73results about How to "Comprehensive assessment" patented technology

The invention relates to the technical field of power system assessment, and discloses a power system vulnerability assessment method and system considering extreme weather influence, and the method comprises the steps: building a line fault probability model of a power system in extreme weather to determine the line time-varying fault probability under dynamic weather influence; generating a typical scene through a time sequence relativity matching generative adversarial network model with gradient penalty and Monte Carlo simulation; taking the generated typical scene as input, simulating cascading failure evolution through an alternating current cascading failure model, and outputting a cascading failure evolution path; and based on a fault evolution result, through a spectrogram theory and a Bayesian network, in combination with severity analysis, structural vulnerability evaluation and causal-probability pre-judgment, multi-level vulnerability quantification of the power system is realized, and the problems that single-level evaluation is insufficient and causal association is ignored in the prior art are solved. And the risk assessment precision and the disaster prevention capability of the power system in extreme weather are improved.

The invention discloses a cascading failure-based wind power credible capacity evaluation method and device, and the method comprises the steps: obtaining the topological structure information of a power transmission network frame of a target power system, the conventional attribute information of a conventional unit, and the wind power attribute information of a wind turbine unit, and obtaining the actual power grid operation information of a target region within a preset time period; on the basis of the information, representative scenes of the target power system before, during and after the cascading failure occur are constructed; fault evolution operation simulation is carried out on the target power system in the representative scene before the fault, the representative scene in the fault and the representative scene after the fault, and a power grid state characteristic matrix of the target power system in each representative scene is determined based on simulation results; and based on the power grid state characteristic matrix, determining the wind power credible capacity through alternate iteration by using the upper layer model and the lower layer model.

The application discloses a kind of hardness correlation liver cancer lung premetastatic niche mouse model construction method, it includes the following steps: (1) in vitro enrichment respectively on the low hardness substrate of hardness 6kPa and the high hardness substrate of hardness 16kPa, the condition culture supernatant of mouse liver cancer cell Hepa1-6 that is cultured and grows, respectively named mL-CM and mH-CM;(2) mL-CM and mH-CM are respectively injected into two groups of mice using tail vein injection mode, every 1 day injection 1 time, until the 26th day, during continuous monitoring the recruitment of BMDCs in fresh lung tissue, while with the induction endpoint, i.e. 26th day premetastatic niche mark feature detection includes lung tissue matrix remodeling, immunosuppression, angiogenesis, vascular permeability and inflammation etc..The method has the advantages of short modeling cycle, easy operation, controllable induction condition, can comprehensively and accurately evaluate the common characteristics of liver cancer lung premetastatic niche formation etc..

The invention discloses a self-healing parallel capacitor aging test device and method for an AC power system. The method comprises the following steps: S1, preparation before test; s2, carrying out a first-stage aging test; s3, carrying out a charge-discharge cycle test; s4, performing a second-stage aging test; and S5, detecting after the test. According to the self-healing parallel capacitor aging test device and method for the alternating-current power system, automatic control over the whole test process is achieved, it is guaranteed that test conditions meet the national standard requirement, the influence and closing impact on a power grid in the test process are eliminated, the accuracy and reliability of a test result are improved, and the test efficiency is improved. A standardized method is provided for performance evaluation of the capacitor, and the problems that an existing test device is low in integration and automation degree, poor in test precision, large in power grid influence and insufficient in safety protection are solved.

This application relates to the field of image recognition technology, specifically to a visually assisted method and system for quality inspection of laser engraving on mobile phone buttons, solving the technical problem that the accuracy of laser engraving quality inspection of mobile phone buttons in the prior art cannot meet the requirements. The method includes: acquiring image sequences of the laser engraved area of ​​the mobile phone button under multiple different lighting directions, and design trajectory information; determining the microscopic gradient vector field and texture contrast value of the laser engraved area based on the image sequences; constructing a light transmission resistance field based on the geometric deviation between the macroscopic light transmission direction and the microscopic gradient vector field, characterized by the design trajectory information, and the texture contrast value; calculating the light transmission attenuation index, which characterizes the overall light transmittance performance of the laser engraved area to be inspected, based on the light transmission attenuation field; and determining the light transmittance quality of the laser engraved area to be inspected based on the light transmission attenuation index.

