667 results about "Online analysis" patented technology

The invention discloses a substation equipment state monitoring and intelligent fault early warning method based on deep learning. The method comprises the following steps: S1, obtaining a preprocessed multi-source state data set; s2, generating a high-dimensional equipment state feature matrix; s3, a fault sensitive deep belief network model is adopted to form a preliminary fault state recognition result; s4, obtaining an optimized sensitive depth belief network model; s5, performing online analysis on the multi-source state data acquired in real time by using the optimized sensitive deep belief network model, generating a real-time fault prediction result of the equipment state, and classifying and grading fault risks; and S6, according to a real-time fault prediction result, triggering a remote fault early warning mechanism, and sending fault early warning information including a fault risk level, an early warning signal and an emergency processing suggestion to a substation operation and maintenance center. According to the invention, intelligent alarm linkage and hierarchical control of the scheduling system are effectively supported.

The invention discloses a personnel behavior analysis management system and method based on AI vision, relates to the technical field of vision analysis, and solves the problem of imperfect definition of abnormal behaviors by introducing a dynamic behavior feature verification module, calculating an image verification factor Bcz and evaluating and extracting potential abnormal behavior features. A multi-target online analysis module is adopted, a convolutional neural network and a space-time diagram convolutional network are fused, a behavior abnormal factor Ax and a target tracking factor Tg are extracted through an attention mechanism, and Kalman filtering and an SORT algorithm are combined, so that accurate tracking of multi-target behaviors is realized, and the problem of difficulty in multi-target tracking is solved; the problem that the platform data fusion degree is low is solved through the self-adaptive comprehensive evaluation module; the abnormal behavior recognition, target tracking and multi-source data fusion analysis capabilities are effectively improved, and accurate monitoring and intelligent intervention of abnormal behaviors in a complex scene are realized.

The invention provides an intelligent online analysis and monitoring system and method for circuit board production, and the system comprises an image collection module, a multispectral imaging module, a three-dimensional scanning measurement module, a copper thickness test module, a data collection module, an intelligent analysis and recognition module, and a self-adaptive algorithm optimization module. The system is used for carrying out real-time image acquisition on each key station in the circuit board production process by adopting a high-resolution industrial camera. Through high-definition image acquisition, multispectral imaging, three-dimensional scanning and measurement, comprehensive data acquisition in the circuit board production process is realized, the problem of limited data acquisition range in the prior art is solved, accurate detection and classification of circuit board defects are realized by applying an intelligent analysis algorithm, and the production efficiency is improved. The accuracy and efficiency of defect detection are improved, automatic adjustment and optimization of algorithm parameters are achieved through the self-adaptive algorithm optimization module, it is ensured that the algorithm can continuously adapt to changes of the production environment, and the stability and reliability of the system are improved.

The invention discloses a crane stress monitoring data processing method and system, and solves the technical problem that real-time online analysis of stress monitoring big data is difficult to realize due to lack of a crane intermittent stress monitoring big data processing method in the prior art. The method comprises the following steps: acquiring stress monitoring data through a crane stress monitoring system; eliminating stress abnormal values; extracting and separating trend terms of the monitoring data to obtain new monitoring data; segmenting the new monitoring data according to the time of one working cycle of the crane to obtain segmented monitoring data; calculating the difference value between the maximum stress value and the minimum stress value of the segmented monitoring data, and assuming that the fatigue limit of the material is Sf, and the threshold value of the stress amplitude Sa is 5% of Sf; and judging whether the stress monitoring data of the section needs to be stored / remotely transmitted or not. According to the method, the calculation requirement is low, whether the crane causes the fatigue accumulated damage state or not can be effectively judged, and the stress monitoring big data storage / transmission capacity is greatly reduced.

The invention relates to the technical field of quality detection, in particular to a gas atomization powder sphericity degree multi-dimensional online analysis system and a method thereof.The gas atomization powder sphericity degree multi-dimensional online analysis system comprises a dynamic dual-mode imaging module, a transverse wind field auxiliary detection unit and a multi-dimensional feature fusion analysis module; the transverse wind field auxiliary detection unit is used for applying controllable transverse wind power through an airflow nozzle orthogonal to the powder falling direction and measuring the deflection track of gas atomization powder ball particles in combination with a laser displacement sensor. The online calibration module is used for spraying standardized spherical particles to the powder flow according to a preset period; the traditional density detection depends on destructive sampling and off-line measurement, the efficiency is low, and the whole production line particles cannot be covered; through an orthogonal wind field trajectory inversion technology, a density value and an internal defect mark are synchronously output through non-contact dynamic measurement, 100% lossless online full inspection of a production line is realized, and sampling limitation and aging bottleneck of a traditional means are broken through.

