377results about How to "Reliable data support" patented technology

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The invention discloses a vehicle target motion state estimation method based on an unmanned aerial vehicle video, and relates to the technical field of computer vision and intelligent monitoring, and the method comprises the steps: receiving a real-time video stream of an unmanned aerial vehicle, decoding the real-time video stream to obtain an original video frame, carrying out the graying, zooming and normalization preprocessing to obtain a processed image, and synchronously adjusting the size of a vehicle bounding box; vehicle targets are detected, a unique ID is allocated for multi-target tracking, and a motion trail is maintained; determining a background feature region, detecting and tracking feature points to estimate an inter-frame transformation matrix, and performing accumulative transformation to obtain a background overall transformation relation and a historical frame-to-current frame mapping mechanism; calculating a displacement residual error based on the trajectory and the mapping, judging direction consistency, estimating a smooth speed, and updating a motion confidence coefficient to judge a vehicle motion or static state and static duration; outputting the ID, the state, the static duration and the average speed of the vehicle; the method effectively eliminates the motion interference of the unmanned aerial vehicle, improves the estimation precision, is suitable for the traffic monitoring of the unmanned aerial vehicle, and is high in real-time performance and reliability.

The invention relates to the technical field of flower moisture determination, and discloses a flower moisture determination system and method based on image data, the flower moisture determination system based on image data comprises the following steps: radiometric calibration is carried out to obtain reflectivity; generating a smooth logarithmic spectrum; calculating a discrete second-order curvature; calculating a curvature residual error; generating a logarithmic spectrum water absorption curvature residual error; generating a single pixel driving quantity; generating a single-value convergence quantity; and generating and outputting a single-value moisture estimation result. According to the method, multiplicative envelope of thin film transmission is converted into additive terms through logarithmic spectrum conversion, noise is suppressed in combination with second-order regular smoothing, non-moisture interference caused by sleeve wrinkle reflection is stripped through discrete second-order curvature calculation and curvature residual extraction, and multi-moisture absorption band characteristics are subjected to adaptive weighted fusion, so that the multi-moisture absorption band characteristics are obtained. Meanwhile, a soft weight field is used for replacing traditional hard segmentation of the flower target area, and result fluctuation caused by boundary drift of the flower target area is avoided; and the automatic online detection rhythm of the flower production line is adapted.

The invention belongs to the field of carbon dioxide geological sequestration and oil-gas field development, and relates to a shale carbon dioxide adsorption expansion damage experiment method considering a hydration state, which comprises the following steps: processing a shale sample according to requirements; the shale is subjected to constant-humidity regulation and control pretreatment, and in the process, different relative humidity environments can be used for pretreatment, so that the influence of different clay mineral hydration interlayer spacing states on adsorption expansion is obtained; soaking the pretreated shale in supercritical carbon dioxide, adsorbing the sample when the temperature and pressure conditions reach a set value, soaking until the rock sample reaches adsorption saturation, and treating by using carbon dioxide with different pressures and temperature gradients; according to collection of sample microstructure and mechanical data, damage can be treated through crack initiation position comparison, porosity and gray scale quantitative analysis and macro-mechanical parameter evolution. The method provides an experimental method for carbon dioxide geological sequestration safety assessment and shale gas fracturing parameter optimization.

The invention discloses a soil nutrient inversion method based on multi-source physical constraint and a multi-scale attention network, and aims to solve the problems that a soil nutrient inversion method based on remote sensing lacks enough truth value marking data and does not consider spatial autocorrelation of soil nutrients in geographic space and a physical imaging rule influenced by a microenvironment and an earth surface structure. Therefore, the problems of deviation of the inversion value and lack of spatial texture constraint and geographical continuity of the soil nutrient content distribution map generated by inversion are solved. According to the method, the collaborative Kriging trend and soil microenvironment and earth surface structure characteristics are introduced as physical constraints, a sample expansion confrontation model is constructed, sample expansion is performed by a scientific method integrating a physical environment and a spatial law, the physical imaging law of soil nutrients is fully considered, and the accuracy of the sample expansion confrontation model is improved. In combination with a designed multi-scale residual attention inversion model for extracting key information from a spectrum, the generated soil nutrient content distribution map is relatively excellent in spatial texture constraint and geographical continuity.