The invention discloses a transformer substation site selection data processing and feedback method, system and device based on unmanned aerial vehicle-AI cooperation and a medium, and belongs to the technical field of intelligent site selection of electric power engineering, and the method comprises the steps: controlling an unmanned aerial vehicle to shoot a transformer substation site selection region according to a preset flight route, and obtaining a site selection region image; performing preprocessing and feature extraction on the site selection area image to obtain key environment element information; inputting the key environment element information into a pre-trained site selection environment evaluation model to obtain an evaluation result, including a terrain suitability grade, infrastructure proximity and a comprehensive site selection feasibility score; according to the evaluation result and a preset engineering constraint rule base, matching an avoidance suggestion; and displaying the avoidance suggestions. According to the method, site selection suggestions can be provided for decision makers in a shorter time, the advancing speed of substation construction projects is increased, the advantages and disadvantages of site selection can be judged more objectively and accurately, and the risk of site selection errors caused by human factors or insufficient data is reduced.

The invention discloses a defect feature recognition method based on a clothing visual image and a quality inspection system, and aims to solve the problems that traditional manual quality inspection is low in efficiency and poor in precision and an existing automatic system is insufficient in robustness and generalization ability. The method comprises the following steps: after image preprocessing, segmenting by using an SAM network to obtain a clothes main body and an initial flaw; constructing multi-scale features by the FPN, inputting the multi-scale features into the improved YOLOv11 network, and outputting an initial candidate box; correcting the candidate frame according to IoU / Dice to obtain a refined frame; extracting texture and morphological characteristics and calculating abnormal scores; carrying out weighted fusion on multiple indexes to obtain a comprehensive confidence coefficient to identify flaws; and carrying out secondary training to update the model after manually annotating the low-confidence sample. The system comprises eight corresponding modules, realizes full-process automatic detection, can significantly improve the precision, robustness and automation level of garment defect identification, and has important practical application value.

The invention discloses an information processing method and device for extracting anorectal pressure frequency domain characteristics, equipment and a medium, relates to the technical field of medical instruments, is applied to a computer device and is used for receiving original pressure information of various anorectal channels at different acquisition time points, and the original pressure information is acquired by an anorectal pressure measuring catheter; integrating the original pressure information of various anorectal channels under a target analysis time window to obtain a time domain pressure signal; performing short-time Fourier transform on the time domain pressure signals to obtain power spectral density of the pressure signals of various anorectal channels in the target analysis time window; and based on a target frequency band corresponding to the target analysis time window, extracting frequency domain features related to anorectal physiological functions from the power spectral density. And the frequency domain characteristics in anorectal pressure measurement are accurately extracted.

The invention belongs to the technical field of mine grouting simulation test equipment, and particularly relates to a multi-well water level observation test device and an early warning method.The multi-well water level observation test device comprises a simulation box body, a winch and an intelligent control center, and multi-well water level monitoring holes which are evenly distributed are fixed to the upper side of the simulation box body; a telescopic hinge is wound and fixed outside the winch, a steel strand is fixed at the other end of the telescopic hinge, a multifunctional throw-in type liquid level transmitter is fixed at the other end of the steel strand, and the multifunctional throw-in type liquid level transmitter is located inside the multi-well water level monitoring hole; the three-dimensional multi-well linkage physical model test device constructed by the invention has the advantages of simple structure, convenience in disassembly and low cost, the number of mines can be flexibly adjusted, and the depth change of an actual mine can be similarly simulated; the device considers the comprehensive effect of water temperature, water level, water pressure, water quality and water flow direction, simulates the underground water level rise and drop caused by grouting, and is more in line with the actual situation.

The invention discloses a model reasoning ability evaluation method, a data processing method and a storage medium, and relates to the field of large model technologies and data processing. The method comprises the steps that a target test set is obtained, the target test set comprises target questions and first verification information, the target questions are open questions obtained after question type conversion is conducted on original questions, and the first verification information is program codes for verifying answers corresponding to the target questions; the target test set is adopted to evaluate the reasoning ability of the to-be-tested language model, a first evaluation result is obtained, and the first evaluation result is used for determining the logical reasoning performance of the to-be-tested language model. According to the method and the device, the technical problems of low evaluation efficiency and poor evaluation reliability when the model reasoning capability is evaluated in related technologies are solved.

