405 results about "Multi state" patented technology

The invention discloses a nuclear radiation index early warning system based on multi-algorithm fusion, and the system comprises an environment data collection module which is used for collecting gamma-ray dose rate data, wind speed data, wind direction data and geographic position information, and constructing a nuclear radiation environment data set; the dose rate prediction module is used for predicting a future change trend of gamma ray dose rate data based on a sparse recurrent neural network model; the anomaly detection module is used for identifying an abnormal mutation point and positioning the position of a high-risk sensor; the diffusion region modeling module is used for calculating a nuclear radiation diffusion influence region; the grid risk evolution module is used for simulating time sequence evolution of a regular grid risk state based on the multi-state cellular automaton; and the fusion judgment module is used for fusing output results and generating a final early warning grade and a spatial risk distribution result. According to the invention, accurate prediction of the nuclear radiation risk and dynamic space early warning are realized, and the early warning accuracy and response efficiency are significantly improved.

The invention discloses a semiconductor packaging device electromagnetic compatibility comprehensive test method and system, and belongs to the technical field of electromagnetic compatibility testing. The method comprises the following steps: collecting structure parameters, packaging topology and predefined function states of a to-be-tested packaging device, and constructing a polymorphic working model; establishing a disturbance injection control model according to each state and configuring disturbance source parameters; implementing dynamic disturbance injection and acquiring response data in a real working state of the device; performing time domain and frequency domain conjoint analysis on the response data, constructing an electromagnetic response dynamic feature sequence, inputting the electromagnetic response dynamic feature sequence into a machine learning model, extracting multi-dimensional coupling features and predicting tolerance; calculating performance indexes such as an interference tolerance score and a coupling strength index based on model output indexes, comparing the performance indexes with a standard, and evaluating a compatible risk level in a full state; the method realizes quantitative evaluation of the EMC performance of the packaging device with high reduction degree and multi-state coverage, and has the advantages of comprehensive test, accurate prediction, explainable attribution and the like.

The invention relates to the technical field of ring main unit monitoring, and discloses a ring main unit online monitoring system based on multi-state quantity sensing. The system comprises an acquisition module used for acquiring a temperature signal and a partial discharge signal and obtaining state quantity data; the calibration module is electrically connected with the acquisition module and is used for preprocessing and calibrating the state quantity data; the analysis module is electrically connected with the calibration module and is used for performing multi-dimensional analysis on temperature and discharge characteristics; the transmission module is electrically connected with the analysis module and is used for data transmission and fusion processing; the early warning module is electrically connected with the transmission module and is used for performing multi-stage early warning analysis; and the adjusting module is electrically connected with the early warning module and is used for dynamically adjusting the monitoring parameters. According to the invention, accurate evaluation and timely early warning of the equipment operation state are realized, and the technical problems of low accuracy and poor adaptability of a single state quantity monitoring method are solved.

The present invention relates to adaptive multi-state encoding and processing in virtualized computing environments. The system includes a virtualized state selection module that dynamically transitions between binary, ternary, quaternary, and higher-order encoding states based on workload, bandwidth, security posture, and compliance requirements. A virtual encoding engine utilizes hardware-accelerated components, such as vFPGAs, vGPUs, and cTPUs, to enhance encoding throughput. A compliance-driven feedback controller continuously monitors encoding efficiency, threat levels, and adherence to mandates such as GDPR, HIPAA, and FIPS 140-3. Additional features include AI-based anomaly detection, federated model refinement, distributed ledger-backed audit trails, and quantum-resistant encoding techniques. By integrating intelligent encoding decisions with scalable compliance enforcement, the system enables high-performance, secure, and regulation-ready data processing across distributed cloud and edge environments, delivering measurable improvements in system responsiveness, data integrity, and operational trust.

