171 results about "Multi state" patented technology

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 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 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 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.

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 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 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.

The invention provides a transformer internal partial discharge detection method, device and equipment and a storage medium, and belongs to the field of transformer monitoring, and the method comprises the steps: obtaining an ultrahigh frequency electric signal, an optical signal and an acoustic signal generated by transformer internal partial discharge through an ultrahigh frequency sensor, an optical sensor and an optical fiber Fabry-Perot ultrasonic sensor; a multi-state quantity integrated sensing SoC chip on the circuit board is used for conditioning and digitizing the signals to generate a digitized signal flow; inputting the signal flow into a state sensing special edge computing NPU chip, processing the signal flow by using a graph attention network algorithm, calculating an attention coefficient between sensor nodes, and fusing the multi-modal signals to generate a fusion signal; and determining the partial discharge type according to the fusion signal. According to the invention, three sensors are internally integrated, signal conditioning digitalization is carried out by using the SoC chip, multi-mode signals are fused through the NPU chip, high-precision and high-reliability identification is realized, and the difficulty of an external sensor is overcome.

A system for electroporation ablation including an electrode assembly and a catheter having one or more states. The electrode assembly may be of different shapes when the catheter is in the different states. The controller is configured to generate a graphical representation of an electric field generated by the electrode assembly when the catheter is in the different states based on one or more models of the electric field. In some embodiments, the controller is configured to overlay the graphical representation of the one or more electric fields on an anatomical map of the patient.

The invention discloses a lithium battery cross-working-condition multi-state joint estimation method which only needs single identification and does not need offline OCV data, and belongs to the technical field of lithium ion batteries. The method comprises the following steps: firstly, acquiring experimental data of a lithium battery in a reference state, constructing a fractional order physical model to be identified, then, carrying out synchronous identification operation on parameters and OCV based on quasi-static hypothesis, and establishing an analytic mapping relation between model parameters and SOC in the reference state; based on the mapping relationship, constructing an adaptive fractional order model fusing a linear migration mechanism and an internal resistance anchoring characteristic; and through an adaptive fractional order model, constructing a lithium battery SOC and capacity joint estimation framework based on a unified augmented state space and a sparse information injection mechanism, and completing joint estimation. According to the method, the high dependence on repeated parameter identification and offline OCV experimental data in the prior art is effectively overcome, the problem of error diffusion caused by multi-state coupling is solved, and the engineering applicability of the model is remarkably improved.

The invention relates to a lithium battery module temperature estimation method based on a multi-state electrothermal coupling model, and relates to the technical field of lithium battery temperature state estimation. Constructing a multi-state electrothermal coupling model of the single battery, wherein the multi-state electrothermal coupling model comprises an RC second-order equivalent circuit model and a multi-state equivalent thermal network thermal model; constructing a hierarchical integrated multi-state electrothermal coupling model of the battery module by connecting each single electric model in series and additionally arranging a conductive thermal resistor between each single electric model to describe heat exchange between adjacent batteries; performing parameter identification on the integrated model by adopting an improved overall cluster optimization algorithm; and based on the model after parameter identification, combining an adaptive unscented Kalman filter which dynamically adjusts noise covariance by adopting an exponential weighted moving average algorithm, and carrying out real-time estimation on the internal and surface temperature states of the battery module. According to the method, the temperature estimation precision and the long-term operation robustness of the battery module under the complex working condition are remarkably improved through the steps.

The invention discloses a photovoltaic hydrogen production grid-connected system and method based on multi-state cooperative scheduling, and relates to the field of new energy comprehensive utilization. The system solves the problems of unstable operation of an electrolytic bath, low comprehensive utilization rate of energy, poor economic benefit and the like caused by intermittency and volatility of photovoltaic power generation in the prior art. The system comprises a photovoltaic power generation unit, an energy storage unit, at least one electrolytic bath unit, a hydrogen storage unit and a controller. The controller monitors the photovoltaic power generation power, the charging state of the energy storage unit and the hydrogen storage state of the hydrogen storage unit in real time, and executes the following operations according to a preset multi-state cooperative scheduling strategy: starting the electrolytic cell units in a grading manner according to a photovoltaic power threshold value; the energy storage unit is used for smoothing photovoltaic power fluctuation and stably supplying power to the electrolytic cell; in addition, on the basis of two independent triggering conditions that the energy storage unit reaches the upper limit or the hydrogen storage unit reaches the upper limit, surplus electric energy of the system is dynamically sold in a grid-connected mode. The device is also suitable for the fields of integrated photovoltaic power generation, electrochemical energy storage and water electrolysis hydrogen production.

