43results about How to "Avoid mismatch" patented technology

This application discloses a method, device, and electronic device for displaying energy flow in a power plant, belonging to the field of new energy power plant technology. The method includes: generating an energy flow diagram corresponding to the current power plant configuration and displaying it on an interface; the energy flow diagram includes multiple visual elements, each visual element including at least source nodes and carrier nodes representing power plant equipment, and path elements representing the energy flow relationship between source nodes and carrier nodes; responding to user interaction with any node or path element, determining the energy path where the interacted node or path element is located; updating the rendering state of the energy path on the interface to make the energy path appear locally focused relative to other energy paths. This application achieves energy path-level visualization and interactive analysis based on power plant equipment topology, improving the accuracy of expressing power plant energy flow relationships and the efficiency of analyzing multi-dimensional operational data.

The application provides an intelligent inventory control management method and system based on a supply chain cooperation mechanism, applied to the technical field of supply chain management, preliminary demand prediction of a downstream partner is received, demand intention information containing customization component possibility weight and potential demand range is generated according to the prediction, after the upstream supplier receives the demand intention information, the influence of the demand intention information on future production resources is further evaluated, an evaluation result is obtained, finally, according to the evaluation result, the method performs flexible preparation in advance, including production window soft reservation, upstream material pre-communication and special mold preparation, effectively coping with the supply uncertainty of the customized components, avoiding the dilemma of standard component overstock and customized component shortage, realizing lean production and on-time delivery, and bringing significant economic benefits and competitive advantages to enterprises.

This invention discloses a semi-physical simulation platform and control system for a dispensing machine, comprising: a mechanical execution module: simulating nozzle deformation through a quantum dispensing head virtual environment to generate first physical data, and integrating a rigid-flexible coupling platform and a laser interferometer to capture high-speed trajectory pose deviations to generate second physical data; a digital hydraulic drive module: simulating fault repair dynamics using a converter pump and a quantum attenuator to generate third physical data; an edge-cloud collaboration module: constructing a twin based on an FPGA-quantum architecture to generate fourth physical data, and generating fifth physical data through transfer learning AI algorithms to optimize hydraulic pump and valve strategies; a global monitoring and diagnostic module: constructing a multi-physical quantity model through fiber optic-quantum sensors to generate seventh physical data to evaluate wide-temperature-range stability, and generating sixth physical data; and a simulation comprehensive management module: evaluating the platform's stability under wide-temperature-range and complex vibration scenarios.

This invention discloses a comprehensive management method for transparent inspection of power grid materials based on the Internet of Things (IoT), belonging to the field of power material management technology. The method includes the following steps: deploying a three-axis vector probe array at the material entry channel to collect multi-point spatiotemporal signals and calculate the field strength distribution, generating an electromagnetic disturbance spatiotemporal matrix, and outputting a radio frequency identification (RFID) tag resonance drift risk matrix. This invention models electromagnetic disturbance sources using a three-axis vector probe array, combines resonance registration fingerprinting and frequency band compensation to achieve dynamic correction of RFID frequency drift, and integrates phase-encoded backscattering and strain acoustic features to ensure identification consistency. By utilizing optical time reference synchronization and phase-programmable metasurfaces to reconstruct the near-field environment, an adaptively adjustable identification space is constructed, improving the identification stability and traceability reliability of power grid materials under high-disturbance environments, thus breaking through the bottlenecks of traditional identification technologies.

This application relates to the field of gas sensor packaging technology, specifically to an automated packaging method, system, and packaging device for gas sensors. The method includes: pre-establishing a packaging process parameter-gas-sensitive channel adaptation model; calculating the actual coaxiality deviation and correcting the sealing pressure reference value based on the gas-sensitive channel aperture; starting the integrated packaging unit, applying pre-pressure according to the corrected sealing pressure, and simultaneously collecting the temperature of the sealing area through an infrared temperature measurement module to determine whether dynamic adjustment of the welding temperature is needed; after welding, maintaining the corrected sealing pressure, and dynamically adjusting the pressure holding time based on the gas-sensitive channel length and the creep coefficient of the sealing material to complete the sealing process. This application achieves a precise balance between sealing performance and conduction efficiency by establishing a dynamic adaptation model of process parameters and gas-sensitive channel structure, overcoming the coupling imbalance bottleneck of existing technologies.