The invention discloses a wide-working-condition steam turbine system operation data correction method based on digital twinning, and relates to the technical field of steam turbine equipment digitalization, and the method comprises the steps: collecting operation data of a wide-working-condition steam turbine system in real time; constructing a digital twinborn model of the steam turbine system; performing prior covariance estimation on the operation data according to the statistical distribution condition and the design parameters; generating a Sigma point by adopting an unscented Kalman filtering algorithm, iteratively updating a state vector and a covariance in combination with a state transition equation and an observation equation, and outputting an updated known variable; performing smoothing processing on the updated known variable in a plurality of time point regions by adopting an RLOESS algorithm to obtain corrected operation data; according to the method, the real dynamic characteristics of the wide-working-condition steam turbine are approached by building the digital twinborn model, the calculation complexity of dynamic data fusion of a steam turbine system can be remarkably reduced, and the problems that the convergence speed is low and calculation is complex due to strong nonlinearity of a traditional method are solved.

This invention discloses a battery temperature and strain detection device and battery pack, relating to the field of battery monitoring technology. The device includes a light source, a controller, and a detection optical fiber. The detection optical fiber is connected between the light source and the controller to receive and transmit light to the controller. The controller is configured to determine a first wavelength shift caused by temperature influence when light flows through a fiber optic grating in the detection optical fiber, and a second wavelength shift caused by strain influence when light flows through a photonic crystal fiber in the detection optical fiber. Based on the first and second wavelength shifts, and the temperature and strain sensitivity coefficients of the fiber optic grating and the photonic crystal fiber, the temperature change and strain change of the battery are determined. Based on the temperature change, strain change, and preset temperature and strain reference values, the battery temperature and strain values ​​are determined. This solution improves the ability to detect battery temperature and strain.

This invention relates to the field of force sensor technology, and more particularly to a pressure-balanced underwater six-dimensional force sensor sealing structure and method. It primarily addresses the problems of insufficient sealing pressure resistance and susceptibility to seawater leakage when existing six-dimensional force sensors are applied in underwater scenarios, and the fact that high underwater pressure can cause deformation of the main structure, interfering with strain measurement and leading to force signal deviation. The proposed technical solution includes a force sensor body, with a mounting plate installed at the output end of the force sensor body, and an elastic element disposed at and penetrated by the elastic element at the output end of the force sensor body; a sealing element disposed on the side of the force sensor body away from the elastic element, the sealing element being made of rigid or elastic material. The force sensor body, the elastic element, and the sealing element form a sealing structure that encloses the deformable beam and the PCB board. This invention can improve its underwater sealing pressure resistance and anti-interference capability, ensure force measurement accuracy, and assist underwater robots in precise operation.

The invention discloses a power grid lightning arrester on-line monitoring system based on a PHM, and the system comprises a voltage on-line collection module which is used for collecting a voltage signal of a corresponding lightning arrester; the synchronous control module is used for acquiring synchronous sampling data of the leakage current signal and the bus voltage signal; the signal processing module is used for acquiring fundamental components of the leakage current signal and the bus voltage signal and harmonic components of preset times; the feature generation module is used for generating resistive current feature data of the lightning arrester; the data integration module is used for forming a multi-parameter operation state data set of the lightning arrester; the health state evaluation module is used for obtaining a health state evaluation result; the trend analysis module is used for acquiring lightning arrester health state change trend information; and the fault risk assessment module is used for generating a lightning arrester fault risk assessment result and realizing online assessment, trend early warning and fault risk prediction of the health state of the lightning arrester.

This invention relates to the field of chemical production technology and discloses a cyclohexanone oxime rearrangement mixer structure, a numerical simulation model, and an analysis method. The cyclohexanone oxime rearrangement mixer structure includes a main structure, a circular ring, a cyclohexanone oxime inlet, and cyclohexanone oxime orifices. The main structure is vertical, with a circulating liquid inlet, a throat, and a mixture outlet arranged sequentially from top to bottom. A circulating liquid containing caprolactam, sulfuric acid, and SO3 flows into the main structure from the circulating liquid inlet. The circular ring is fitted onto the main structure and located between the circulating liquid inlet and the throat. To achieve thorough mixing of cyclohexanone oxime and the circulating liquid, the numerical simulation model is constructed using the Eulerian multiphase flow model and the Realizable k-ε turbulence model. The momentum ratio (MR) is used as an evaluation index for mixing effect, ensuring the momentum ratio is within a suitable range of 1-4, thereby achieving efficient mixing.

