346 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 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 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 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.

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 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 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.

The invention relates to the technical field of automobile part cutting, in particular to an automobile part cutting table which comprises a control cabinet, a first transferring set, a second transferring set and a lifting mechanism are arranged on the upper side of the control cabinet, a cutting assembly is arranged on the side face of the lifting mechanism, and a clamping assembly is arranged on the upper side of the control cabinet in a mirror image mode. The clamping assembly comprises an electric rotary table, a multidirectional mechanical arm and an electric clamping jaw, and clamping blocks are arranged on the side face of the electric clamping jaw in a mirror image mode. According to the cutting table module assembly, the clamping assembly and the cutting assembly are arranged, the cutting table module assembly with multi-state cutting and self-adaptive clamping can be integrated, single-laser, single-water-jet-cutter and water-laser mixed cutting operation can be carried out on spare and accessory parts made of different materials and in different shapes, meanwhile, the spare and accessory parts made of different materials and in different shapes can be adaptively clamped, and the cutting table module assembly is convenient to use. The clamped materials can be subjected to multidirectional position adjustment to be matched with cutting, in addition, independent adjustment operation can be carried out during single-laser cutting and single-water-jet cutting, and efficient and high-precision machining operation of spare and accessory parts is met.

The invention discloses a track fusion method for incremental updating of a Gaussian mixture model and multi-state transition filtering, and relates to the technical field of track fusion, and the method comprises the steps: carrying out the preprocessing of observation information of a radar and electronic reconnaissance equipment; obtaining a feature vector of the observation information and performing target category identification to obtain a target category label set; generating an initial track of the observation subset by using a multi-correlation gate and a cost function; identifying track pairs with potential interaction and / or conflicts from the initial track set to form a target track set without intersection and / or interference; based on a plurality of preset state transition models, using the track quality score set and the sensor weight set to obtain a track fusion result; on the premise of considering the real-time performance and the precision, the cross track and the high maneuvering target are efficiently processed based on the range and performance difference of multiple sensors, and key filtering and associated parameters are adaptively adjusted according to the change of the environment and the sensor state, so that the continuous and accurate tracking of the target track information is realized.

The invention discloses an unmanned aerial vehicle battery replacement scheduling system and method based on multi-state battery prediction, particularly relates to the technical field of unmanned aerial vehicle battery management, and is used for solving the problems of insufficient energy of an inspection unmanned aerial vehicle and mismatching of battery replacement decisions. According to the method, multi-source data such as voltage, current, temperature, internal resistance and environment wind speed are collected, key states such as charge, health, power, energy and temperature are extracted, state feature vectors related to task context are formed, and task energy consumption and return energy are estimated based on a prediction model. A scheduling instruction for continuing tasks, going to a charging station or a battery swap station, maintaining charging and cooling fast charging is generated, in a battery swap scene, an improved ant colony algorithm of a battery health factor is introduced to construct a path cost function, distance, energy consumption and time are considered, optimal battery swap station selection and safe path planning are achieved, and the optimal battery swap efficiency is improved. And the energy management precision and the task stability of the unmanned aerial vehicle inspection task are obviously improved.

The invention relates to an intelligent power grid and artificial intelligence, in particular to a non-intrusive load detection method and system based on multi-state power consumption and machine learning, and the method comprises the steps: obtaining electric appliance level power consumption data; preprocessing the data; feature extraction and fusion; and classifying load anomalies. According to the scheme, the high generalization ability can be kept while the electricity stealing detection accuracy is improved, the integrated power consumption sequence and the electric appliance power consumption matrix are received at the same time to serve as input, the household overall electricity consumption information and the single equipment level characteristics are organically fused, and therefore more comprehensive modeling and analysis of the electricity consumption behavior of a user are achieved, and the user experience is improved. And the capability of identifying abnormal behaviors such as electricity stealing is enhanced.

The invention discloses a control mode smooth switching method for a multi-port flexible multi-state switch, and the method comprises the steps: carrying out the Udc-Q control of any port of the flexible multi-state switch during grid-connected operation, and carrying out the PQ control of other ports; when a certain port is off-grid due to a feeder line fault, smoothly switching to a VSG control mode through state tracking control, and providing voltage and frequency support for a power-losing area; after the fault is cleared, the voltage amplitude, the phase and the frequency of the VSG are synchronized with a power grid through synchronous control, smooth grid connection is achieved, any port of the flexible multi-state switch comprises a grid-connected controller and an off-grid controller, Udc-Q control and PQ control in the grid-connected controller share a current loop and a reactive loop, and the switching complexity is reduced; the off-network controller adopts VSG control; in the state tracking control, the state tracking quantity is introduced into the inputs of different controllers in a negative feedback form, so that the bidirectional tracking of the output states of the controllers is realized. According to the invention, the cooperative control of the multi-port flexible multi-state switch and the smooth switching of any port control mode can be realized, and the transient impact at the switching moment is reduced.

The invention discloses a measuring result stability analysis method and system of a metering instrument, and relates to the technical field of time sequence data analysis. The method comprises the steps of measurement data flow alignment, measurement result stability baseline feature construction, three-state feature decomposition and measurement result stability analysis of the metering instrument. Extracting repeatability features, trend features and structural features of the measurement result, and constructing a measurement result stability baseline feature vector; a three-state feature decomposition method based on baseline constraint is adopted to decompose the stability change of the measurement result into a drift feature, a noise feature and a jump feature; comprehensively analyzing the stable state and the change trend of the measurement result of the metering instrument based on the baseline feature and the tri-state feature decomposition result; according to the method, the stability of the measurement result of the metering instrument can be subjected to refined and cause-distinguishable analysis under the complex working condition and the multi-state operation condition, and a reliable basis is provided for the evaluation of the operation state of the instrument and the judgment of the credibility of the measurement result.

This application discloses an intelligent method and apparatus for detecting active speech with sentence segmentation based on multi-state temporal modeling. The method includes: receiving audio signals from at least one channel; extracting acoustic feature sequences from the audio signals using a target speech recognition model corresponding to the number of channels; determining the probability distribution of each speech frame corresponding to the acoustic feature sequences belonging to different speech activity states, obtaining a state sequence corresponding to each channel, wherein the speech activity state includes at least one of the following: initial silence state, speech state, intra-turn pause silence state, and inter-turn sentence segmentation silence state; and determining the time of sentence segmentation in the audio signal based on the state sequence. This application solves the technical problem of erroneous sentence segmentation in speech activity detection based on a fixed silence threshold in related technologies.

The invention discloses a multi-state N-out-of-K power generation system reliability detection method based on a parallel architecture. The method comprises the following steps: firstly, establishing a multi-state reliability function corresponding to each element in the large-scale N-out-of-K power generation system by using a general generation function method; then, according to the multi-state reliability function corresponding to each element, multi-state reliability functions corresponding to subsystems from the first hierarchy to the (A-1) th hierarchy of the power generation system are calculated in sequence by utilizing a multi-layer parallel subsystem construction method; and then, based on the multi-state reliability function corresponding to the (A-1) th hierarchy subsystem, generating the reliability of the large-scale N-out-of-K power generation system by adopting a general function generation method, and completing the detection of the reliability. According to the method, the multi-state reliability function of each subsystem is subjected to parallel calculation by adopting a parallel method, so that the time accumulation effect in traditional serial calculation is avoided, and the time period of reliability detection of the large-scale N-K power generation system considering parallel elements is shortened.