The application discloses a kind of conformal array rotation interference amplitude-phase error correction design methods, first, construct rotating array signal receiving model, according to the radius of rotating platform and angular velocity calculation rotating guide vector, construct rotating array channel amplitude-phase error model, correction source incident signal information acquisition, record the rotation angle of precision turntable;Covariance matrix is solved to the received data and eigenvalue decomposition, construct amplitude-phase error calculation equation;Solve amplitude-phase error matrix, construct amplitude-phase error correction matrix and correct the received data;Solve adaptive weight vector, and weighted output is carried out to the corrected data.The application compared with traditional array amplitude-phase error correction scheme, system structure is simple and easy to realize, without specific algorithm can be completed to the amplitude-phase error caused by array receiving channel is accurately corrected, effectively solve the receiving channel mismatch problem, improve array anti-interference performance.

This invention discloses an ultrasound-guided minimally invasive Achilles tendon suturing navigation device, belonging to the field of medical device technology. It includes a clamp body structure and two navigation mechanisms. The clamp body structure includes a connecting shaft, a clamp handle, and clamp heads. The clamp handle and clamp heads are connected by the connecting shaft. The clamp heads are located on the clamp handle, and there are two clamp handles and two clamp heads. The two navigation mechanisms are located on the two clamp heads respectively, and the two navigation mechanisms on the two clamp heads are interconnected. In use, ultrasound is used preoperatively to determine the course of the sural nerve and its accompaniment to the small saphenous vein to avoid intraoperative injury. During the procedure, the position and thickness of the Achilles tendon are confirmed under ultrasound guidance. Simultaneously, the navigation mechanism is passed through the Achilles tendon at an appropriate position, fixed, and the needle core is removed. Finally, the suture is passed through a cannula.

This application discloses a liquid level control device and a liquid cooling cabinet for automatically adjusting the liquid level inside the liquid cooling cabinet to prevent the liquid level from being too high or too low. The liquid level control device is applied to a liquid cooling cabinet, which includes a cabinet body, a first inlet pipe connected to a liquid supply pipe, and a first outlet pipe connected to a return pipe. The device includes: a liquid level monitoring device installed inside the cabinet body, a control valve installed on at least one of the first inlet pipe and the first outlet pipe, and a controller. The controller is used to acquire liquid level detection data from the liquid level monitoring device and adjust the opening of the control valve according to the liquid level detection data.

This invention belongs to the field of triple mode redundancy (TMR) technology, and particularly relates to a selective TMR conversion method and system based on two-stage decoupling. The method includes acquiring the Verilog design code to be converted and parsing the circuit signals; calculating the dynamic activity of each circuit signal, dividing the circuit signals into critical and non-critical circuit signals, and forming a list of critical circuit signals; reading the list of critical circuit signals, traversing each assignment statement in the Verilog design code to be converted, and identifying whether the current circuit signal is a critical circuit signal; performing TMR operation on the identified critical circuit signals, and using logical assignment to make the replica signals track the original signals in real time for the identified non-critical circuit signals, thus completing the selective TMR conversion. This invention completely decouples the two stages of dynamic activity analysis of circuit signals and selective conversion of source code, and performs true / pseudo-TMR splitting processing.

The application discloses a liquid level height automatic calculation method and system based on spectral characteristics, a medium and equipment, and particularly relates to the technical field of container liquid level automatic calculation and dynamic monitoring. The method improves the algorithm through spectral curve change point detection, accurately captures the spectral feature difference between gas phase and liquid phase through spectral sequence modeling, introduces the running length index and dynamic updating mechanism, filters out the real gas-liquid interface change point through the multiple check mechanism to filter the false change point, infers the type according to the mean difference before and after the change point and the running length change, takes the clear mutation point or the midpoint of the gradual transition zone as the interface, combines the pixel resolution and the bottom starting position, and obtains the actual liquid level height through formula calculation, establishes the conversion relationship between the pixel quantity and the actual liquid level height through the proportional relationship between the image axis pixel number and the absolute height of the container, and finally takes the average value of the calculation results of three wave bands as the absolute height of the liquid level based on the pixel number of the spectral curve feature point.

