290 results about "Online analysis" patented technology

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 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 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 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.

The invention relates to the field of gates, and provides a gate vibration online analysis early warning method and system, and the method comprises the steps: training the historical monitoring data of a gate through a machine learning algorithm, and constructing a mapping relation between an independent variable and a dependent variable; upstream and downstream related independent variable information of the gate is obtained, and the gate vibration state is calculated online according to the mapping relation; analyzing and calculating the natural vibration frequency of the gate based on the modal analysis model of the gate; and evaluating the safety state of the gate according to the gate vibration state and the natural vibration frequency of the gate. When the system is used, the problems of data islanding, prediction lag, model distortion and low decision efficiency in the traditional technology are solved, high-precision and full-period intelligent guarantee is provided for hydraulic engineering safety, the resonance accident risk is remarkably reduced, and gate operation and maintenance management is promoted to be upgraded to the standard and unmanned direction.

The invention provides a building heating and ventilation intelligent monitoring and energy consumption final calculation method based on smart energy management and control, and relates to the field of intelligent monitoring. The intelligent building heating and ventilation monitoring system based on intelligent energy management and control comprises a data acquisition module, an intelligent analysis module and a digital twin engine module. The energy consumption final calculation module is used for obtaining calibrated equipment operation state time sequence data, carrying out itemized energy consumption calculation and multi-dimensional allocation final calculation and obtaining an energy consumption final result, and the intelligent decision module is used for carrying out online analysis on the energy consumption final result and deviation tolerance, carrying out multi-target optimization solution and obtaining an energy consumption final result. According to the invention, model updating is driven through real-time data, calibration is triggered in combination with a deviation threshold value, the problem of model drifting is solved, dynamic analysis is carried out in combination with an energy consumption final result, and the intelligent monitoring effect is remarkably improved.

The invention discloses a new energy box-type substation state abnormity diagnosis method and system, and relates to the technical field of power equipment monitoring. According to the method and the system, through event-triggered high sampling and cross-channel time base self-inspection, multi-source sequence synchronization is ensured, and a consistent time axis is provided for subsequent estimation, so that online analysis under the condition of no power outage is supported; introducing dual-path estimation of RL step fitting and voltage drop robust regression in a transient stage, cooperatively inhibiting a closing peak and outlier data, and obtaining a stable initial value of the contact resistance; in a steady-state stage, adopting Goertzel frequency selection to extract a fundamental wave phasor and performing ohmic purity judgment, and expanding to a resistance-inductance joint model when necessary to remove interference of parasitic inductive reactance on resistance estimation; and then mutual identification and residual constraint are carried out on the temperature and electric power coupling relationship by using a discrete heat RC model, and local write-back correction is carried out on the deviation, so that the consistent closed loop of the electric domain and the heat domain is realized.

The invention belongs to the technical field of power system stability analysis, and discloses a power system anticipated disturbance frequency safety on-line analysis system, a training method and an application, through a local-global double-input channel feature extraction architecture, the spatial topology correlation features and global physical characteristics of a power system are captured at the same time, and the stability of the power system is improved. And more comprehensive and essential feature expression of the frequency dynamic process is realized. The frequency response knowledge of the power system is embedded into a frequency safety online analysis system based on a guided learning training mode, and the prediction precision and generalization performance of the model under frequent change of the operation condition of the power system are remarkably improved by combining the advantages of a physical mechanism and real data. A conditional distribution-based adaptive loss function is designed as a loss function of a second stage, so that the knowledge learned by the model in the first stage is prevented from being forgotten in the second stage. The online real-time analysis requirement can be met, so that the safety of a power system is improved, and the practicability is high.

The invention provides a gas sensor low-delay classification method based on a sliding window and confidence accumulation, and relates to the technical field of gas sensing and intelligent diagnosis. The invention provides an SWSD-CAD framework aiming at the problem of high detection delay caused by dependence on a complete periodic signal of an existing temperature modulation gas sensor. According to the framework, a small window sliding detection (SWSD) strategy is adopted, and high-frequency online analysis is carried out on real-time data streams; meanwhile, continuous prediction results are arbitrated through a confidence cumulative decision CAD logic, and a final decision is made only when the prediction results continuously meet a confidence threshold within a preset time, so that the reliability of the results is ensured. In order to realize the framework, the invention designs a ConvMama hybrid network model which is used for efficiently extracting discriminative features in a short signal window. According to the invention, on the premise of ensuring high classification precision, the detection delay is obviously reduced, and early, rapid and reliable identification of gas types is realized.