The invention discloses an escalator operation condition intelligent monitoring method and system, and the method comprises the following steps: collecting multi-source data of an escalator, including people flow data and equipment state data; preprocessing the collected data, wherein the preprocessing comprises data cleaning and data normalization; constructing an escalator danger early warning network EHPNet based on a Transform network and a graph neural network, and training the escalator danger early warning network EHPNet; and inputting the preprocessed multi-source data of the escalator into the trained escalator danger early warning network, and monitoring the operation condition of the escalator. According to the method, the operation condition is monitored by fusing the passenger flow data and the equipment state data of the escalator, comprehensive and real-time monitoring and deep insight of the passenger flow, the safe operation state and the equipment health state are achieved, and potential safety hazards can be found in time to guarantee elevator taking safety.

This application provides a learning status assessment method, system, and device based on big data analytics, relating to the field of big data analytics. The method includes: collecting multi-source learning behavior data of students to construct individual knowledge graphs; collecting students' resting physiological signals to construct a physiological signal database; using the individual knowledge graphs as federated nodes and combining them with the physiological signal database to construct a group knowledge graph federation; constructing a teaching progress timeline based on knowledge points and calculating the progress offset between the student's current learning progress and the class's teaching progress; comprehensively evaluating the individual knowledge graphs, the group knowledge graph federation, and the progress offset to obtain a multi-dimensional comprehensive evaluation report; and using a multi-objective optimization algorithm to generate personalized learning plans and push them to students. This solves the technical problems of one-sided, subjective, and inaccurate learning status assessment results caused by a single evaluation dimension and neglect of the dynamic influence of class teaching progress.

The application discloses a marketing activity data analysis management system and method based on a two-dimensional code, relates to the technical field of data analysis, and comprises the following steps: establishing a behavior data management system to collect scanning data and user behavior data, and generating corresponding scanning records; performing multidimensional evaluation on any scanning record, and performing abnormality identification; analyzing the user behavior data of any scanning record, and extracting a user behavior set; selecting two scanning records with different abnormality identification results at random, performing abnormality feature extraction from the user behavior set, and analyzing the influence values of each difference feature; setting an abnormality evaluation threshold value for whether there is abnormality by constructing an abnormality evaluation model; collecting the scanning data and user behavior data of a user in real time, and generating real-time scanning records; and performing abnormality identification on the real-time scanning records based on the influence values of each difference feature in the real-time scanning records.

This invention discloses a transformer aging diagnosis method, apparatus, terminal device, and storage medium based on multi-source data fusion, relating to the field of transformer diagnosis. The method includes: acquiring multi-source state data of the transformer under test collected at different sampling frequencies, inputting it into an aging diagnosis model to extract aging feature parameters; performing time-series alignment on the aging feature parameters to obtain a multi-source feature sequence under the same target time series; generating a static average feature based on the average value of all target time series in the multi-source feature sequence; performing linear regression on the multi-source feature sequence to obtain the feature change slope; generating a global representation vector based on the static average feature and the feature change slope; and generating an aging diagnosis result based on the global representation vector. By implementing this invention, the problem of existing aging assessment methods focusing only on static diagnosis of the current aging state is solved, allowing for a more comprehensive assessment of the transformer's aging condition.

The present application relates to the technical field of automatic control of thermal power plants, and specifically provides a method and system for monitoring and regulating a thermal power plant, which comprises: collecting DCS operation data, and calculating a multi-dimensional feature vector representing the operation state of a unit; inputting the multi-dimensional feature vector into a deep reinforcement learning model, and outputting a regulation action suggestion containing a controlled device, a regulation direction and a regulation amplitude; performing multi-dimensional risk assessment on the regulation action suggestion, and triggering a collaborative decision-making process when any target condition is met; directly and automatically executing when the process is not triggered; generating a structured collaborative decision-making proposal containing an operation object, an operation parameter and a decision basis when the process is triggered, and pushing the proposal to an operator station for execution after receiving an operator response instruction. The present application realizes hierarchical management of regulation tasks through multi-dimensional risk assessment, and realizes effective integration of man and machine through structured collaborative decision-making proposals, thereby improving the safety and reliability of autonomous regulation of thermal power plants.