This application provides a digital grading method and apparatus for paper-based assignments. The grading method includes: performing adaptive partitioning on an assignment image containing student information to obtain a question area and an answer area; the answer area includes an objective filling area and a subjective writing area, wherein the subjective writing area includes a handwritten text area and a handwritten formula area; based on the content characteristics of the target area, calling a detection and recognition model that matches the content characteristics to obtain the recognition result of each answer area; for fuzzy recognition results of the subjective writing area, introducing the writing style characteristics of the current student information to correct the fuzzy recognition results, and updating the recognition results of the subjective writing area based on the correction results; comparing the final recognition results of each answer area with the assignment answers to generate and output the grading results. The grading method and apparatus of this application form a fully automated process from image input to grading result output, requiring no manual intervention and achieving effective automatic grading.

The present application belongs to the field of blast furnace system health management and prediction, and specifically discloses a blast furnace degradation model calibration and residual life prediction method under a noise environment. The method is based on a fractional Brownian motion with historical dependence, constructs an initial degradation model of the blast furnace system, estimates the model parameters by the maximum likelihood estimation method, and determines the optimal model structure of the blast furnace system temperature change by the Akaike information criterion. In addition, the present application also designs a model calibration trigger mechanism; when the mechanism is not triggered, the Bayesian fusion particle filter is used to estimate the potential degradation state of the system and update the model parameters; when the mechanism is triggered, a prediction error model is constructed and the degradation model structure is calibrated to adapt to complex working conditions. Finally, the probability distribution function of the residual life of the blast furnace system is derived, and the residual life prediction of the blast furnace system is carried out according to the calibrated degradation model.

This invention discloses a landmark matching PDR positioning method in multi-intersection scenarios, belonging to the field of indoor positioning technology. The method enhances landmark credibility by constructing landmarks through multi-dimensional information perception. Simultaneously, by adaptively extracting landmarks with different spatial features, this method is applicable to various landmarks, such as some unconventional intersections. Furthermore, this application uses different thresholds to define the radius of influence of different landmarks, solving the localization system mismatch problem caused by traditional single-location detection of landmarks, thus improving positioning accuracy to a certain extent. This application also further improves positioning accuracy by incorporating heading weights into trajectory similarity metrics, achieving dual correction of the position and heading of moving targets.

The present application relates to the technical field of intelligent dry ice production hydraulic control, a dry ice production hydraulic control method and system based on multi-sensor cooperation, the method comprising: confirming a dry ice production hydraulic control environment based on a dry ice production hydraulic control instruction, performing hydraulic pressure on the dry ice raw material based on a hydraulic cylinder, collecting data based on a multi-source sensing unit, time-synchronizing multi-source information to obtain synchronized multi-source information, analyzing the synchronized multi-source information based on an intelligent analysis and decision unit, calculating a target flow based on a working condition stage, calculating a compensation pressure based on a pipe cross-sectional area and the target flow, performing comparative analysis based on synchronized real-time pressure, synchronized output flow, the target flow and the target pressure, and obtaining a reversing valve control instruction based on the working condition stage. The present application can improve the precision, efficiency, reliability and energy utilization rate of dry ice production hydraulic control.

The present application relates to the technical field of animal-related pattern recognition in image / video data, and particularly relates to a multi-source information fusion intelligent recognition method and system for sheep health monitoring. The method first obtains a pair of visual data through synchronous verification and pairing of visible light and infrared acquisition units, and screens high-quality data through preprocessing and quality verification. Then, features are extracted, redundant and weakly distinguishable features are removed, and the fusion weight is dynamically adjusted in combination with the feature consistency coefficient to obtain fused features. Finally, the prediction result is obtained through hierarchical decision fusion, the sheep health and emotional state are determined based on the confidence, and the state duration is combined for grading early warning. The method ensures efficient fusion of multi-source information, improves recognition accuracy, ensures timely and accurate early warning, adapts to the needs of fine monitoring of large-scale breeding, reduces breeding risks, and improves efficiency.

The present application relates to a kind of FDA-MIMO radar incremental distance-angle joint estimation method, comprising the following steps: using the echo data of FDA-MIMO radar to establish the signal model of incremental distance and angle;Incremental distance information and angle information in signal model are separated, and the decoupling model of FDA-MIMO radar incremental distance and angle is established;Based on decoupling model, define the two-dimensional atom norm of FDA-MIMO radar target incremental distance and angle, the minimum problem of two-dimensional atom norm is converted into the first semi-positive programming problem, and the first semi-positive programming problem is used as parameter estimation function;Based on parameter estimation function, the incremental distance estimation value and angle estimation value of target are calculated.The method can directly estimate the incremental distance estimation value and angle of target in continuous domain, the method does not need to carry out grid division to space domain, can solve grid mismatch problem, effectively improve the precision of parameter estimation result, improve the efficiency of parameter estimation.