The invention discloses a large power station boiler inferior coal low-nitrogen combustion optimization control system and method based on machine learning and multi-objective optimization, and relates to the technical field of coal-fired power generation and clean combustion control. The control system is composed of a combustor subsystem, a detection subsystem and a control subsystem, the combustor subsystem constructs a subarea air supply structure with stable combustion at the bottom layer, low nitrogen at the middle and upper layers and burnout at the upper part through layered combustors and OFA nozzles, and the detection subsystem completes online monitoring of coal quality and online analysis of combustion state parameters; and the control subsystem comprises coal quality adaptive decision, multi-objective optimization and closed-loop feedback. According to the control method, inferior coal is recognized through machine learning, layered air distribution is activated in a self-adaptive mode, the optimal air volume and the rotational flow angle are optimized and solved online with efficiency and NOx as multiple targets, and finally precise execution and fine adjustment are conducted through closed-loop feedback. According to the invention, wide-load stable combustion, continuous low NOx level and burnout degree improvement can be realized, and the method is suitable for engineering application of combustion of inferior coal in a large-scale unit.

The invention discloses an online monitoring and regulating system for inhibiting nitration reaction by thiourea for sewage treatment, and relates to the technical field of sewage treatment. Comprising an on-line monitoring module which monitors and obtains nitrification parameters and environmental parameters in the nitrification activity process through an on-line analyzer and a sensor network, and adjusts parameter monitoring frequency according to the nitrification parameters; the intelligent control module is used for determining optimal parameters of a PID (Proportion Integration Differentiation) controller through a virtual reference model according to the nitrification parameters and the environmental parameters, and determining the addition amount of a thiourea solution according to the optimal parameters; and the thiourea adding unit is used for adding the thiourea solution at an adding point through adding equipment according to the adding amount of the thiourea solution. According to the method, excessive inhibition possibly caused by a traditional control model based on historical data is avoided, the risk that fragile nitrifying flora is thoroughly killed is effectively prevented, success of the bacterium cultivation process is ensured, and the system starting time is shortened.

The application discloses an AI sound online analysis and identification method and system based on optical fiber sensing, which comprises the following steps: capturing sound signals of a target area by a distributed optical fiber sensing unit and converting the sound signals into optical fiber transmission optical signals, and completing photoelectric signal conversion to form an acoustic electric signal stream through a sound signal conversion transmission unit. Hierarchical voiceprint feature extraction is sequentially performed through an optical fiber voiceprint feature self-encoding model, feature refinement and redundancy elimination are realized by using a voiceprint feature distillation optimization algorithm, time sequence feature correlation is constructed through a sound signal time sequence prediction identification model, and finally online analysis and category determination are completed by a sound signal AI real-time identification engine. The application fully adapts to the characteristics of optical fiber sensing signals, strengthens the synergy of feature processing and time sequence modeling, improves the identification response speed and accuracy, effectively solves the problems of insufficient feature synergy and time sequence adaptation in the prior art, and can be widely applied to online analysis of sound signals in complex scenes such as industrial monitoring and security warning.

The utility model relates to the technical field of cold box interlayer gas oxygen content analysis, in particular to a cold box interlayer gas oxygen content on-line analysis device which comprises a sampling pump, a three-way electromagnetic valve, a pretreatment box, an analysis instrument and a control system, wherein the sampling pump is used for pressurizing and introducing interlayer gas of the cold box into the analysis device; the analysis instrument is used for analyzing the oxygen content in the pretreated gas; the three-way electromagnetic valve is arranged between the sampling pump and the analysis instrument and is used for remotely switching and analyzing the waste nitrogen and the cold box interlayer gas; the pretreatment box is connected between the three-way electromagnetic valve and the sampling pump. Through remote switching of the three-way solenoid valve and automatic logic setting of the DCS, online intelligent analysis of the oxygen content of the interlayer gas of the cold box is achieved, and the analysis accuracy and efficiency are improved; and an operator can finish the analysis work of the waste nitrogen and the interlayer gas of the cold box without frequently and manually switching an analysis instrument, so that the operation burden is reduced.