The application discloses a face image face filling method and system and a storage medium, and the method comprises the following steps: acquiring an input image, performing face feature extraction, and obtaining two-dimensional face features; obtaining two-dimensional face texture feature information according to the two-dimensional face features, and calculating the illumination coefficient of the input image; performing three-dimensional face reconstruction based on the two-dimensional face features and the two-dimensional face texture feature information, combining a preset three-dimensional face model, obtaining a first three-dimensional face model; performing morphological filling processing on the first three-dimensional model, obtaining a second three-dimensional face model, and then adding the illumination coefficient to obtain a third three-dimensional face model; and mapping the third three-dimensional face model to a two-dimensional plane to obtain a face image face filling effect diagram. Through the three-dimensional face reconstruction and morphological filling processing based on the preset three-dimensional face model, the filling effect diagram is more realistic, natural and stereoscopic, and the user can comprehensively evaluate the risk of medical beauty filling.

The invention discloses an electric pole stay wire inspection method and system, and relates to the technical field of electric power, and the method comprises the steps: obtaining the visual monitoring data of a to-be-detected stay wire in the flight process of an unmanned aerial vehicle, and enabling the visual monitoring data to be collected through a visual machine carried on the unmanned aerial vehicle; and detecting attribute information of the to-be-detected stay wire based on the visual monitoring data to determine whether the to-be-detected stay wire is in an abnormal state. According to the invention, unmanned aerial vehicle inspection, a visual machine and a data analysis technology are organically fused, intelligent monitoring of the state of the electric pole stay wire can be realized, and one set of equipment can perform monitoring operation on multiple point positions of multiple electric pole stay wires, so that the labor cost and the hardware installation cost are reduced. Multiple attribute information such as the inclination angle, the fracture condition and the tightness of the electric pole stay wire are detected and analyzed cooperatively, the overall state of the electric pole stay wire can be evaluated more comprehensively and accurately, and a complete data support is provided for operation and maintenance management of electric power facilities.

The present application relates to the cross field of intelligent transportation, human factors engineering, emergency management and artificial intelligence, and particularly relates to a fire driving fatigue monitoring system and method based on survival analysis, which fuses multi-modal data such as physiology, behavior, environment and task, constructs a time-dependent dynamic risk assessment model, introduces a survival analysis framework to quantitatively determine the probability of accidents caused by fatigue during task execution, and identifies fatigue critical points with intervention value in combination with an adaptive threshold mechanism, thereby providing scientific rest determination and takeover decision basis for the task management system. The present application solves the problems of existing fatigue recognition technology in special operation scenarios, such as hysteresis, limitations and lack of critical risk judgment ability; it takes into account real-time, predictability and deployability, and is suitable for high-risk driving environments such as fire fighting, police and dangerous chemical transportation.

This application provides an object evaluation method and apparatus. The object evaluation method includes: acquiring object parameters of the target object to be evaluated in the ontology attribute dimension and the interaction attribute dimension; based on the object parameters in the ontology attribute dimension and the interaction attribute dimension, obtaining the target ontology feature vector in the ontology attribute dimension and the target interaction feature vector in the interaction attribute dimension through the corresponding feature analysis layer in the object evaluation model, wherein the feature analysis layer is determined based on the attributes of the object parameters in the corresponding attribute dimensions; and fusing the target ontology feature vector and the target interaction feature vector through the fusion layer in the object evaluation model to obtain the target value evaluation information of the target object. This solution extracts ontology and interaction attribute dimension parameters and extracts features specifically through an adapted feature analysis layer, improving the comprehensiveness and accuracy of value evaluation. It can be applied to digital cultural product production software in the field of next-generation information technology (such as virtual reality).

The present application relates to the technical field of agricultural product origin identification and traceability, and particularly discloses an agricultural product origin identification and traceability system and method based on characteristic fingerprints, which comprises the following steps: collecting agricultural product samples to obtain a target sample set; marking the target sample set with dominant characteristic fingerprints according to the dominant characteristics of the agricultural products, and performing one-class partitioning on the target sample set according to the dominant marking result to obtain a plurality of one-class sample clusters; marking the target sample set with recessive characteristic fingerprints according to the recessive characteristics of the agricultural products, and performing two-class partitioning on the target sample set according to the recessive marking result to obtain a plurality of two-class sample clusters; comparing the one-class partitioning result and the two-class partitioning result to determine whether to start a successive verification mode or a separate verification mode; based on the successive verification mode, obtaining each verification result, and determining whether to output an actual origin traceability result according to the verification results.