The invention discloses a GIS disconnecting switch multi-state intelligent sensing system, and relates to the field of GIS disconnecting switch state monitoring. A self-calibration multi-mode sensor is deployed for multi-source data acquisition, and novel sensors including terahertz imaging and the like are included; in data preprocessing, deep learning noise reduction is applied, fuzzy entropy is used for dynamic weighted fusion, and abnormal values are processed by an improved algorithm; feature extraction is combined with a plurality of frontier algorithms to process vibration signals, and CRNN is used to analyze acoustic signals; the QPSO evidence theory is adopted for state fusion perception, the node relation is learned by means of GNN, and the weight is adjusted according to the information gain rate; state assessment and early warning are based on transfer learning, GAN and LSTM-attention mechanisms, and early warning priorities are ranked by FAHP. According to the invention, multi-mode accurate acquisition, intelligent data processing, deep feature mining, innovative fusion perception, accurate evaluation and early warning and efficient fault diagnosis and positioning are realized, the state of the GIS isolation switch can be comprehensively and accurately perceived, the system is self-learned and optimized, the equipment safety is guaranteed, the risk of a power system is reduced, and the power operation and maintenance benefits are improved.

The invention discloses a GIS online monitoring method based on multi-state quantity integration, and relates to the field of GIS online monitoring, and the method comprises the steps: deploying an array composed of an ultrahigh frequency sensor, an ultrasonic sensor, a gas density sensor, an optical fiber temperature sensor and a vibration sensor based on a GIS equipment cavity structure zone; the method comprises the following steps: synchronously acquiring an ultrahigh-frequency electromagnetic wave signal, an ultrasonic signal, a gas density signal, a local temperature signal and a shell vibration signal in an operation process of GIS equipment so as to obtain a multi-dimensional original state quantity sequence; according to the method, multiple types of sensors are accurately distributed and controlled for the GIS cavity structure partition, and through time alignment, adaptive weight fusion and time-space convolution feature extraction, hidden dangers such as a partial discharge source can be accurately positioned, and a state quantity can be predicted by means of a correlation evolution equation. Meanwhile, mechanisms such as sensor fault automatic elimination and complementation, prediction accuracy verification and the like guarantee data reliability, equipment states can be mastered in real time, and faults can be warned in advance.

The invention discloses a reliability evaluation method for a micro-grid power distribution system based on a Bayesian network and a sequential Monte Carlo method, and the method comprises the steps: building a micro power supply multi-state combination output model according to the operation state of a power distribution element; carrying out load partitioning on the load in the microgrid through a multi-target particle swarm optimization algorithm; calculating a load output time sequence problem, and enabling the micro-grid distributed power supply to be equivalent to a piecewise function; carrying out analogue simulation on the wind speed and the illumination intensity by adopting an improved ARIMA (Autoregressive Integrated Moving Average), and establishing a time sequence composite model; calculating the ratio of the weekly load to the annual maximum load, the ratio of the daily load to the weekly maximum load, and the ratio of the load per hour to the daily maximum load; establishing a logic relation graph of each node through a Bayesian network, and establishing a time sequence source-load change model; in combination with the time sequence composite model and a time sequence source-load change model, sampling each node of a system element, and judging an operation state; and performing simulation analysis on the reliability index of the power distribution system to obtain a final result. The method can be used for improving the power supply performance by improving the reliability of the fixed-point weak link.

The invention discloses a coordination control method for energy storage and a flexible multi-state switch in a power distribution network system, and relates to the field of power supply and distribution. The hierarchical control mode is adopted to coordinate the energy storage system and the flexible multi-state switch; the coordination control layer performs working mode selection and switching in a networking operation mode by a centralized controller according to the feeder load power, the charge state of a storage battery, the operation state of each transformer and the position and the number of feeder faults; the control strategy of the flexible multi-state switch can be changed among a constant DC voltage control strategy, a constant power control strategy and a droop control strategy; the control strategy of the storage battery can be switched among constant-current charging control, floating charging control and constant-voltage control; and the feeder load in the equipment control layer can also realize a load switching control strategy. By adopting the coordination control method, the power supply reliability and the power quality of the system can be improved.