This utility model discloses a purification system for adjustable fuel gas specific gravity and calorific value, comprising a mixing tank, a primary pressurization device, a harmless treatment tower, an adsorption purification device, and an online analysis unit. The mixing tank is connected to the primary pressurization device via a pipeline, the primary pressurization device is connected to the lower part of the harmless treatment tower via a pipeline, and the upper part of the harmless treatment tower is connected to the adsorption purification device via a pipeline. The adsorption purification device is electrically connected to the online analysis unit for real-time monitoring of petrochemical gas component data entering the primary pressurization device, transmitting the data to the adsorption purification device for adjusting process parameters. The purification system for adjustable fuel gas specific gravity and calorific value provided by this utility model allows the fuel gas specific gravity to be adjusted to any desired value, which is beneficial for generating sufficient calorific value during fuel gas combustion.

The application relates to the technical field of analytical chemistry detection, and specifically discloses a rare earth ion chromatographic online analysis and detection method and system, which adopts a chromatography-mass spectrometry combined system, realizes multi-scale time-frequency decomposition of signals by constructing an adaptive wavelet base function library, accurately identifies and classifies interference types in combination with a convolutional neural network and vacuum degree coupling analysis; a U-Net generator with an attention mechanism and a multi-scale discriminator are designed for signal repair aiming at repairable interference; a state transition model containing a mass-to-charge ratio database is established, empirical mode decomposition and adaptive filtering technology are used to realize dynamic calibration of a mass axis; quantitative accuracy is ensured through double internal standard correction and a triple verification mechanism; when unrepairable interference is detected, a hierarchical self-checking program is started, and fault diagnosis is carried out in combination with spectrum fingerprint analysis.

The invention provides a performance testing method and device and a storage medium. The method comprises the steps that all executable programs of a software system submitted by a user and modified program files in the software system are received; based on the program file and all executable programs of the software system, performing a performance test to obtain a test report; and sending the test report to the user. According to the application, a user only needs to send all the executable programs of the software system and the currently modified program file to the server. And the server automatically completes the performance test of the software system and returns a test report to the user. Automatic testing of the whole process of the software system is achieved, the automation degree is high, and the testing efficiency is improved. And the test is performed only when the modified program file appears, so that the incremental performance test is realized, the performance test is more targeted, and the test efficiency and accuracy are improved. And tests in the aspects of off-line analysis, on-line analysis, integration test and the like can be carried out, and the performance test is more comprehensive, efficient and accurate.

The present application relates to the technical field of oil and gas production, in particular to a kind of crude oil production water content online analysis and measuring device, including pipeline positioning mechanism, centering clamping mechanism and lifting mechanism, lifting mechanism is arranged on the side of oil and gas pipeline, pipeline positioning mechanism and centering clamping mechanism are arranged on the lifting mechanism, when installing water content online analyzer to oil and gas pipeline, the accurate control of the installation position of water content online analyzer is realized, the setting position and inclined posture of the sensing probe of water content online analyzer in oil and gas pipeline are guaranteed.

The invention provides a method, a device and a system for rapidly analyzing components of direct coal liquefaction oil based on a near infrared spectrogram, the method comprises the following steps: acquiring sample data of the direct coal liquefaction oil, the sample data of the direct coal liquefaction oil comprises near infrared spectrum data of the direct coal liquefaction oil and detailed composition data of sample oil; according to sample data of the direct coal liquefaction oil and a ResNet-34 neural network algorithm, the near infrared spectrum of the liquefied oil with known composition is subjected to statistical treatment, the relationship between the liquefied oil composition and a spectrogram is obtained, then the near infrared spectrum spectrogram of an unknown oil product is identified to predict the composition, and a direct coal liquefaction oil component prediction model is established. The prediction model is at least used for component prediction of the direct coal liquefaction oil; the direct coal liquefaction oil in the production process is analyzed according to the prediction model obtained through training, online analysis can be rapidly and accurately conducted on the direct coal liquefaction oil, and the method can solve the technical problems that in the direct coal liquefaction oil production process, analysis is difficult, and the analysis period is long relative to the production period.

The application discloses an oil blending component oil proportioning optimization control method, system, device and medium based on soft measurement. The application predicts the quality attribute of the finished oil in real time through a soft measurement module, obtains an attribute prediction value, determines a target gain with the original proportioning data, and corrects the model gain of a multivariable controller online by using the target gain, generates adjusted target proportioning data by the multivariable controller, and issues a formula control instruction to a control device, so that the component oil proportioning is accurately adjusted. When the component oil formula or attribute changes, the application can automatically and timely adjust the controller gain, effectively overcome the nonlinearity of the blending process, improve the control precision and system robustness, thereby guaranteeing the stability of the finished oil quality and avoiding the waste of high-value component oil. By introducing the soft measurement technology, the method can replace the traditional online analyzer to a certain extent, reduce the dependence on expensive instruments, and improve the economy and maintenance convenience of the system.