The present application relates to the technical field of pedal data processing, and particularly relates to a method and system for replacing pedal data in a playing file. The method comprises: obtaining a playing file of a piece of music; obtaining a score file corresponding to the piece of music; generating an insertion node according to the score file and a pedal insertion rule, and / or according to the playing file, wherein the pedal insertion rule comprises a chord rule; selecting replacement data of a pedal in response to a selection signal of a user, wherein the selection signal comprises a specified style or a specified pedal file; and inserting the replacement data into the insertion node to form a new playing file. The present application can meet the demand of users who want to reference pedal data of others by replacing pedal data, and greatly improves the efficiency of music production, teaching assistance, performance analysis and the like.

This application discloses a current calibration loop and method for current calibration of a current-controlled DAC. The current calibration loop includes: a selected reference current source and a selected current source to be calibrated; a clamping management module that clamps the output nodes of the two sources to the same fixed potential to discharge the static current of the two output nodes in different calibration modes, retaining only the current difference; an error comparison module that amplifies the current difference into a voltage difference and outputs the comparison result; a calibration control logic module that generates a calibration control signal based on the comparison result; and a calibration module that injects error compensation current into the output nodes according to the calibration control signal, so that the compensated output current of the selected current source to be calibrated is equal to the reference current provided by the selected reference current source. By discharging most of the static current and retaining only the current difference for comparison, it can respond promptly to a wide current range, significantly improve the current calibration accuracy, and adapt to various calibration modes.

This invention relates to a NOMP-based RIS-assisted millimeter-wave MIMO system channel estimation method, belonging to the category of channel estimation methods. Taking the downlink of a RIS-assisted millimeter-wave MIMO system as an example, the channel model of the base station (BS)-RIS and the RIS-mobile station (MS) is represented as a concatenated channel model in Khatri-Rao product form. One-dimensional NOMP, two-dimensional NOMP, and least squares (LS) algorithms are used to estimate multiple parameters in the concatenated channel, thereby achieving channel estimation. The advantages are that the proposed RIS-assisted millimeter-wave MIMO system channel estimation method estimates channel parameters with lower pilot overhead, providing effective CSI for RIS-assisted systems; applying the NOMP method to RIS-assisted millimeter-wave MIMO channel estimation can solve the grid mismatch problem existing in traditional compressed sensing algorithms, improve the accuracy of joint parameter estimation, and thus improve the channel estimation accuracy.

The application provides a dynamic management and intelligent dispatching method for power distribution network repair work orders under extreme disasters, and relates to the field of power distribution network emergency management and information technology. The method comprises the following steps: obtaining extreme disaster monitoring data; when the extreme disaster monitoring level reaches the warning level, an audit request of a special repair strategy is pushed to the command end; after receiving the confirmation instruction of the command end, the method automatically switches to the extreme disaster emergency repair mode, constructs a multi-factor fusion model, extracts the social influence factor, fault disposal difficulty factor and team intelligent matching factor corresponding to the repair work order, and calculates the dynamic priority score of the work order; the method matches the best recommended repair team information for the repair work order and generates an intelligent dispatching suggestion sheet, which is pushed to the command end; the repair work order is pushed to the mobile terminal of the best recommended repair team, and the repair work order is received, applied for transfer, and grabbed, so as to realize automatic disaster sensing, intelligent analysis and decision-making, resource optimization and allocation, and precise and efficient dispatching.

The application provides an energy efficiency service deployment and delivery method and system for an edge computing network, and relates to the technical field of edge computing.The method comprises the following steps: extracting multi-dimensional service features, encoding and fusing the extracted multi-dimensional service features to generate a global context feature representation; combining system load dynamic prediction results to adaptively adjust an upper-layer decision time scale based on the global context feature representation; executing service deployment decisions and base station sleep / activation switching decisions under the adjusted upper-layer time scale; executing service delivery decisions and resource allocation decisions based on real-time service requests under a fine-grained lower-layer time scale; and coordinating the decision-making process through a double-time-scale hierarchical learning framework.The method can effectively reduce long-term network overhead, effectively respond to dynamic service requests, improve the processing capacity for time coupling relationships between deployment and delivery cycles, and reduce system costs.