Systems and methods for protecting electronic communications are described. A cyber security appliance may be configured to calculate a topic shift score for a communication by comparing a first lexical profile derived from the communication to a historical lexical profile established for an associated user. This analysis may be performed without using a large language model. The system may also parse communications to extract sensitive data and content from attachments, performing behavioral modeling on the extracted data. Based on the analysis, an autonomous response module may take a variety of mitigation actions. Furthermore, a security mailbox assistant module may perform a secondary, in-depth analysis on user-submitted communications and generate a deterministic report. For outbound communications, a data loss prevention architecture may divert messages for in-line analysis and may include a fail-safe timeout mechanism to ensure service continuity.

The invention belongs to the field of air pollution prevention and control, and particularly discloses an urban air pollution transmission path and source contribution evaluation system and method based on machine learning and a numerical mode, and the evaluation system comprises a meteorological simulation module, a pollution emission list module, a numerical traceability module and a machine learning transmission path evaluation module. According to the method, machine learning and a numerical mode are combined, the automation degree is high, automatic downloading, automatic running and online data analysis can be achieved without manual data statistics and analysis, operation is convenient, data accuracy is high, the response speed is high, and important support is provided for work such as atmospheric pollutant cause tracing and atmospheric pollution control scheme making.

The invention provides a laser spectrum online analyzer, and relates to the field of mineral processing. The laser spectrum online analyzer comprises a control analysis unit, a first sample chamber, a second sample chamber, a spectrum unit and a laser unit, the first sample chamber is used for accommodating a tested sample; the second sample chamber is used for accommodating a to-be-detected sample; the spectrum unit comprises a spectrograph, a first light receiving probe and a second light receiving probe; the laser unit comprises a laser light source, a reflector, a first focusing lens and a second focusing lens. The control analysis unit compares the current spectral intensity of the detected sample with the spectral intensity of the detected sample which is measured in advance, so that the change amplitude of the spectral intensity can be obtained, the spectral intensity is calibrated, and long-term on-site stable operation can be realized. In addition, the laser spectrum analyzer can also perform self-calibration on spectral line drift.

The invention provides an efficient quality management system for a cement production line, and the system comprises an online analysis device which is used for obtaining the chemical component data of a raw material and the technological parameters in the production process; the data processing unit is used for preprocessing the chemical component data and the process parameters to obtain standardized data; the mathematical model is obtained based on historical production data and product quality target training and used for predicting product quality according to the standardized data; the data acquisition module is used for continuously acquiring real-time data in the production process and forming a dynamic data set; the model optimization unit is used for carrying out iterative optimization on the mathematical model by utilizing the dynamic data set; the automatic equipment is used for executing raw material ratio adjustment and process parameter optimization according to the optimized control strategy; and the quality detection equipment is used for detecting the final product in real time, acquiring key index data and comparing the key index data with a preset quality target to form a closed-loop feedback mechanism.

The invention relates to the technical field of on-line analysis, in particular to a polyvinyl alcohol alcoholysis degree distribution on-line measurement method and system.The method comprises the following steps that spectral data of a polyvinyl alcohol solution is obtained, a characteristic absorption wave band in the ester group to hydroxyl group process is extracted, absorption intensity in the wave band is recorded to construct a sequence, peak positions are extracted, intensity difference is calculated, and the direction is marked; and identifying a fluctuation interval, calculating an angular velocity trend, and screening anomalies and generating an unstable section set in combination with a disturbance amplitude and a component coincidence rate. According to the method, quantitative analysis of alcoholysis degree conversion characteristics is realized through selection of characteristic absorption wavebands in spectral data and accurate identification of the change trend of the intensity difference values, the characterization precision of the alcoholysis degree of polyvinyl alcohol is improved, and more accurate trend fluctuation identification capability is provided through comparison of angular velocity difference values of absorption intensity change rates, so that the accuracy of the analysis of the alcoholysis degree of polyvinyl alcohol is improved. The analysis level of alcoholysis degree distribution details is remarkably improved, the abnormal fluctuation interval of alcoholysis degree component distribution is recognized, and the product quality difference caused by alcoholysis degree fluctuation is reduced.

