the main cap body is in sealed connection with a bottle opening of the bottle body, and the integrated guide pipe is connected with the sampling one-way valve; the barometer is installed on the main cover body, a pressure sensing probe of the barometer is communicated with a headspace in a bottle, one end of the integrated guide pipe is communicated with the headspace in the bottle, and the other end of the integrated guide pipe penetrates through the main cover body to be connected with the sampling one-way valve. The integrated sediment methanogenesis anaerobic culture bottle provided by the invention has the functions of air pressure monitoring, lossless gas taking and convenient sampling, and the accuracy, convenience and data output quality of a sediment methanogenesis long-term culture experiment are remarkably improved.

This invention discloses a method and apparatus for accurate bridge damage identification and location based on multi-source data fusion. The method includes: performing spatiotemporal registration and data fusion on the time-series data of the bridge's global planar deformation obtained by ground-based synthetic aperture radar and the time-series data of the bridge's point-like three-dimensional deformation obtained by the BeiDou satellite navigation system to obtain a fused deformation field of the entire bridge area; calculating multiple damage characteristic indicators reflecting different deformation physical mechanisms of the bridge based on the fused deformation field, and determining the corresponding preliminary damage level based on the damage judgment threshold of each damage characteristic indicator; using the preliminary damage levels of each damage characteristic indicator as independent evidence sources, performing evidence fusion to resolve indicator conflicts, and determining the bridge damage location and damage level based on the fusion result. This method can effectively improve the accuracy and reliability of bridge damage identification and location, providing a scientific basis for bridge operation and maintenance decisions.

The invention discloses a power distribution network system bearing capacity evaluation method and device, a medium and equipment, and the method comprises the steps: calculating first index values of a plurality of evaluation indexes at the same sampling moment based on a target access scheme of a to-be-accessed new energy system in a target power distribution network system; based on the first index value of each evaluation index, performing fuzzy judgment on the importance degree of any two evaluation indexes, and determining a target subjective weight of each evaluation index; for the evaluation dimension to which each evaluation index belongs, performing fuzzy judgment on the importance degree of any two evaluation dimensions, and determining a target subjective weight of each evaluation dimension; and determining a score of the target access scheme at least based on the target subjective weight of each evaluation index, the target subjective weight of the evaluation dimension to which each evaluation index belongs and the first index value of each evaluation index, so as to obtain an evaluation result of the bearing capacity of the target power distribution network system. According to the invention, the bearing capacity of the power distribution network system can be accurately evaluated.

The present invention relates to the field of data analysis technology, and in particular, to a Taihu Lake cyanobacteria bloom early warning system based on multi-factor analysis and time lag strategy. It includes a data collection and monitoring unit for monitoring and collecting data from various lake areas of Taihu Lake; a data analysis unit determines the key driving factors and time lag response mechanism and lag duration of the cyanobacteria bloom outbreak, and constructs a cyanobacteria bloom outbreak prediction model for different lake areas of Taihu Lake based on the key driving factors and time lag response mechanism of the cyanobacteria bloom outbreak; a risk assessment and early warning unit uses the cyanobacteria bloom characterization parameter results predicted by the cyanobacteria bloom outbreak prediction model to obtain the future cyanobacteria bloom risk. The system can identify the key factors that directly affect the growth of cyanobacteria, and reveal the mechanism of action of those indirect influencing factors. At the same time, it can evaluate the immediate impact of potential variables on the occurrence of cyanobacteria blooms, capture their cumulative effects at different time points, and provide more accurate information for the early warning system.

This invention provides a method and apparatus for evaluating software bill of materials (SBOM) generation tools, relating to the field of computer technology. The method includes: inputting a pre-selected target software project into a SBOM generation tool to be tested, obtaining an original SBOM file output by the tool; performing standardized parsing on the original SBOM file to obtain a corresponding standard SBOM file; performing multi-dimensional evaluation on the standard SBOM file to obtain an evaluation score; the evaluation score includes a field compliance score, a package-level consistency score, and a field-level consistency score; and obtaining an evaluation result for the SBOM generation tool based on the evaluation score. The software bill of materials (SBOM) generation tool evaluation method provided by this invention, by integrating multi-dimensional scores to generate a final evaluation result, achieves an accurate and reliable evaluation of the SBOM generation tool.

The invention relates to the field of paint testing, in particular to a method for testing the cleaning resistance of a marine antifouling coating. According to the test method, experimental equipment is provided, and the experimental equipment comprises a sample plate for coating a coating, a groove body for accommodating the sample plate, a brush disc, a driving device for driving the brush disc to rotate and move up and down, and a control system electrically connected with the driving device. According to the testing method, the cleaning resistance of the antifouling coating is reliably evaluated by matching the steps of artificial seawater soaking experiment, underwater cleaning experiment, coating detection, coating loss grade evaluation and the like. According to the scheme, the cleaning resistance of the anti-fouling coating can be efficiently and reliably evaluated indoors within a short time, scientific data support is provided for research and development of the anti-fouling coating, and the period from laboratory development to practical application of an anti-fouling coating system is shortened.

