258 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 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 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 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.

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 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 provides a file co-processing method and system based on distributed multithreading and dynamic sub-libraries, and relates to the technical field of file data processing, and the method comprises the steps: obtaining a to-be-processed file, and generating a file list according to batch information; a production-consumer model is adopted, a producer main thread scans a file list, a task queue is generated, a consumer thread pool concurrently executes downloading tasks, and the maximum concurrency number is controlled through semaphore; file data are uniformly distributed to a plurality of physical storage nodes on the basis of a fragment routing algorithm, real-time updating of a mapping relation between fragments and instances is managed by utilizing a dynamic routing table, resources are preferentially allocated to high-priority file tasks on the basis of a service routing strategy, and the tasks are dynamically allocated to specified database fragments; multi-file parallel processing on a processing node is realized through a three-stage parallel model, dynamic Feign calling is carried out on a service instance dynamic route and a weight load, multi-state table state synchronous updating is carried out based on a two-stage state machine, and a processing log is saved.

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.

An electronic modal base valve is disclosed. The electronic modal base valve includes a motive component, a controller communicatively coupled with the motive component, and a control valve coupled with the motive component. The control valve includes a multi-state rotary spool. The controller is configured to control an operation of the motive component, wherein a movement of the motive component is configured to cause the control valve to adjust a flow rate for a flow path through the electronic modal base valve. The multi-state rotary spool has a softest setting, a lockout setting and at least one intermediate setting for the flow rate along the flow path.

The application discloses a kind of autonomous ship operating state evaluation methods considering multi-state component degradation, establishes the function control structure of autonomous ship in remote control mode, and determines the multi-state safety function of autonomous ship subsystem and system risk function, to obtain the time of predicted guarantee response, the time of backup response and the critical time when system risk exceeds the critical state system risk level set, to evaluate the operating state of autonomous ship in remote control mode.The application can more accurately capture the unique risk control process of autonomous ship through the function control structure of system in multiple operating states and the interaction mechanism between multi-component subsystems, and provides basic support for scientific risk management strategy and decision-making process in autonomous ship operation, and provides theoretical support for preventing autonomous ship from deviating from operating boundary.

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.