This invention relates to the field of transportation device technology, and discloses a multi-state transportation device with reconfigurable load-bearing boundaries and its state transition method. The transportation device includes a main structure, a deformable support unit movable relative to the main structure, and a movable support component associated with the deformable support unit. The deformable support unit can move between a concealed state and an expanded state. In the concealed state, the movable support component is at least partially located within the outer boundary range formed by the main structure, giving the device a neatly defined concealed profile. In the expanded state, the movable support component moves beyond the outer boundary range and participates in defining the load-bearing boundary range in the expanded state, realizing the switching of the movable support component from a boundary-inward state to a boundary-outward support state. Through the movement of the deformable support unit, the load-bearing boundary composition of the device changes, and the movable support component transforms from a concealed entity within the boundary to a boundary builder, thereby achieving load-bearing boundary reconfiguration. The device can form a concealed form, a transportation form, a platform form, and / or a desktop form. This invention solves the problems of exposed wheel sets, irregular concealment, and the need for separate disassembly and assembly of the movable support component in existing folding transportation devices, and has the advantages of compact structure, convenient state transition, neat boundaries, and high functional integration.

Embodiments of the present application provide a soft mute control method and device for a radio device, a medium and a product. By extracting the spectral deviation feature and the time domain energy feature of the digital audio signal of the radio device, the spectral deviation feature can reflect the frequency spectrum similarity between the signal and the noise, and the time domain energy feature can reflect the signal strength. Combined with multi-state decision and energy decision, multi-dimensional decision of the signal state is performed to realize accurate identification of the signal state, and then the output gain is dynamically adjusted. Compared with the prior art, not only the signal receiving strength index is relied on for adjustment, but also the problem of large and small sound caused by signal strength fluctuation due to position change is avoided. The spectral deviation feature is used to effectively distinguish between effective signals and noise, improve the accuracy of soft mute decision, and the time domain energy feature is used as auxiliary decision to enhance the reliability of the system in a low energy scene, so that the volume is smooth and continuous, and the user's radio experience is improved as a whole.

The invention provides a zinc pot stabilizing roller adjusting device and method capable of achieving accurate positioning. According to the invention, through a multi-state cooperative control model, a dual accurate positioning system of induction distance measurement and scale visual feedback, and execution mechanisms which are independently or synchronously adjusted on two sides, rapid, accurate and quantifiable adjustment among a working position, a critical position and an exit position of the front stabilizing roller is realized. The device comprises a sink roll, a rear stabilizing roll, a front stabilizing roll, a front stabilizing roll supporting arm, a front stabilizing roll beam and two sets of symmetrically-arranged adjusting devices, and the adjusting devices drive lead screw shafts through gear motors, convert rotary motion into linear motion of supporting seats and drive the front stabilizing roll beam and the front stabilizing roll to move accurately. According to the invention, electric automatic adjustment is realized, the adjustment precision, response speed and stability are improved, the running stability of strip steel and the uniformity of a zinc coating are ensured, and meanwhile, the safety of a working environment is improved.

Embodiments of the present disclosure relate to a multi-state control interface between a control plane and a user plane in a disaggregated broadband network gateway architecture. The present invention provides a disaggregated broadband network gateway (DBNG) control plane system that can receive an association setup request message from a DBNG user plane device, wherein the association setup request message is received through a state control interface between the DBNG control plane system and the DBNG user plane device. The DBNG control plane system can determine one or more capabilities of the DBNG user plane device based on the association setup request message, and can cause one or more additional state control interfaces to be established between the DBNG control plane system and the DBNG user plane device as a result. The DBNG control plane system and the DBNG control plane system can communicate messages associated with a first message type through the state control interface, and can communicate messages associated with a second message type through at least one of the one or more additional state control interfaces.