The invention belongs to the technical field of safety of energetic materials, and particularly discloses a method for determining a thermal-mechanical coupling ignition threshold value of an energetic material, which comprises the following steps: firstly, heating an energetic material sample to a preset specific temperature, simulating a possible thermal environment of the energetic material sample, and then immediately carrying out an impact sensitivity test at the temperature to determine the thermal-mechanical coupling ignition threshold value of the energetic material. And thus, a safety threshold closer to an actual risk scene is obtained. According to the determination method, the safety threshold closer to the actual risk scene can be obtained, and the method has the characteristics of comprehensive evaluation and accurate and reliable test result.

The application provides a method, system, device and medium for screening a region suitable for low-altitude logistics layout, relates to the fields of low-altitude economy and geographic information, and comprises the following steps: acquiring navigation electronic map data, DEM elevation data and administrative division data, calculating the average altitude of each township based on the DEM elevation data and the administrative division data of the whole country to generate a preliminary screening region; calculating the elevation characteristics and slope characteristics of each road in the preliminary screening region by using the DEM elevation data to form a road elevation-slope characteristic data set; calculating the road bypassing coefficient, the number of sharp bends and the convenient accessibility index in the preliminary screening region based on the road elevation-slope characteristic data set and the navigation electronic map data, and constructing a road traffic obstacle index set; and evaluating the road traffic obstacle index set by using the analytic hierarchy process, and screening a region suitable for low-altitude logistics layout according to the evaluation result.

This utility model relates to the field of anti-icing coating testing technology, and provides an anti-icing coating testing device using rapid cooling with liquid carbon dioxide. The device includes an aluminum substrate, an aluminum vaporization grid, and a test sample. The test sample is positioned on the top of the aluminum substrate, and the aluminum vaporization grid is positioned on the bottom of the aluminum substrate. A liquid carbon dioxide inlet is located in the middle of the left side of the aluminum vaporization grid, and a carbon dioxide outlet is located in the middle of the right side of the aluminum vaporization grid. This utility model utilizes the principle of heat absorption during liquid carbon dioxide vaporization to rapidly reduce the temperature of the aluminum substrate in a short time, quickly simulating the icing / icing phenomenon under actual extreme low-temperature environments. Compared to traditional testing methods, this significantly shortens the testing cycle, allowing for rapid testing of the anti-icing coating performance, effectively improving testing efficiency, and saving considerable time and costs for research and development and production. Simultaneously, the realistic simulation of extreme environments enhances the practicality and reference value of the test results.

The application provides an infrared video monitoring method and system for fire alarm, comprising the following steps: obtaining a thermal infrared image of a specified scene, and determining the fire smoke concentration of the specified scene according to the thermal infrared image; on the basis of obtaining the thermal infrared image, continuously obtaining the thermal infrared image of the specified scene, and monitoring the change of the fire smoke concentration through real-time analysis; periodically and continuously obtaining the thermal infrared image and monitoring the fire smoke concentration, determining whether the fire smoke concentration exceeds a pre-set threshold according to the continuously obtained thermal infrared image and the change of the fire smoke concentration; in the case that there is obvious flame point, triggering the fire alarm, sending an alarm notice to relevant personnel, and recording relevant information; if there is only smoke without obvious flame point, sending a warning notice to relevant personnel to prompt potential fire risk.

This application relates to the field of soil and water conservation carbon sequestration technology, providing a method and apparatus for calculating carbon sequestration based on temporary measures. The method includes: obtaining soil erosion and soil organic carbon content in the production and construction project area; determining protective effectiveness parameters according to the type of temporary measures for the production and construction project; and determining the carbon sequestration amount of the temporary measures for the production and construction project based on soil erosion, soil organic carbon content, and protective effectiveness parameters. This application proposes a carbon sequestration calculation scheme for temporary protective measures during the construction period of production and construction projects, which can more comprehensively and scientifically assess the carbon sequestration benefits of production and construction projects. Furthermore, it can dynamically determine the corresponding protective effectiveness parameters according to different types of temporary measures, which fully considers the physical differences in sand reduction and erosion prevention mechanisms of various temporary measures, making this method universally applicable to temporary protection systems under various complex construction scenarios.