The utility model discloses an air flotation test device for solid-liquid separation of biogas slurry, which relates to the technical field of anaerobic fermentation product treatment and comprises an air flotation tank, a water collecting tank, a residue collecting tank, a residue scraping mechanism, a reflux pump, a bubble machine and a bubble water releaser, the water collecting tank is communicated with the air flotation tank, and the water collecting tank can receive residue-removed biogas slurry in the air flotation tank; the bubble water releaser is fixedly arranged in the treated biogas slurry in the air flotation tank and can fill bubble water into the treated biogas slurry, a liquid inlet of the reflux pump is communicated with the water collecting tank, a liquid outlet of the reflux pump is communicated with a liquid inlet of the bubble machine, a liquid outlet of the bubble machine is communicated with the bubble water releaser, and the bubble water releaser is communicated with the water collecting tank. The slag collecting tank is fixedly arranged at the top of the inner side wall of the air floatation tank, the slag scraping mechanism is arranged above the air floatation tank, and the slag scraping mechanism can scrape biogas residues on the liquid level of treated biogas slurry in the air floatation tank into the slag collecting tank; according to the utility model, reliable evaluation and pre-estimation can be provided for the actual removal effect of the biogas residue in the biogas slurry doped with the biogas residue by the air flotation equipment.

The application provides a multifunctional testing device for simulating a real use scene of a paper diaper, and relates to the technical field of paper diaper performance detection. The multifunctional testing device comprises a base, a large arm connected to the base, a first rotating component arranged on the large arm, a small arm rotatably connected to the large arm through the first rotating component, a turning flange connected to the small arm, a second rotating component arranged on the turning flange, a baby posture simulation model connected to the output end of the second rotating component, a liquid simulation unit in communication with the baby posture simulation model through a liquid pipeline, a temperature control unit connected to the liquid simulation unit, a gas simulation unit arranged in the baby posture simulation model and used for outputting gas, a sensing unit arranged on the surface and / or inside of the baby posture simulation model, and a control unit electrically connected to the first rotating component, the second rotating component, the liquid simulation unit, the temperature control unit, the gas simulation unit and the sensing unit respectively.

The invention provides an aircraft performance evaluation model construction and evaluation method based on arm angle influence, and the method comprises the steps: building a traditional flight mechanical model based on a power unit model, a control efficiency model, a rigid body dynamic model and a rigid body kinematic model, and obtaining various aerodynamic parameters of an aircraft arm at different angles through CFD simulation; the method comprises the following steps: constructing aerodynamic relation models at different angles, embedding the aerodynamic relation models into a traditional flight mechanical model to obtain a flight mechanical model based on arm angle influence, and constructing a flight performance simulation evaluation model based on a power unit model, a control efficiency model and the aerodynamic relation models. According to the method, more reliable aircraft scheme evaluation and higher-precision flight performance calculation are realized. The construction of a flight performance model fusing the influence of the external parameters of the aircraft also has expansibility, and the flight performance model can be embedded into an influence model of other appearance parameters and is used for evaluating the flight performance of multi-rotor aircrafts of different configurations.

This invention relates to the field of power equipment technology, and more particularly to an intelligent monitoring method for the operating status of charging cables. The method includes: conducting a torsion test on a sample of the charging cable to obtain its structural stability; determining the distribution of monitoring points to implement a monitoring strategy for the operating parameters of the charging cable; acquiring fluctuations in current, voltage, and resistance at several monitoring points during operation to determine if the fluctuations are abnormal; determining an anomaly index based on the average of several historical fluctuation data that could cause abnormal charging temperatures; determining a temperature monitoring mode for the charging cable based on the anomaly index and establishing a correlation prediction model for the charging cable temperature; adjusting the distribution of monitoring points based on the historical accuracy of the temperature prediction model; and determining an optimization strategy for the temperature monitoring mode based on the changes in the adjusted accuracy. This invention solves the problem of inaccurate temperature monitoring of charging cables.

This invention proposes a continuous learning method and evaluation method to mitigate the double forgetting of visual language models. The method includes: adding two parallel paths to the backbone network of a pre-trained visual language model—one a task-agnostic expert path and the other a task-related expert group path—to obtain a model based on heterogeneous expert hybridization; training the model using a two-stage training strategy, including: a first stage, freezing the task-related expert group path and training only the task-agnostic expert path, using contrastive learning to solidify the pre-trained general knowledge of the visual language model; a second stage, freezing the task-agnostic expert path and training only the task-related expert group path, using a cross-entropy loss function to learn task-specific knowledge; and an inference stage, dynamically fusing the outputs of the two parallel paths through a hierarchical routing mechanism to achieve collaborative learning of pre-trained knowledge and task-specific knowledge.