This invention relates to the field of transportation device technology, and discloses a multi-state transportation device and its state transition method that features automatic deployment triggered by a lift. The transportation device includes a main structure, deformable units movable relative to the main structure, and a movable support assembly associated with the deformable units. By applying a lifting force to the main structure, relative motion is created between the main structure and the deformable units, triggering the deformable units to exhibit a self-deploying tendency relative to the main structure under gravity, and to move in the deployment direction under constraint guidance. The deformable units drive the movable support assembly from a receiving position to a ground support position to support the main structure off the ground, thereby transforming the transportation device from a receiving state to an extended state. This invention utilizes lift triggering, gravity drive, and structural constraint guidance to achieve automatic deployment. Users can trigger state switching with a single lifting action, offering advantages such as simple operation, smooth deployment, good structural compatibility, and coordinated deployment of the left and right deformable units.

This invention discloses a method and system for stability analysis of metrological instrument measurement results, relating to the field of time series data analysis technology. The method includes measurement data stream alignment, construction of baseline features for measurement result stability, three-state feature decomposition, and stability analysis of metrological instrument measurement results. Repeatability, trend, and structural features of the measurement results are extracted to construct a baseline feature vector for measurement result stability. A three-state feature decomposition method based on baseline constraints is used to decompose the stability changes of the measurement results into drift, noise, and jump features. Based on the baseline features and the three-state feature decomposition results, a comprehensive analysis of the stability state and changing trends of the metrological instrument measurement results is performed. This invention enables refined and causally distinguishable analysis of the stability of metrological instrument measurement results under complex operating conditions and multi-state operation, providing a reliable basis for instrument operating status assessment and measurement result reliability judgment.

This invention discloses a fully passive jammer and a fully passive jamming method for channel knowledge map scenarios. The jammer includes: a data acquisition module for generating a multi-state channel dataset by traversing and controlling the configuration of a reconfigurable smart metasurface and performing channel simulation; a map construction module for constructing a channel path map based on channel state information; a beamforming parameter determination module for determining fixed hybrid precoding parameters based on the channel path map in an interference-free reference scenario; and a performance evaluation module for reusing the fixed precoding parameters and calculating the communication rate based on the real channel state in a dynamic scenario with disco-type reconfigurable smart metasurface interference, thereby quantifying performance loss. This invention transforms dynamic interference into an analyzable channel sequence through multiple simulation sampling, separates beam selection from rate evaluation, objectively quantifies mismatch penalties, and provides a standardized evaluation platform for countermeasure research on disco-type reconfigurable smart metasurfaces.

This invention discloses a method for constructing a multi-state model of hydropower units that takes into account load temporal fluctuations. It focuses on the impact of regional time-period water inflow restrictions and system safety constraints, corrects the outage characteristics of the hydropower unit model within a fixed period, correlates the outage characteristics of the units with load locations, and converts the unit failure rate into a dynamic calculation process. Simultaneously, considering the impact of system safety constraints, it optimizes the unit commissioning sequence under the constraints of system ramp-up capacity reserve and spinning reserve, obtaining richer system operation information, including system reliability indicators, safety margin indicators, and unit start-up and shutdown frequency, providing a reference for power system safety assessment.

The application provides a 10GBase-T physical layer synchronization and equalization method and device, which realizes fast capture of a PN training sequence in PN synchronization by using iteration interaction of a multi-state equalizer and a PN synchronization algorithm; meanwhile, the multi-state equalization method in the equalizer has a high multiplexing degree and an inheritance characteristic of equalization training results on hardware, which can greatly reduce hardware overhead of a synchronization and equalization module in 10GBase-T and significantly improve convergence speed of equalization training; further, with training convergence of filter coefficients in the equalizer, the quality of equalization output signals is continuously improved, and input of the equalization output results to the PN synchronization module will further improve stability of PN synchronization tracking and reduce step-out probability.

The subject matter of the utility model is a multi-state indicating device and an electrical system. A multi-state indicating device (10), comprising a first polarizer (11); a liquid crystal panel assembly (20) comprising a first liquid crystal panel (21) configured, in use, to enable incident light (40) having a first polarization state from the first polarizer (11) to propagate through the first liquid crystal panel (21); a second polarizer (12); a pattern layer (30) having a predetermined first pattern (31), the pattern layer (30) being positioned such that, in use, the first pattern (31) receives incident light (40) having a second polarization state from the second polarizer (12) and the first pattern (31) reflects the incident light (40) having the second polarization state towards the second polarizer (12), the reflected incident light (40) sequentially passes through the second polarizer (12), the first liquid crystal panel (21) in the first operation mode, and the first polarizer (11).