The invention discloses an anti-digestion polysaccharide-based food colon simulated glycolysis and multi-dimensional online analysis system, and belongs to the technical field of food. According to the method, glycolysis simulation of each colon part is completely carried out according to a human body digestion and glycolysis process and a physiological environment, and intestinal mucosa pellets are added to simulate a human body intestinal mucosa environment, so that the degradation process of partial microorganisms of the human body colon for resisting digestion of polysaccharide-based food is simulated under an in-vitro condition; and the glycolysis condition of the digested polysaccharide-based food entering the colon can be observed on line, and the device fits the real physiological environment of people.

The invention relates to an acetic acid production line on-line analysis system, and relates to the field of on-line gas analysis equipment.The acetic acid production line on-line analysis system comprises a pretreatment box and an analysis cabinet, the pretreatment box is connected with an acetic acid production line through a sample feeding pipe and connected with the analysis cabinet through a sample conveying pipe, and a pretreatment module is arranged in the pretreatment box; the pretreatment module comprises a sample pressure reduction unit and a heating unit, the sample pressure reduction unit is connected between the sample feeding pipe and the sample conveying pipe, and the heating unit is arranged adjacent to the sample pressure reduction unit and the sample conveying pipe and is connected with the analysis cabinet; a pretreatment module, an analysis module and a tail gas treatment module are arranged in the analysis cabinet, the pretreatment module comprises a bypass unit and a flow stabilizing unit, the bypass unit is arranged between the sample conveying pipe and the tail gas treatment module, the flow stabilizing unit is connected between the sample conveying pipe and the analysis module, and the tail gas treatment module is connected with the analysis module; the stability and the real-time performance of a sample detection result of an online analysis system can be improved.

The invention belongs to the technical field of automatic welding of large steel structures. According to the large steel structure field welding integrated robot and the operation method, through the design of the quick change mechanism, integration of various tail end tools is achieved, and integration of multiple functions such as welding, grinding, flaw detection and spraying is achieved; a real-time online analysis-processing-sensing system of multi-source data space-time fusion interaction is constructed, a multi-terminal working path autonomous online planning strategy in a complex field environment is provided, and a high-precision, high-speed and anti-disturbance control method for a mechanical arm and a self-learning optimal control method for terminal precise positioning are provided. The problem that the on-site steel structure welding procedure is simplified is solved, the installation precision and the construction efficiency are improved, and intelligent building development is promoted.

The invention relates to the field of wastewater treatment, in particular to an online analysis method and system for ink-jet printing wastewater treatment data, and the method comprises the steps: obtaining the water quality, process and equipment state parameter data of ink-jet printing wastewater based on each sensor, and constructing an original data matrix through preprocessing; decomposing the matrix, selecting a preset number of principal components for reconstruction, and generating a reconstructed data matrix; a reconstruction error is calculated by analyzing the difference between an original matrix and a reconstruction matrix, a correlation distortion index is analyzed based on row vector similarity, and an objective function is constructed to determine the number of optimal principal components; and clustering is carried out by using reconstruction errors and distances, abnormal data points are screened, and process parameters are regulated and controlled. According to the method, by optimizing the number of principal components and improving clustering analysis, the noise interference problem under complex water quality changes is effectively solved, the anomaly detection precision and the system stability are remarkably improved, and the robustness and the adaptability of an ink-jet printing wastewater treatment system are enhanced.

The invention belongs to the field of coal quality analysis, and discloses a microwave heating type coal quality on-line analysis device and application thereof.The device comprises an on-line sample collecting and preparing module, a microwave heating module, a weight collecting module and an analysis control module, and the microwave heating module comprises a microwave drying cavity, a microwave devolatilization cavity and a microwave ashing cavity; each chamber is connected with a microwave temperature control unit for independent temperature control; the online sampling and sample preparation module is used for collecting coal from a coal conveying line in real time, crushing the coal into standard coal samples, and feeding the standard coal samples into the corresponding treatment chambers for microwave heating treatment; the microwave ashing cavity is further connected with an oxygen supply unit, and the oxygen supply unit is used for providing an oxygen-enriched environment for the microwave ashing cavity; the weight acquisition module is connected with the analysis control module and is used for acquiring the weight of the standardized coal sample before and after heating; and the analysis control module is used for controlling the microwave temperature control unit to adjust the temperature of the corresponding chamber and obtain various indexes of the standardized coal sample. According to the invention, the efficient and full-automatic microwave heating coal quality online sampling analysis effect can be realized.