A numerical simulation analysis method for the swelling and bursting of pressurized water reactor fuel rod cladding, relating to the field of reactor safety analysis technology, includes: obtaining constant parameters of the fuel rod cladding; establishing and meshing a geometric model; assigning physical property values ​​to each element mesh; calculating the temperature distribution of the fuel rod cladding and determining whether a phase transition has occurred; if a phase transition has occurred, calculating the phase transition process of the cladding material; if the phase transition is complete or has not occurred, calculating the creep and plastic behavior of the cladding material; updating the effective stress and effective strain rate of the cladding material, and then calculating the yield stress of each element mesh; determining whether both the effective strain rate and yield stress have reached the corresponding failure thresholds; if neither has reached the threshold, repeating the calculation; if either reaches the failure threshold, performing a dynamic bursting process calculation of the cladding until the pressure inside and outside the cladding is balanced, and simulating the dynamic bursting process of the cladding; this method addresses the limitations and inaccurate results of traditional bursting analysis.

The application relates to the technical field of medical detection, and particularly discloses a fall prevention control method for inpatients, which comprises the following steps: recording fall risk data of a patient during hospitalization, and lower limb muscle strength data and motor nerve conduction velocity data in daily examination through a data recording module; the compensation of nerve signal transmission delay is realized by correcting the lower limb muscle strength data of the patient in daily examination during hospitalization, so that the corrected lower limb muscle strength data is closer to the real situation of the patient; on the basis, the comprehensive fall risk of the patient is quantitatively analyzed based on the corrected lower limb muscle strength data and the fall risk data of the patient during hospitalization, the risk assessment based on high-quality data is realized, the reliability of the fall risk assessment result of the patient is improved, and reliable data support is provided for subsequent formulation of the fall prevention control method.

This invention discloses a low-cycle fatigue life prediction method applicable to thin-walled complex structures, comprising the following steps: Characteristic simulation component design: Based on the critical distance theory and the stress gradient equivalence principle, a characteristic simulation component with stress distribution equivalent to that of a real thin-walled complex structure is designed; Material constitutive model and fatigue life equation construction: Based on strain-controlled test data of standard smooth specimens, the cyclic stress-strain curve, strain life equation, and SWT life equation of the material are established; Stress-controlled fatigue test of the characteristic simulation component; L-N curve calibration; Life prediction model construction; Model verification and application. This invention, through the technical route of "equivalent substitution of characteristic simulation components + stress-controlled testing + material constitutive data," effectively solves the core technical problems of high cost of existing fatigue tests for thin-walled complex structures, the inability to implement strain-controlled testing, and the difficulty in quantifying stress gradient effects, achieving low-cost and high-precision life assessment.

The invention discloses a multi-sight-distance deep learning track line detection method based on global features, and the method comprises the steps: 1, installing a far-focus camera and a near-focus camera at the head or side surface of a train, obtaining track line images in different scenes in the train operation process, and constructing a data set; 2, in image preprocessing, a Sobel operator is used for calculating gradient energy to generate a focusing degree image, a decision diagram is generated through multi-scale morphological optimization operation, and smooth transition of fused image boundaries is achieved through Gaussian weighted fusion; step 3, constructing an improved ResNet18 backbone network, fusing multi-scale features, combining row selection and structure perception loss, and performing Adam optimization training; and 4, real-time track line detection is carried out. According to the invention, through multi-sight-distance image fusion and global feature extraction, technical support is provided for realizing high-precision and real-time detection of a train track line, automatic train driving, track state monitoring and other key tasks.

A monitoring system for a food preparation system includes a sensor unit having at least one sensor for determining current sensor data of food being loaded or unloaded to or from a food processing chamber of the food preparation system; the processing unit is used for determining current feature data according to the current sensor data; the classification unit is used for determining characteristic data of food in the food processing chamber according to the current characteristic data; and a control unit for controlling at least one actuator adapted to notify or alert a user or to set operating parameters of the food preparation system based on the determined characteristic data of the food present within the food processing chamber.

The invention discloses a baijiu fermentation quality prediction and evaluation method and system, and the method comprises the steps: collecting environmental parameters of a fermented grain fermentation process, and obtaining evaluation parameters of the fermentation quality; constructing a fermentation quality evaluation model, inputting the environmental parameters and the evaluation parameters as sample data into the fermentation quality evaluation model, and training a network model to obtain a trained evaluation model; inputting to-be-measured environmental parameters in the fermented grain fermentation process into the trained evaluation model, and outputting predicted evaluation parameters; and evaluating the fermentation quality by using the predicted evaluation parameters to obtain an evaluation result. According to the method, human interference can be remarkably reduced, evaluation parameters are quickly obtained by using the network model, and reliable and effective evaluation of the fermentation quality is realized.