The invention discloses an online analysis experiment system for simulating fluid migration and component change under multi-scene multi-medium multi-field coupling, which comprises a model unit and a fluid conveying unit, and the fluid conveying unit injects experiment fluid into the model unit. Each model unit structurally comprises a cylindrical shell with two open ends, a rubber cylinder is arranged in the shell, an annular space between the rubber cylinder and the shell is sealed, experimental fluid can be directly injected into the rubber cylinder, or experimental fluid can be injected into the rubber cylinder after a rock core or a sand filling model is placed, and a plurality of monitoring holes are formed in the side wall of the rubber cylinder at equal intervals. The sampling holes are communicated with the corresponding round pipes on the shell to serve as monitoring channels or sampling holes, and sealing covers or monitoring sensors are selectively installed on the monitoring channels. The experiment system can test and analyze fluid mixing and mixing zone change, displacement migration, component change and other conditions under multi-scene multi-medium multi-field coupling on line, for example, the experiment system is used for oil and gas displacement, gas storage injection and production simulation, underground energy storage and other experiment researches.

The utility model discloses a small-scale test device for evaluating a fixed bed catalyst, which comprises a gas feeding unit, a catalytic reaction unit, a synthetic reaction unit, a product collecting unit and a product online analysis unit, materials in the gas feeding unit are synthesized through the catalytic reaction unit or the synthesis reaction unit, then effectively separated through the product collection unit and finally detected through the product online analysis unit, and the catalytic reaction unit or the synthesis reaction unit adopts a double-channel double-temperature-control mode. And transverse contrast test is realized through different reaction temperature control modes, so that a catalytic reaction and a synthetic reaction of reactants at proper temperature and pressure are ensured, and the reaction efficiency and the product quality are improved.

The invention discloses an electric energy meter with an abnormal state online analysis function, and belongs to the technical field of electric energy meters. The control module is arranged in the electric energy meter body; and a plurality of mounting cavities are arranged. According to the electric energy meter with the abnormal state on-line analysis function, through the use of the detection mechanism, the modular design capable of being independently disassembled and assembled is adopted, the telescoping of the positioning block is controlled by rotating the supporting disc, the rapid locking or releasing of the detection sensor in the mounting cavity is realized, a professional tool or complex operation is not needed, the difficulty and time of field maintenance are obviously reduced, and the working efficiency is improved. The operation and maintenance efficiency is improved, flexible configuration of sensor types is supported, different monitoring requirements are met, a heat dissipation system is automatically triggered through cooperative use of the ejection mechanism and the flow control mechanism, when the detection sensor is installed in place and the butt joint is connected with the butt joint seat, the flow control motor starts fan blades to perform forced air cooling, and the working temperature of the sensor is effectively reduced.

The invention relates to the technical field of remote sensing, in particular to a remote sensing image on-line analysis processing system, which comprises an identification module used for acquiring a target remote sensing image and corresponding auxiliary geographic data; the correction module is used for correcting the target remote sensing image; the processing module is used for optimizing the correction result of the target remote sensing image; through multi-source data fusion, efficient storage, an adaptive correction model and a real-time error feedback mechanism, the problems of low precision, poor efficiency and insufficient complex scene adaptability in traditional remote sensing image processing are solved, high-precision and high-efficiency online analysis processing is realized, and the application value of the remote sensing image is remarkably improved.

This invention discloses a simulation device for hydrothermal reactions under vacuum chamber dehydration accidents, belonging to the field of vacuum chamber accident simulation technology. The device includes a quartz tube with its opening facing upwards, an induction heating coil wound around its exterior, and a detachably sealed end of the quartz tube via a flange assembly. A water injection pipe extending from the lower end of the flange assembly to above a metal sample is connected to a storage tank. The flange assembly also has an outlet pipe communicating with the inner cavity of the quartz tube, which is connected to a mass spectrometer analysis unit via a liquid nitrogen cold trap. The middle section of the outlet pipe is connected to a vacuum pumping unit via a vacuum pumping pipe. A monitoring unit is located on one side of the quartz tube. This invention integrates vacuum acquisition, induction heating, controllable coolant injection, in-situ monitoring, and online analysis of gaseous products, achieving comprehensive simulation of the high-temperature metal-coolant hydrothermal reaction process under vacuum chamber dehydration accidents. It is suitable for preliminary research on vacuum chamber dehydration accidents in fusion devices, high-temperature high-vacuum furnaces, and other similar applications.