The invention provides a positioning method, device and equipment based on multi-state color consistency constraint, which can be applied to the technical field of computers. The method comprises the steps of performing imaging simulation on a positioning point based on a three-dimensional position of the positioning point in a three-dimensional point cloud, and determining an imaging position of the positioning point in a current frame image; correcting an initial object state corresponding to the current frame image based on a projection position and an imaging position of the positioning point in the current frame image to obtain a corrected object state, and obtaining a corrected object state based on a plurality of historical poses of the inertial measurement tool, a plurality of observation colors of the positioning point, a current color of the positioning point in the three-dimensional point cloud and a color noise distribution parameter; correcting the state of the corrected object to obtain the state of the target object; and determining the target pose of the positioning object based on the state of the target object, so as to at least partially solve the technical problem of poor positioning effect in related technologies, and achieve the technical effect of improving positioning robustness and precision.

The invention relates to the technical field of storage and transportation monitoring, in particular to a green hydrogen production, storage and transportation integrated real-time operation monitoring method and system, and the method comprises the following steps: S1, respectively setting intelligent sensor networks in a hydrogen production link, a hydrogen storage link and a hydrogen transportation link of green hydrogen production, storage and transportation, and collecting the operation state data of each link in real time; s2, performing multi-state cooperative monitoring based on the operation state data of each link, and performing linkage monitoring on a plurality of state variables in the hydrogen production, hydrogen storage and hydrogen transportation processes; s3, constructing a multivariable model, and describing a nonlinear coupling relationship among a plurality of state variables in the links of hydrogen production, hydrogen storage and hydrogen transportation; and S4, designing a multi-state cooperative control algorithm based on the nonlinear coupling relationship described in the multivariable model. According to the method, control failure caused by simple linear hypothesis is effectively avoided, and particularly, relatively high prediction precision can be kept for state variables of nonlinear coupling.

The invention discloses a lithium battery dynamic rapid charging track generation method based on multi-state estimation and risk criterion, belongs to the technical field of electric vehicle lithium ion battery charging, and aims to solve the problem that the charging speed, the energy efficiency and the battery life are difficult to consider in the rapid charging process of a lithium ion battery in a wide temperature range. And a relatively high lithium plating safety risk exists. The method comprises the following steps: firstly, constructing an electrochemical thermal aging coupling model, and establishing a lithium plating risk criterion and risk map based on the model; then, on-line multi-state estimation is realized based on an electrothermal coupling equivalent circuit model, and a multi-objective optimization function and a safety constraint system which comprehensively consider charging time, energy efficiency and life loss are constructed; and finally, a model prediction control framework is utilized, a state estimation result and a risk criterion are fused, and an optimal charging current track is generated in a real-time rolling manner.

The invention relates to the technical field of aircraft path planning, and particularly provides an aircraft path planning method for a space non-cooperative target. The method comprises the following steps: constructing an aircraft dynamics model and constraint conditions, and obtaining a non-convex optimal control problem; performing discretization processing on a non-convex optimal control problem through a non-equal-interval pseudo-spectrum discrete optimization model, and converting the non-convex optimal control problem into a fixed-time nonlinear programming problem about discrete nodes; according to the method, a fixed time nonlinear programming problem is convexed to form a convex sub problem, a local optimal solution of a non-convex optimal control problem is obtained through sequence iteration, under the multi-state constraint, path planning of an aircraft approaching a space non-cooperative target is achieved, the problem of no feasible solution caused by non-accurate linearization is solved, and the method is suitable for being applied to a non-cooperative target. And the convergence rate of the algorithm is accelerated.