This application relates to the field of medical device technology, and discloses a signal processing method, an implantable closed-loop neurostimulation system, and a storage medium. The method includes: calculating feature change indices in at least two dimensions based on a target EEG signal; determining a current processing strategy based on the feature change indices in the at least two dimensions; generating a first control command when the current processing strategy is the first strategy; the first control command instructing the output of a first electrical stimulation signal according to a fixed first set of stimulation parameters; generating a second control command when the current processing strategy is the second strategy; the second control command instructing the output of a second electrical stimulation signal according to a dynamically adjusted second set of stimulation parameters; wherein each stimulation parameter in the dynamically adjusted second set of stimulation parameters is calculated based on the modulation of the target EEG signal by the previous stimulation parameter.

The invention relates to the field of micro-noninvasive physical ablation treatment, and discloses a real-time monitoring method and system based on a multi-parameter quantitative ultrasonic image.Firstly, the most original lossless ultrasonic imaging channel data is obtained, conventional signal processing is carried out, a conventional B-mode ultrasonic image is generated, the conventional B-mode ultrasonic image is used for spatial positioning, and a multi-parameter quantitative ultrasonic image is obtained; carrying out two-dimensional traversal processing; calculating quantitative ultrasonic parameter images with different physical meanings; unifying the pixel sizes of different quantitative ultrasonic parameter images; multiple quantitative ultrasonic parameter images reflecting different physical characteristics of the ablated tissue are obtained, data standardization processing is carried out, data fusion is carried out, and a comprehensive quantitative image superior to a single quantitative ultrasonic parameter is generated; the problems that in the prior art, a single-parameter quantitative ultrasonic monitoring image is not sensitive to thermal damage characterization formed in physical ablation treatment, the contrast ratio is low, and damage characterization is not comprehensive are solved.

The present application relates to the technical field of energy planning utilization, and particularly relates to a comprehensive energy system capacity planning optimization method for a zero-carbon park, the present application obtains an output power curve and a consumption power curve, divides a plurality of explicit time periods on the output power curve and the consumption power curve respectively, calculates explicit characteristic coefficients of the explicit time periods according to performance parameters of the explicit time periods, screens first profit and loss fluctuation time periods and second profit and loss fluctuation time periods according to analysis results of the output power curve and the consumption power curve under a first division ratio matching mechanism and a second division ratio matching mechanism, determines profit and loss fluctuation characteristic aggregation time periods, and determines an optimized calling mode of an energy storage end device in each profit and loss fluctuation characteristic aggregation time period, thereby, a complex energy supply and demand relationship is captured according to a multi-matching mechanism, and energy storage optimization calling is combined with physical constraints such as device capacity and geographical distribution, so that the overall performance of the energy system is improved.

This invention discloses a cloud computing-based surveying and mapping geographic information data acquisition system, relating to the field of natural resource management technology. It utilizes a data acquisition module to obtain observation point height (G), observation point latitude (W), and neighboring point data. A data processing module runs data processing algorithms to output assessment data for surveying and mapping geographic information. Based on the assessment data, in-depth analysis is performed on the processed data. A data visualization module displays the data acquisition results and assessment report, and optimizes and adjusts the system. The data processing module includes a unit reflecting the corrected ground elevation, a unit comprehensively assessing horizontal position accuracy, and a unit comprehensively assessing geographic information data quality. This invention has beneficial effects in improving data accuracy, optimizing data processing flow, enhancing system adaptability, and improving decision support capabilities. These effects collectively promote the intelligent and modern development of surveying and mapping geographic information data acquisition systems.

The invention provides a research and development investment project discrimination method and system based on a large language model, and relates to the technical field of artificial intelligence, and the system comprises a data collection module which obtains data through the calling of an API interface, and the data comprises project document data, scientific research report data, market data and historical project data. And the data preprocessing module is used for preprocessing the data, and the preprocessing comprises formatting processing, denoising processing and standardization processing. According to the research and development investment project discrimination method and system based on the large language model, external data source information can be acquired in real time and discrimination standards and rules can be adjusted by introducing an adaptive updating module, the discrimination standards can be flexibly adjusted in the face of rapidly changing market demands and technical progress, and the discrimination efficiency is improved. And the discrimination accuracy of emerging fields or interdisciplinary projects is improved.