Systems and methods for golf analysis including a tag coupled to a golf club providing statistical analytics for coaching including text, tabular, graphic, and image-based outputs that include trends information for the golfer, all based upon actual golf play on course situations, wherein the golfer inputs shot data during play, without interrupting the flow of the game, and uploads the shot data for analytics and review online, and wherein all information related to a given user are reviewable by an authorized coach user through a web-based coach access account. The system is further operable to provide the coach user rights for providing corrective or instructive feedback to the user, including visual recommendations such as modified target areas.

The application discloses a system and method for detecting SF6 gas decomposition products based on a spectrum method, and the system comprises an SF6 gas and decomposition product collecting device, a gas sample pool, a high-purity argon gas bottle, a laser device, an argon gas collecting pool, a spectrum analysis and detection device and a gas recharging device; the SF6 gas and decomposition product collecting device, the high-purity argon gas bottle, the laser device, the argon gas collecting pool, the spectrum analysis and detection device and the gas recharging device are all connected with the gas sample pool; the gas sample pool is embedded with a one-side wideband total reflection mirror and a quartz window sheet, the wideband total reflection mirror is symmetrically provided with a first arc-shaped total reflection mirror and a second arc-shaped total reflection mirror which are perpendicular to the wideband total reflection mirror, and the quartz window sheet is opposite to the wideband total reflection mirror; and the spectrum analysis and detection device collects scattered light through the quartz window sheet. The application has high detection sensitivity, fast detection speed and can realize real-time online analysis and detection.

The application provides an aero-engine bleed air component test system, which comprises a bleed air flow path, an ambient air flow path, a bleed air online analysis device and an ambient air online analysis device. The bleed air flow path is connected with the bleed air online analysis device and used for analyzing the components of the engine bleed air. The ambient air flow path is connected with the ambient air online analysis device and used for analyzing the components of the ambient air. The test system further comprises a switching flow path, which is connected with the bleed air flow path and the ambient air flow path. In a first test state, the switching flow path is closed, the engine bleed air in the bleed air flow path enters the bleed air online analysis device, and the ambient air in the ambient air flow path enters the ambient air online analysis device. In a second test state, the switching flow path is opened, and the ambient air in the ambient air flow path enters the bleed air online analysis device.

The invention discloses a pilot operated safety valve state monitoring method and device with helium online leakage detection, and relates to the technical field of industrial process safety and equipment state monitoring, and the method comprises the steps: installing a microcavity leakage collection module on a to-be-detected pilot operated safety valve, connecting a helium online analysis subsystem and a tracing gas source through a pipeline, and carrying out the detection of the helium online leakage detection of the to-be-detected pilot operated safety valve; starting a vacuum pump set to vacuumize to a working vacuum degree; pure nitrogen is introduced to eliminate background helium, sampling analysis is performed after an interface is closed, and a helium background signal is recorded as a base line; low-concentration helium mixed gas is injected at a controlled speed, a tracing environment is constructed, and helium concentration, pressure and temperature multi-dimensional time sequence data are synchronously collected and preprocessed; inputting the data into a composite artificial intelligence model to judge a leakage state and divide alarm grades; the leakage rate is analyzed, the remaining life is calculated, monitoring information is uploaded to an upper-layer system, multi-channel notification is triggered, and monitoring is completed. Through the helium mass spectrum and the edge AI technology, accurate real-time monitoring is achieved, and the problem of off-line lag misinformation is solved.

The invention discloses a composite nondestructive testing and analysis system based on an electromagnetic effect and AI vision, belongs to the technical field of nondestructive testing, and aims to solve the technical problems that in the prior art, electromagnetic testing and vision testing work independently, data space and time are not synchronous, so that surface and subsurface defect information is separated, and effective correlation judgment cannot be achieved. In-situ synchronous acquisition and data alignment of the electromagnetic sensor and the visual sensor are realized through the multi-field fusion acquisition module; performing feature-level adaptive fusion on the heterogeneous data by using a dual-path deep network in the intelligent fusion analysis module; defect identification and positioning are completed by means of a real-time online analysis module; and the closed loop feedback control module dynamically adjusts a detection strategy according to a result to form an intelligent verification closed loop. According to the invention, integrated, high-precision and self-adaptive intelligent detection and comprehensive judgment of'surface-near surface-subsurface 'multi-level defects of the workpiece are realized.