The invention discloses a ship loading and unloading hose curvature intelligent monitoring system, which relates to the field of intelligent monitoring and comprises a panoramic view acquisition module, a panoramic image fusion module, a simulation driving analysis module, a multi-state parallel architecture module and a hose early warning analysis module. The panoramic view acquisition module is used for acquiring visual acquisition information; the panoramic image fusion module is used for performing multi-dimensional non-overlapping splicing fusion processing on the visual collection information to obtain three-dimensional hose visual information; the simulation driving analysis module performs simulation driving processing on the ship loading and unloading process according to the three-dimensional hose visual information to obtain a corresponding fault parameter data set; the multi-state parallel architecture module is used for setting a corresponding target node for the three-dimensional hose visual information and carrying out space-time fusion processing on state data in the target node to obtain corresponding state information; the hose early warning analysis module is used for performing verification early warning analysis on the state information corresponding to each target node; therefore, the monitoring accuracy in the use process of the hose is improved.

The invention discloses a braking control optimization method and system combined with vehicle multi-state perception, and belongs to the technical field of vehicle intelligent control, and the method comprises five steps of multi-source data acquisition, data preprocessing, multi-state risk modeling, multi-target braking force distribution and braking control optimization. Based on a tire dynamic model and a semantic physical double-source weighting mechanism, generating high-precision vehicle multi-state sensing feature data; a multi-state risk modeling method based on path prediction and a physical constraint model is combined with a dynamic risk weight adjustment mechanism to calculate a comprehensive target deceleration; a multi-objective optimization function including the braking distance, the stability and the tire reliability is constructed, and four-wheel braking force distribution and coaxial cooperative control are carried out; and pressure control is executed according to the optimization result, and brake control optimization is achieved. According to the method, real-time self-adaptive adjustment of the brake control strategy can be achieved under the complex environment and multiple working conditions, and the safety, stability and response precision of braking are improved.

A phase shifter cell and multiple coupled phase shifter cells that mitigate signal glitches arising from phase state changes by a combination of design architecture and control signal timing. Specifically, one or more of the following three concepts are employed to mitigate insertion loss glitches and control phase behavior during phase state transitions: the timing of switching for each switched half-cell (e.g., including series and / or shunt reactance elements, such as inductors and / or capacitors) within a phase shifter cell is controlled in such a way that the reactance elements do not all switch at the same time; use of a “make before break” timing scheme for combination or “multi-state” phase shifter cells; and / or arranging the timing of each phase shifter cell in a set of multiple coupled phase shifter cells such that the individual cells do not all switch at the same time.

The invention provides an automatic steering driving humanoid trajectory planning method and system. The method comprises the following steps: acquiring relative distance information between a vehicle and obstacles on two sides of a road and vehicle kinematics information by acquiring and processing human control data in a curve scene; non-linear features are extracted from the vehicle kinematics information based on a kernel principal component analysis (KPCA) method; the multi-state cycle prediction model is constructed based on an LSTM network, and the method comprises the following steps: carrying out weighted attention on key data of long and short term information by cell state information; the model inputs the nonlinear features, the relative distance information between the vehicle and obstacles on the two sides of the road and the kinematics information of the vehicle into a multi-state cycle prediction model, and predicts future driving track points. Therefore, the mapping precision of the network is improved, human manipulation behaviors are well learned, and the stability of the planned trajectory is improved.

The invention discloses a technical scheme of a submarine pipeline health assessment method and system based on multi-state quantity data fusion, and the method comprises the steps: improving the defect classification precision while reducing the dimensionality through dynamic balance global variance retention and local discrimination enhancement; and a solution with high efficiency and robustness is provided for feature fusion and accurate evaluation of the multi-source high-dimensional pipeline data. The submarine pipeline health assessment method comprises the following steps: collecting monitoring data of a sensor in a submarine pipeline, the monitoring data including but not limited to stress strain, acceleration, vibration and temperature in the submarine pipeline; carrying out fusion and dimension reduction processing on the obtained multi-source heterogeneous data, and finding out a mutual relation of changes among parameters of the submarine pipeline in the same time period; calculating a pipeline damage condition coefficient and a repair index according to an analysis result of the multi-source heterogeneous data; and dividing repair grades according to the repair indexes, comprehensively judging the health state of the submarine pipeline, and giving a repair suggestion.