The invention relates to filter stick box tracing equipment and a filter stick box tracing method thereof. The method comprises at least one filter rod box processor which is further configured to carry out at least one processing of loading, storing and air clearing on the filter rod boxes; each filter stick box processor is correspondingly connected with a code scanner, and the code scanners are further configured to scan identification codes of the filter stick boxes on the filter stick box processors so as to establish an identifier mapping relation between filter stick box identifiers of the filter stick boxes and filter stick box processor identifiers of the filter stick box processors; the upper computer is connected with the code scanners and is configured to associatively store the identification mapping relation and the scanning time sent by the code scanners into an identification database for each code scanner and display a query interface under the condition that a query demand is received; the query interface is used for querying the processing track of each filter stick box. By adopting the method, the tracing efficiency of the filter stick box can be improved.

The invention relates to a space laser radar forest structure data correction method and system, and belongs to the technical field of space laser remote sensing and forest resource monitoring. Aiming at four kinds of errors of geometric positioning offset, slow distortion, terrain broadening effect and canopy structure influence of GEDI data, UAV control points are arranged by adopting a hierarchical arrangement strategy, a homonymy point relation is established through waveform registration, and weights are calculated; performing overall geometric correction based on the regular grid control points; carrying out local distortion correction based on the encryption control point; establishing a physical compensation model to compensate the terrain broadening effect; based on the canopy structure parameters and GEDI signal quality indexes, establishing a statistical regression model to correct a canopy height residual error; and finally, obtaining a high-precision canopy height convergence result through spatial smoothing processing, and outputting corrected data. The method achieves step-by-step precision improvement from the whole domain to the local domain and from the geometry to the height, and is low in cost, high in precision and wide in application range.

The application discloses a leveling device and method for bridge support assembly and belongs to the technical field of bridge support assembly; the leveling device comprises a supporting frame, a conveyor and a pressure applying and leveling assembly; the pressure applying and leveling assembly applies pressure through a leveling oil cylinder, then height adjustment and state detection are realized with the help of the leveling oil cylinder and a distance sensor, and a pressure sensor is arranged between the leveling oil cylinder and a horizontal fixing plate to monitor pressure; manual operation is replaced by mechanical automation, the efficiency of bridge support assembly is remarkably improved, accurate measurement and control are realized through the sensor, human errors are avoided, leveling precision and assembly quality are improved, human cost and labor intensity are reduced, and reliable guarantee is provided for bridge support assembly.

The application discloses an intelligent dust removal device for waste gas treatment of a coal-fired power plant, and relates to the technical field of waste gas treatment.The device comprises a dust removal box, an air inlet fixedly connected to the side wall of the dust removal box, a filter plate fixedly connected to the inside of the dust removal box, and a filter effect real-time detection mechanism and a dust cleaning and collecting mechanism.The device can reduce unnecessary troubleshooting and maintenance frequency, thereby reducing maintenance cost and time cost, and can maintain or replace the clogged or damaged filter plate in time when the filter plate is damaged, so that the continuous and efficient operation of the spray dust removal system can be ensured, and the overall operation efficiency is improved.Further, the device can avoid long-time use of the filter plate without timely maintenance or replacement, so that impurities and particulate matter can be prevented from entering the spray dust removal system, the cleanliness of water resources is ensured, and the overall performance of the spray dust removal system is improved.

The invention provides a method for generating performance degradation data of a train air braking system. The method comprises the following steps: on the basis of a brake system of a preset model, analyzing three stages of pressure rise, maximum pressure and pressure stability of pressure change of a brake cylinder, and extracting a plurality of typical fault modes; based on an extended random process model with non-monotonicity and independent incremental property, three stages of pressure change of a brake cylinder and multiple typical fault modes are combined, and linear, nonlinear or stepped performance degradation process modeling of the train air brake system is carried out; overlapping normal distribution random noise on a performance degradation track generated by modeling, simulating a control precision error of an actual braking system, and optimizing a performance degradation process model of the train air braking system; and utilizing the train air braking system performance degradation process model to generate train air braking system performance degradation data in batches.