The invention discloses a multi-modal AI-based contract online analysis optimization system and method, and relates to the field of contract analysis, and the method comprises the steps: obtaining a to-be-analyzed contract file, and carrying out the standardization processing of the to-be-analyzed contract file; dividing the content features of the contract file into text content features, visual layout features and logic structure features, and synchronously extracting the features; dynamically generating an analysis process path through a lightweight decision tree model, and selecting an optimal analysis engine combination; calling at least three analysis engines for parallel processing based on multi-engine collaborative analysis; correcting a conflict analysis result generated by the parallel processing analysis engine based on an attention mechanism to generate a final analysis result; and recording the accuracy rate and time consumption index of each analysis, and dynamically adjusting an analysis process generation strategy through reinforcement learning. The method has the advantages that the text, visual and logic features in the contract are extracted based on the multi-modal AI technology, and the accuracy and efficiency of contract analysis are improved through multi-engine collaborative analysis and attention mechanism correction.

The utility model discloses equipment for producing high-purity methyl ethyl ether, which relates to the field of synthesis of chemical compounds and comprises a reaction device, a heating component, a cold bath tank, a crude product receiving tank, a heavy component removal tower, a light component removal tower, a first reboiler, a second reboiler, a first condenser, a second condenser, a recovery tank, a product receiving tank and a controller, raw materials including sodium methoxide and halogenated ethane directly react under the anhydrous condition, a catalyst is not needed, crude methyl ethyl ether is produced, then the crude methyl ethyl ether enters a heavy component removal tower, crude methyl ethyl ether gas with heavy components removed enters a light component removal tower from the top of the light component removal tower after being detected to be qualified through a first online analysis and detection component, light component removal rectification is conducted, and methyl ethyl ether is obtained. Gas-phase impurities at the top of the light component removal tower are analyzed through the second online analysis and detection part, when the gas-phase impurities are detected to be qualified, the methyl ethyl ether product enters the product receiving tank, and then the high-purity methyl ethyl ether product is produced through continuous rectification, so that the product purity is high, the reaction temperature is low, the energy consumption is reduced, the reaction yield is high, and the production cost is low.

The invention relates to a rapid VOCs source component spectrum construction and evaluation method. The method comprises the following steps of S1, performing field investigation and survey to determine a target VOCs emission source, a sampling port position and a sampling mode; s2, carrying out on-site collection on a target VOCs source sample by utilizing an air bag or a Suma tank; s3, the sample is sent to a vehicle-mounted VOCs online analysis laboratory staying near a sampling source within 1-2 hours after being collected, and analysis and determination are conducted through an analysis instrument; and S4, based on the measured data of the plurality of VOCs samples of the same type of emission sources, constructing and evaluating the VOCs source component spectrum of the source type. According to the present invention, the on-site sampling and analysis determination method is adopted, the rationality of the on-site sampling method and the dilution scheme of the high concentration VOCs source sample are improved so as to achieve the detection range of the analysis instrument, and the timeliness and the accuracy of the obtained data are improved.

The invention discloses an online analysis system based on hydrogen and methane expiration monitoring, and belongs to the technical field of respiration monitoring. Comprising a zero calibration module used for obtaining a first collection environment background carbon dioxide concentration; the original signal acquisition module is used for acquiring an expiration sample; the data processing module is used for processing the original signal data stream; the signal processing module is used for outputting the filtered concentration signal; the signal compensation module is used for obtaining the compensated hydrogen and methane concentration; the secondary zero calibration module is used for acquiring a reference carbon dioxide zero point; the baseline correction module is used for carrying out baseline correction; and the model building module is used for outputting trend judgment. By means of the online hydrogen and methane expiration analysis system, the technical effect that high-concentration precision is still kept under the expiration volume fluctuation and sensor nonlinear conditions is achieved, and the problem of measurement deviation caused by volume change, nonlinear response and carbon dioxide zero drift in the prior art is solved.

The invention discloses a new media data online analysis method and device, and a server side method of a BI system comprises the steps: collecting user interaction data about a target product from a plurality of new media platforms at the same time through a preset distributed data collection architecture; extracting emotional description information capable of reflecting the emotional tendency of the user to the target product from the user interaction data of each new media platform to obtain multi-source emotional description information; inputting the multi-source emotion description information into a preset new media data online analysis component, and outputting a user emotion fusion feature corresponding to the target product; and according to the user emotion fusion features and a pre-established feature knowledge base, mining behavior pattern information and preference information of the user for the target product in a preset period, and storing the behavior pattern information and the preference information in a database of a BI system. Therefore, by adopting the embodiment of the invention, cross-platform data integration can be realized, and meanwhile, user behavior patterns and preferences can be found from a large amount of data.