The invention discloses a multi-state network irregular minimum cut set vector identification and prevention method, which comprises the following steps: constructing a multi-state network according to an actual network system, and obtaining all minimum cut sets MC and demand levels d; according to the demand level, the edge maximum state and the minimum cut set capacity, whether repeated d-MCs exist or not is judged, and therefore the state upper limit of the edge under the minimum cut set is calculated in a self-adaptive mode; calculating a state lower limit of each edge in the multi-state network; based on a preset repetition-free d-MC search rule, searching for all candidate d-MCs; and carrying out authenticity verification on all the candidate d-MCs, rejecting unreal candidate d-MCs, and taking the remaining candidate d-MCs as real d-MCs. The method is applied to the field of reliability evaluation of the multi-state network, can eliminate the need of deleting a single step of repeating the d-MC, eliminates redundant conditions of non-real d-MC verification, and obviously improves the identification efficiency of the d-MC.

This invention relates to the field of intelligent monitoring technology for power equipment. To address the problems of isolated cable condition monitoring parameters, difficulty in deeply correlating with fundamental insulation aging indicators, and fuzzy anomaly location, a multi-state low-power sensing system for distribution cables is disclosed. This system acquires cable sheath temperature, discharge waveform, and insulation loss data through an information acquisition module; a condition generation module processes the data to obtain comprehensive cable condition characteristics; a weight learning module uses a trained anomaly representation learning network to generate an anomaly weight spectrum reflecting the correlation strength between operating conditions and insulation loss; a source tracing and location module performs dual-source anomaly trajectory backtracking analysis on the original temperature and discharge data based on this weight spectrum, achieving precise location of the anomaly's physical location and identification of its inherent defect type; and a parameter optimization module generates and executes a control parameter adjustment scheme. This invention achieves deep correlation assessment of cable insulation status and precise physical-level diagnosis of anomaly root causes.

The application discloses a kind of dynamic multi-energy coupling and conversion comprehensive energy system reliability evaluation method.Establish the multi-state reliability model of multi-energy production element considering dynamic multi-energy coupling, establish the multi-state reliability model of multi-energy conversion element considering dynamic multi-energy conversion, establish the multi-state reliability model of multi-energy transmission element considering dynamic multi-energy coupling, according to the multi-state reliability model of three kinds of elements, the multi-state reliability model of three kinds of subsystems is constructed;According to the multi-state reliability model of three kinds of subsystems, the reliability of comprehensive energy system considering multi-energy coupling and conversion is obtained by using improved general production function method, and reliability evaluation is realized.The dynamic characteristics of the comprehensive energy system can be more accurately characterized by using the multi-state model, and the reliability of the comprehensive energy system that meets the accuracy requirements is accurately calculated.

The application discloses a kind of multi-energy coupling and conversion comprehensive energy system multi-state reliability evaluation method.Establish the multi-state reliability model of multi-energy conversion element considering multi-energy conversion, using clustering algorithm reliability aggregation, and mapping formation aggregated multi-state reliability model;Multi-state reliability model of multi-energy coupling element considering multi-energy coupling is established, and then using Gaussian approximation and sampling approximation reliability approximation processing in sequence obtains multi-state approximate reliability model;The aggregated multi-state reliability model and multi-state approximate reliability model are processed according to the fast reliability evaluation method to obtain the reliability of the comprehensive energy system, and the reliability evaluation is realized.The application improves the traditional reliability evaluation method from time and accuracy, reduces the calculation time, and quickly and effectively realizes the estimation of system reliability.

This invention discloses a method for identifying unipolar and bipolar depression based on deep learning-based multi-state EEG fusion, comprising: Step 1, performing continuous wavelet transform on EEG signals in open and closed states respectively to obtain open-eye time-frequency maps and closed-eye time-frequency maps; Step 2, using a deep learning model to extract features from the open-eye and closed-eye time-frequency maps obtained in Step 1 to obtain feature vectors for open-eye and closed-eye states; then, fusing the feature vectors in open-eye and closed-eye states to obtain a multi-state fused feature vector; finally, using a deep learning classification network to classify and identify the multi-state fused feature vector to obtain the identification result, thus completing the identification. This invention uses a deep learning model based on EEG signals to perform three-class classification identification of unipolar depression, bipolar disorder, and healthy individuals, improving classification performance.