The invention belongs to the technical field of petroleum well logging, and discloses a method for eliminating array induction direct coupling signals, which comprises the following steps of: calibrating the unit thickness change of an adjusting piece and the quantitative contribution of each receiving coil direct coupling signal through electromagnetic simulation modeling and an underground environment equivalent experiment; the target thickness is solved and replaced through a linear correction model, closed-loop calibration is matched to enable a direct coupling signal to approach a preset threshold value, based on array induction logging, an existing three-coil system structure is difficult to thoroughly offset the direct coupling signal due to machining errors, useful signal extraction is seriously disturbed, the method does not need to modify a core structure of an instrument, operation is easy and convenient, adaptability is high, and the method is suitable for large-scale popularization and application. Direct coupling signals are eliminated accurately and thoroughly, the measurement accuracy of the stratum conductivity is effectively improved, and reliable data support is provided for oil and gas reservoir identification and evaluation.

The application discloses a kind of based on regional meteorological characteristics wind farm wind speed refinement prediction method, it is related to wind power prediction technical field, including: first, using convolutional neural network (CNN) extraction wind farm in the grid meteorological data of multiple pressure layers in region, to obtain regional meteorological characteristics;Second, using long short-term memory network-multi-head self-attention mechanism (LSTM-MHSA) model processing wind farm location multiple vertical isobaric surface sequence meteorological data, to extract vertical wind profile feature;Third, using multilayer perceptron (MLP) extraction wind farm surface static meteorological elements in nonlinear feature.Finally, the above-mentioned three different dimensions, different sources of features are fused, and a coupled prediction model is constructed to output short-term wind speed prediction results for wind farms.The application significantly improves the accuracy and refinement level of short-term wind speed prediction for wind farms by comprehensively integrating regional, vertical and surface multi-source meteorological information.

The invention provides a steel plate defect detection method and system based on machine vision, and relates to the technical field of steel plate defect detection.The method comprises the steps that upper and lower surface sensors, an electrical cabinet, a detection server and a camera computer are deployed on a production line, and power supply connection is conducted through the electrical cabinet; irradiating the steel plate by using an LED light source, and triggering a line scanning camera by an encoder to acquire upper and lower surface and edge images; processing and filtering pseudo defects through a camera computer, identifying real defects and extracting images, and determining defect types, positions and severity by combining a multi-level classifier and an expert database; after related data are stored, quality files such as coiled material reports are automatically generated, sound-light alarm is triggered when the defect severity threshold value is exceeded, the field control unit is linked to execute feedback operation or output I / O signals, online detection, classification, storage, report generation and threshold-exceeding alarm linkage of steel plate defects can be achieved, and the detection efficiency and the quality control level are improved.

The present application relates to the technical field of smart park management and intelligent traffic, in particular to a smart park parking decision optimization method and system, comprising the following steps: S1: collecting multi-dimensional original data related to park parking through multi-source sensing equipment, and preprocessing the collected original data. Through the weighted feature fusion and coarse-fine granularity adaptive prediction model system, the present application dynamically optimizes the prediction accuracy combined with the online learning mechanism, accurately outputs the multi-time and space granularity parking demand and traffic situation results, provides reliable data support for decision making, and according to the cloud-edge-end collaborative architecture and high-fidelity digital twin simulation environment, through the hierarchical dynamic multi-objective optimization algorithm and iterative verification mechanism, generates the optimal parking scheduling and traffic guidance strategy that meets the constraints of complex scenes and takes into account multiple demands, greatly improves the scientificity and feasibility of decision making.

A rotor engine comprehensive bench test system and test method belong to the technical field of engine test. The system contains rotor engine, AC power dynamometer, main control unit and other groups of modules. The dynamometer can realize forward and reverse reversible rotation of the engine. The main control unit is provided with forward and reverse switching and three-stage alarm module. Each component is connected and communicated. Sensors, acquisition modules, analyzers and the main control unit are cooperatively networked. The test method sequentially completes bench building, system inspection, pre-starting verification, lubrication establishment, engine starting, top dead center searching, mechanical loss test, warming, full-range boundary monitoring, hot-state running-in, ECU online calibration and data evaluation. The combustion analyzer can calculate cylinder pressure parameters. ECU modified parameters take effect immediately. Data analysis covers power and economic indicators. The present invention solves the problem that existing benches cannot adapt to rotor engine tests, builds a safe and efficient comprehensive test platform and provides technical support for rotor engine research and development.