The invention relates to the technical field of power equipment monitoring, and discloses a low-voltage power distribution cabinet fault monitoring system and method. According to the system, multiple paths of original operation signals are collected and preprocessed in real time to form a standard time sequence data stream, frequency domain feature extraction, transient feature capture and load fluctuation analysis are carried out, and a dynamic multi-dimensional feature reference library is constructed; iteratively calculating a feature-fault association weight based on the feature library and a pre-stored fault case graph, and establishing a dynamic mapping relation network which can be corrected in real time; according to the fault probability distribution output by the mapping network, the sampling frequency, the feature priority and the diagnosis threshold are adaptively adjusted, and an optimal monitoring strategy is formed; and finally, generating a standardized diagnosis report containing fault types, positions and severity levels through online analysis. According to the invention, comprehensive perception of fault features, autonomous optimization of a diagnosis strategy and accurate output of a fault report are realized, and the intelligent level and reliability of fault monitoring of the low-voltage power distribution cabinet are significantly improved.

The invention belongs to the field of long-chain alkane online analysis systems, and discloses a long-chain alkane online analysis method and system based on comprehensive two-dimensional gas chromatography and an aerosol thermal desorption analyzer. The method comprises the following steps: during sampling, sucking ambient air through a cyclone separator with a PM2.5 cutting head, then removing gas-phase organic matters through a multi-channel carbon remover, and then intensively collecting particulate matters to a thermal desorption unit (CTD); the analyte after thermal desorption is re-concentrated into a focusing trap (FT) at 45 DEG C; starting separation and analysis of GC * GC-MS (gas chromatography-mass spectrometry); and the separated compound enters a mass spectrometer for mass spectrometry. According to the method, the total time from pollutant collection to analysis is controlled within two hours, and the change characteristics of long-chain alkane in the generation and elimination process of a pollution event can be effectively captured.

The invention belongs to the technical field of online analysis of organic pollutants, and particularly relates to a device and a method for real-time online analysis of non-volatile organic pollutants. The device comprises a sample injection module, a vacuum ultraviolet lamp, an ionization source cavity, a repulsion electrode, an ion funnel, a mass analyzer and a vacuumizing module, the ionization source cavity is provided with a sample injection port, a vacuum extraction port and an ion output port, and the vacuum ultraviolet lamp, the repulsion electrode and the ion funnel are sequentially arranged in the ionization source cavity at intervals in the axis direction of the ion output port; the ion funnel is close to the ion output port; the sample injection module is arranged at the sample injection port; the vacuumizing module is arranged on the vacuum extraction opening; the ion output port is externally connected with a mass analyzer; a direct-current voltage is applied to the repulsion electrode, and a direct-current voltage and a radio-frequency voltage are applied to the ion funnel. According to the invention, the ions with relatively large initial distribution area can be focused, so that the detection sensitivity is further improved, and the detection requirements on trace non-volatile organic pollutants are met.

The invention relates to the field of online analysis of chemical components of materials, and discloses an online monitoring process for components of a lead frame electroplating solution, which comprises the following steps: conventionally monitoring the spectrum of the electroplating solution to calculate the concentration; calculating a spectral entropy index based on the deviation degree of the real-time spectrum and a pre-established statistical baseline model, and comparing the spectral entropy index with a preset failure trigger threshold; a dynamic calibration step is started only when the spectral entropy index exceeds the preset failure trigger threshold, the dynamic calibration step compares a physical true difference spectrum with a model virtual difference spectrum by injecting a standard pulse to generate a model error vector, and the model error vector is utilized to correct the chemometrics model, so that the stoichiometry accuracy is improved. According to the method, on-demand calibration is realized, and the consumption of the standard substance is reduced while the real-time accuracy of the model is guaranteed.

The invention discloses a battery material database construction method and system. The method comprises the following steps: manually inputting raw material and battery material information; automatically acquiring experimental data of the battery material; converting the acquired unstructured warehousing data into structured warehousing data; carrying out model training, testing and evaluation to obtain an optimized model; on the basis of the optimized model, online analysis is carried out on warehousing data, and the potential relation between the performance and the characteristics of the battery material is searched for actual prediction or classification tasks. According to the method and the system, the integrity and the richness of database information are ensured by collecting the relevant information of the whole life cycle of the battery material, a solid data foundation is laid for application, and by performing data mining and analysis on the warehousing data, the safety of the battery material is improved. And a scientific basis is provided for performance evaluation, life prediction and formulation of a personalized research and development scheme of the battery material.