The utility model discloses a flexible load regulation and control framework based on a three-port flexible multi-state switch. The flexible load regulation and control framework comprises the three-port flexible multi-state switch, a first power grid module, a second power grid module and a third power grid module, the first power grid module, the second power grid module and the third power grid module are electrically connected with one another through a three-port flexible multi-state switch; the three-port flexible multi-state switch at least comprises a state A, a state B, a state C and a state D; in the A state, the first power grid module, the second power grid module and the third power grid module are mutually independent; in the B state, one power grid module in the three power grid modules is independent, and the other two power grid modules are in bidirectional power flow transfer connection; in the C state, two power grid modules in the three power grid modules are connected with the other power grid module in a tidal current transfer mode; in the D state, one power grid module in the three power grid modules is connected with the other two power grid modules in a tidal current transfer mode; and the power flow regulation and control flexibility and flexible load power supply reliability of the power distribution network are improved.

The invention discloses an energy storage detail data acquisition and compression control method based on batch stream fusion, which relates to the technical field of data compression control, and comprises the following steps: obtaining operation state parameters of an energy storage system, and carrying out state perception and hierarchical mapping on the energy storage system to obtain state levels; based on a deep reinforcement learning method, performing adaptive adjustment in combination with the state level to obtain a compression control parameter; according to the compression control parameters, compression control strategy adjustment and feedback optimization are carried out on the energy storage system based on a fuzzy reasoning method; according to the method, adaptive adjustment of the compression strategy is realized by constructing the running state potential function and combining deep reinforcement learning and fuzzy reasoning, and the problems that the compression strategy of an existing energy storage system is fixed, regulation and control response is lagged and the control precision is insufficient under the multi-state working condition are solved.

The invention belongs to the technical field of electric power system dispatching optimization and electric power and electric quantity balance analysis, and relates to a time sequence random production simulation method considering a flexibility demand in an electric power market environment, which comprises the following steps: 1, constructing an electric power system time sequence-random production simulation framework considering the flexibility demand in the market environment; 2, the upper layer model obtains a start-stop scheduling scheme by taking the minimization of the total operation cost of the system as a target, calculates the time sequence flexibility supply capability of each type of unit, and provides an input basis for the lower layer; 3, constructing a multi-state flexibility supply model of the unit under different time scales in a lower layer model, carrying out multi-time scale system flexibility supply and demand probabilistic matching by adopting an equivalent electric quantity function method, and realizing flexibility index evaluation under a short time scale; 4, converting and solving the model; according to the invention, support is provided for coordinating the operation economy and flexibility of the system under security constraints.

The invention belongs to the technical field of EL system control, and discloses a preset performance control method considering dynamic and constraint of an execution mechanism. The method comprises the following steps: firstly, establishing a system dynamics model considering dynamic and input saturation constraints of an executing mechanism; then, designing an asymmetric tubular performance boundary to restrain a system tracking error, and defining a conversion error according to the system tracking error; meanwhile, a disturbance observer based on immersion and invariance is designed, and composite disturbance is estimated. Furthermore, a tubular preset performance controller is designed by adopting a backstepping method, a virtual control law and an expected torque are constructed, and a multi-state auxiliary system is introduced to compensate the input saturation influence. And finally, a control instruction is generated by integrating the auxiliary system state, the virtual control law, the expected torque and the interference estimation value, and the control instruction acts on the system after being processed by a saturation function. According to the method, actuator dynamics, input saturation and external disturbance can be processed at the same time, and tracking errors are ensured to strictly follow a preset performance boundary.

An image sensor with one or more imaging sensor layers and / or one or more color filter layers is provided. Imaging sensor layers sense different combinations of wavelengths of light depending in part on filtered light passing through the color filter layers. The color filter layers, which can be tunable filters, plasmonic color filters or dielectric subwavelength grating filters, allow certain colors of light to pass through to the imaging sensor layers and block others. The image sensor is connected to control circuitry that measures the properties of light received at each imaging sensor layer, reconstructs the color components of each pixel of the imaging sensor layers based on these measurements, and generates full-color image data from the color components. Methods of manufacturing the image sensor are also provided using lithography and securing the layers in a sensor stack using a bonding substrate.