The invention belongs to the technical field of electric power prediction, and particularly relates to an electric power load prediction system which obtains a load parameter sequence through an acquisition module and extracts correlation coupling characteristics representing influence degrees of seasons, meteorology and electricity price factors; using a first prediction module to obtain a short-term load prediction result based on the sliding time window and the short-term prediction sub-model, and using a second prediction module to obtain a long-term load prediction result based on the longer time window and the long-term prediction sub-model; a coupling loss function is innovatively constructed through an online coupling module for cooperative training, and deep correlation analysis of fluctuation mode types corresponding to temperature, electricity price and load fluctuation sequences is realized by adopting fluctuation mode clustering, multi-dimensional feature extraction and load mode coupling weight matrix technologies. The technical problem of mutual isolation of long-term and short-term prediction is effectively solved, and the accuracy and adaptive capacity of load prediction are remarkably improved.

The utility model discloses a kind of spiral samplers for sampling in steeping pit, including spiral sampler and installation platform, sampling port, screw mechanism, water level sensor and sample storage mechanism are equipped on the spiral sampler, sealing mechanism is equipped on the sampling port, the bottom end of the installation platform is provided with sliding slot, sliding rail is equipped on the sliding slot, electric sliding block is equipped on the sliding rail, the bottom end of the electric sliding block is equipped with adjusting plate, lifting mechanism is equipped between the adjusting plate and the top end of the spiral sampler, installation plate is equipped on the spiral sampler, locking mechanism is equipped between the installation plate and the adjusting plate, the locking mechanism includes lifting iron cylinder and lifting column, the structure is moved from specified position, adjusts sampling depth, executes sampling task to lastly take out sample, the whole process realizes automation control, not only significantly improve work efficiency, also reduce the error possibly brought by human operation, improve the accuracy and consistency of sampling.

This invention discloses a real-time evaluation method for photovoltaic panel defects and performance based on multispectral imaging, belonging to the field of computer processing technology. The method includes the following steps: S01, emitting multispectral light including visible light, near-infrared, and thermal infrared bands to the photovoltaic panel, and simultaneously receiving reflection and radiation signals based on the multispectral light to obtain a multispectral image dataset; wherein, the dataset includes visible light images, photoluminescence images in the near-infrared band, and thermal infrared images; S02, performing registration and fusion processing on the multispectral image dataset to generate a registered multispectral fused image. This invention, through multispectral information fusion and intelligent analysis, achieves simultaneous diagnosis of internal and external defects of photovoltaic panels and quantitative evaluation of power generation performance, significantly improving detection efficiency and maintenance accuracy.

This invention discloses a method, apparatus, equipment, and medium for parameter inversion of the main reinforcement of concrete poles. It includes: acquiring and parsing raw data to obtain a pure static magnetic feature sequence; calculating the spatial coordinate offset values ​​of the pure static magnetic feature sequence on the first and second coordinate axes respectively, fusing the spatial coordinate offset values ​​of the first and second coordinate axes to obtain a topology navigation signal curve; acquiring multiple local first numerical points on the topology navigation signal curve, and taking the point with the smallest value among adjacent first numerical points as the second numerical point; obtaining multiple feature slices; constructing a multidimensional feature mapping vector; and inputting the multidimensional feature mapping vector into a pre-trained nonlinear regression model for multivariate inversion calculation to obtain the predicted size parameters and predicted lift-off distance parameters corresponding to the main reinforcement of the concrete pole. By processing the acquired signal, this invention effectively solves the problems of conventional deep learning models lacking physical prior constraints and facing high difficulty in parameter inversion.

The invention relates to a high-resolution remote sensing image tree segmentation method based on a crown perception double-branch attention network, and belongs to the technical field of remote sensing segmentation and remote sensing recognition. The method comprises the steps that a data enhancement module is adopted for processing, and tree specific enhancement and general geometric enhancement are included; the feature coding module performs multi-level feature extraction; processing by a double-branch attention module; tree crown sensing multi-scale feature extraction; decoding and up-sampling: fusing high-level semantics and bottom-layer texture information by adopting a multi-level up-sampling and jump connection structure, and gradually recovering complete details of the tree crown; multi-task prediction: outputting three results of tree region segmentation, boundary detection and center prediction at the same time, and realizing unified modeling of semantic and instance segmentation; and in combination with the center and boundary prediction results, instantiation separation of the tree crown is completed by using a morphological method and a watershed algorithm, and an independent individual tree identification result is obtained. According to the method, instance-level separation of overlapped crowns is realized, and the accuracy of individual tree identification is improved.