The invention discloses an AI-based online data analysis method for medical molecular sieve oxygen production equipment. The method comprises the following steps: step 1, collecting multi-source operation monitoring data of the medical molecular sieve oxygen production equipment; 2, constructing a task prompt vector to obtain a normalized feature vector; 3, inputting the normalized feature vector into an improved TabPFN model to obtain a hidden space representation, and generating an enhanced representation in combination with a retrieval result of the prototype memory bank; 4, performing drift detection on the enhanced representation; 5, inputting the robust representation into a multi-task decoder; and 6, executing event label judgment, and outputting online analysis result data. According to the invention, real-time analysis of multi-source data and advanced identification of abnormal trends are realized, and the method is suitable for equipment state monitoring and risk early warning in hospital wards, rehabilitation centers and long-term oxygen supply scenes.

The invention provides an intelligent cloud testing system and method based on cloud and edge computing, and particularly relates to the technical field of automatic testing, and the system comprises a cloud service platform, an edge unit, an instrument discovery unit and message middleware. The cloud service platform manages test cases and test data in a centralized manner, provides a code-free programming tool, saves test records, and supports multiple report formats and data online analysis. The edge unit is deployed on a user site, automatically identifies test instruments and equipment, receives test cases, autonomously completes testing, pushes test data to the cloud service platform in real time, and supports offline testing. An instrument discovery unit automatically detects and configures an access instrument. And the message middleware improves the data throughput, realizes module decoupling, and is convenient for independent deployment and upgrade. The system solves the technical problems that an automatic test system is long in research and development period, poor in flexibility and difficult to deploy, and rapid construction, flexible adjustment and low-cost deployment of the automatic test system are achieved.

The invention relates to an on-line analysis system applied to a high-performance resin production line, and relates to the technical field of resin production, the on-line analysis system comprises a sampling module, a main flow path module, a rapid backflow module, an analysis detection module and a tail gas recovery processing module, resin gas can be conveyed to the analysis and detection module through the main flow path module, the analysis and detection module can detect and analyze the resin gas, and the two ends of the rapid backflow module are connected with the main flow path module and the tail gas recovery treatment module correspondingly so that part of the resin gas in a main flow path can be shunted to the tail gas recovery treatment module. And the analysis detection module is connected with the tail gas recovery treatment module so as to recover and treat the detected and analyzed resin gas. The gas flow rate is increased, the time for reaching the analyzer is shortened, the detection error is reduced, and the detection precision of the online analysis system is improved.

The invention relates to the field of agricultural intelligent monitoring, in particular to a system and method for multispectral online analysis of soil dryness and humidity based on an unmanned aerial vehicle, and the system comprises an unmanned aerial vehicle collection module, a multispectral data processing module, an analysis and modeling module and a data storage and display module. The unmanned aerial vehicle acquisition module is responsible for efficiently acquiring multispectral image data, the multispectral data processing module is responsible for performing radiation correction, geometric correction, noise filtering and spectral feature extraction on the acquired data, and the analysis and modeling module processes the multispectral data in real time and predicts soil humidity. The data storage and display module is used for storing historical data, and the soil humidity distribution condition is displayed in real time through a visual interface, so that the problem that key information of soil humidity is still difficult to efficiently and accurately extract from spectral data and accurate prediction of the soil humidity through multispectral data at present is solved. And the problem of how to maintain relatively high prediction precision under different region and environment conditions is solved.

The invention discloses a high-proportion new energy power system frequency response modeling method and application. The method comprises the steps that all nodes in a power system are divided into active nodes and passive nodes; establishing a linear power flow model of the power system; reducing the linearized power flow model to obtain an equivalent active node power flow injection power expression; frequency-active response models of various power resources in the active nodes and the passive nodes are established respectively; combining an equivalent active node power flow injection power expression with a frequency-active response model, and constructing a unified linear state space model taking an active node phase angle and frequency as state variables; and calculating the frequency response of the power system based on the unified linearization state space model. The unified linear state space model constructed by the method can realize quicker and more accurate simulation and stability analysis of the frequency dynamic state of the high-proportion new energy power system, and is suitable for quick simulation and online analysis of a large-scale system.