The invention provides a circuit breaker monitoring method and system based on multi-state sensing, a medium and equipment, and relates to the technical field of electrical equipment monitoring. According to the technical scheme provided by the invention, the initial influence weight of the directed edge is dynamically updated into the target influence weight according to the weight adjustment rule corresponding to the event type of the operation event, so that the fault propagation map accurately reflects the actual change of the influence relationship of the current operation event on the components. And calculating the first node health degree of each node based on the updated target influence weight and the multi-dimensional state data, accurately evaluating the current health state of the circuit breaker, predicting the second node health degree within the duration of the operation event, and realizing the pre-judgment of the development trend of the health state. According to the first node health degree and the second node health degree, the monitoring mode is determined, and the early warning response of the corresponding level is triggered, so that the timeliness and pertinence of early warning are ensured, and the accuracy of monitoring and early warning of the circuit breaker can be improved.

The invention belongs to the technical field of lithium ion batteries, and provides a power battery multi-state collaborative estimation method and system based on a large language model, and the method comprises the steps: initializing the large language model; aging feature extraction is carried out under the random charging behavior, and window extreme voltage and accumulated charging amount are extracted as aging features; based on the initialized large language model, determining input and output of the model according to a multi-state collaborative estimation task, fusing the extracted aging characteristics with battery state parameters to jointly serve as input characteristics, and adjusting an input type; inputting and outputting a base model, improving a large language model, and adding an output layer module for the large language model to adapt to a multi-state collaborative estimation task; based on the improved large language model and the actual data set, adopting a low-rank adaptation method to finely adjust the model; and processing the target fragmented charging data based on the fine-tuned model, and carrying out multi-state collaborative estimation. According to the invention, multi-state collaborative accurate estimation can be realized.

The invention discloses a stability control strategy test system and method applied to a field stability control device, and the system comprises a test host which is configured to be in communication connection with a stability control host of a stability control master station; the at least one test slave computer is connected with the test host computer and is deployed in a distributed manner to simulate a stability control substation; and the software control system is connected with the test host and is used for analyzing the strategy file, extracting strategy logic from the strategy file, decomposing test steps into a multi-state test template, generating strategy test items, executing the strategy test items according to a preset sequence and dynamically modifying a soft pressing plate and a control word of the stability control host through an MMS protocol. Through distributed communication control of the test host and the test slave, comprehensive simulation of an interface of the field stability control device is realized, and comprehensive test of the field stability control device is realized by simulating all communication signals of the stability control device, reading and identifying a stability control strategy and producing batch stability control test strategy test items. And a new technical means is provided for on-site stability control device testing.

A portable fluid tank system can include wireless control capabilities. The portable fluid tank system can include a fluid tank with an internal volume for fluid storage and a fluid actuation system for controlled fluid movement and pressurization. An electronics housing within the portable fluid tank system can accommodate a removable energy storage device, providing power to the actuation system. The portable fluid tank system can include a multi-state control interface, facilitating direct user interaction or remote operation via a wireless communication module. The module can receive and execute commands from a remote transmitting device, enabling remote activation and control of the fluid actuation system.

An image sensor with one or more imaging sensor layers and / or one or more color filter layers is provided. Imaging sensor layers sense different combinations of wavelengths of light depending in part on filtered light passing through the color filter layers. The color filter layers, which can be tunable filters, plasmonic color filters or dielectric subwavelength grating filters, allow certain colors of light to pass through to the imaging sensor layers and block others. The image sensor is connected to control circuitry that measures the properties of light received at each imaging sensor layer, reconstructs the color components of each pixel of the imaging sensor layers based on these measurements, and generates full-color image data from the color components. Methods of manufacturing the image sensor are also provided using lithography and securing the layers in a sensor stack using a bonding substrate.