The application discloses a wheel-bucket excavator experimental platform suitable for an alpine environment and relates to the technical field of mine mechanical test equipment, comprising a simulated rock wall, a wheel-bucket test device and a strain gauge; the wheel-bucket test device comprises a wheel-bucket assembly and a plurality of buckets uniformly arranged along the circumference of the wheel-bucket assembly, and a plurality of bucket teeth are arranged on the outer side of the bucket and directly contact the simulated rock wall; the strain gauge is inlaid in the connection between the bucket tooth and the bucket and is used for collecting the horizontal and vertical torsional stress changes of the bucket tooth; the simulated rock wall is arranged to simulate the physical properties of rock-soil bodies in the alpine environment, the bucket teeth directly contact the simulated rock wall to realize accurate simulation of the digging working condition, and the technical problem that the existing experimental platform cannot be adapted to the alpine environment is solved, thereby providing an experimental basis in line with actual working conditions for performance verification of the wheel-bucket excavator used in the alpine environment.

The present application belongs to the technical field of port safety monitoring, and specifically relates to a method and system for identifying personnel approaching a cable launching area in a port, a terminal and a storage medium, which comprises selecting a fixed cable column of a port berth as a physical reference, using a high-resolution network camera to collect panoramic images of the port berth, using a pre-trained YOLOv8 deep learning model for multi-target segmentation, and performing secondary focusing identification to quickly and accurately identify personnel, cables, cable columns and ship outline targets, and by obtaining dynamic factors such as cable tension and ship docking angle, the reference radius of the dangerous area is corrected by combining the corresponding calculation formula, and a dynamic dangerous area polygon is generated, fully considering the dynamic changes of the port operation environment, which can update the dangerous area in real time, making the division of the dangerous area more in line with the actual situation, avoiding misjudgment and missed judgment due to the fixed dangerous area, and improving the accuracy and effectiveness of safety management.

The invention discloses an integrated control system for electric modification of an electric tractor, and belongs to the technical field of agricultural machinery. The system comprises a signal processing module, a health state evaluation module, a control decision module, an execution module and an optimization module, all the modules realize data interaction through the Ethernet, and the system is adaptive to heterogeneous hardware integration requirements after electric modification of a traditional fuel tractor. According to the invention, the health state evaluation module and the prediction model realize quick response and graded protection of high-voltage insulation, battery overheating and actuator fault scenes through clear quantification, and realize quantitative scoring of the health degree in the limitation of temperature, load and attitude coupling complex scenes; meanwhile, the time domain and frequency domain characteristics of the signals are extracted to provide a quantitative basis for evaluation, different actions of power reduction, speed limiting and emergency shutdown are triggered according to the health degree state, the situation that operation efficiency is affected by excessive protection is avoided, early warning can be conducted in the early stage of a fault, rapid protection can be conducted when the fault occurs, and the running safety and reliability of the tractor are improved.

The application discloses a kind of dike damage animal information acquisition method, system, equipment and storage medium.It includes: obtaining the authorized account information input by patrol officer, the authorized account information is checked, when checking, access permission is determined based on authorized account information;Obtain the project list corresponding to access permission, and determine target project from project list;Based on target project, obtain patrol information;The patrol information is checked, and after checking, it is stored in census database as patrol record.Through checking authorized account information to determine access permission, data access range can be accurately controlled, information leakage and disorderly operation are avoided, and system use safety is guaranteed.Through obtaining patrol information based on target project, data and project accurate binding are realized.Through checking information and storing in census database, data format is guaranteed to be standard, complete and effective, structured storage is realized, and reliable data support is provided for subsequent management analysis.

The invention discloses a sodium-ion battery pack health state online evaluation method and system, and the method comprises the following steps: S1, constructing a sodium-ion battery aging model, collecting and preprocessing pack operation data, and generating a data sequence; s2, calculating a feature entropy value, adjusting the state of the liquid neural network, and extracting a fusion feature sequence; s3, performing path signature transformation on the fusion feature and the simulation sequence, calculating a structural deviation, and generating a deviation sequence; s4, updating model parameters by using particle filtering, and reasoning a capacity estimation value to form a capacity sequence; s5, performing Loess fitting and smooth filtering on the capacity sequence to generate a capacity estimation curve; and S6, evaluating the Pack health state according to the capacity estimation curve, and outputting an online result. According to the method, digital twin modeling, a liquid neural network and the like are fused, and the method has the advantages of high evaluation precision, high response speed and high adaptability.