The application discloses a pinyin decoding method and related equipment, and relates to the technical field of natural language processing. The application first acquires a first text sequence containing a historical input text sequence and a current to-be-decoded pinyin string, and extracts semantic features corresponding to the text sequence by using a neural network model; then, corresponding statistical information is acquired by relying on a statistical language model. The statistical language model can store various types of text static statistical information, including candidate word entries and corresponding probability information, and the statistical information is mapped to a feature space consistent with the semantic features to obtain statistical features. The semantic features and the statistical features are fused to obtain fused semantic features, and a decoding result corresponding to the pinyin string is generated according to the fused semantic features. The application combines the semantic understanding ability of the neural network and the prior statistical advantage of the statistical language model, and takes into account the decoding accuracy and the use stability, is efficient in reasoning, and is suitable for various input method use scenarios.

This disclosure relates to the field of oil and gas geology, and particularly to a method, apparatus, equipment, medium, and procedure for analyzing the dissection process of oil and gas reservoirs. The method includes: selecting a target oil and gas reservoir based on the distribution characteristics of a predetermined target stratigraphic level; performing dissection analysis on the target oil and gas reservoir to obtain a dissection dataset; determining a data extraction method for each dissection data point based on its corresponding dissection category; extracting dissection attributes for each dissection data point using the data extraction method; analyzing each dissection data point based on the dissection attributes and pre-acquired dissection attribute data standards to obtain a dissection evaluation for each dissection data point; determining the complete dissection process corresponding to the target oil and gas reservoir using the dissection dataset; and comprehensively analyzing the complete dissection process using the dissection evaluation of each dissection data point. This invention can improve the accuracy of oil and gas reservoir process analysis.

This invention relates to the field of electricity meter technology, specifically to a method and system for predicting the aging state of electricity meters based on LSTM. The method includes: calculating the aging driving force index for each field vector and the aging driving force index for each simulated vector; taking any field vector as the target vector; calculating the absolute difference between the aging driving force index of the target vector and the aging driving force index of each simulated vector; using the simulated vector corresponding to the minimum absolute difference as the matching vector of the target vector; constructing a mapping vector for the target vector by combining the aging driving force index of the target vector, the aging driving force index of the matching vector, and the matching vector; iterating through the mapping vectors of each field vector to obtain the mapping vector; fine-tuning the prediction model based on all mapping vectors; and predicting the aging state of the electricity meter to be predicted based on the fine-tuned prediction model. This invention can reduce the error of the LSTM model when actually predicting the aging state of electricity meters.

This invention discloses an adaptive terrain-following flight control method and system for railway unmanned aerial vehicles (UAVs) that integrates multi-source terrain data and a data-driven model. The method utilizes an extended Kalman filter to estimate the change in rotational inertia online, dynamically correcting a preset initial dynamic model to obtain a dynamic baseline model. Simultaneously, it integrates multi-source terrain data to generate a terrain-following flight reference altitude surface that considers the track's geometric characteristics, using the track centerline as a constraint. Vertical and horizontal trajectories are planned based on the surface curvature, and dynamic yaw angles are calculated. A Gaussian process-enhanced prediction model is constructed, incorporating aerodynamic parameter perturbation learning and L1 adaptive laws into the nonlinear model predictive controller. An inner and outer loop cascaded architecture is used to solve for total lift and three-axis torque control quantities. Flight is driven by a pseudo-inverse assignment matrix mapped to rotor speed commands, and a safe distance is monitored in real time to trigger replanning. This method solves the problems of model mismatch and environmental adaptation in complex environments, improving flight safety and trajectory tracking accuracy.

This invention provides a method for accelerating real-time inference of multimodal large models, relating to the field of data processing technology. The method includes: Step 1, generating a minimum envelope ellipse using the peak point of the first visual attention weight, the second visual coordinate point, and the third visual association point as boundary points, and calculating the ratio of the area to the perimeter of the ellipse as a spatial clustering index. This invention effectively improves the efficiency, accuracy, and resource utilization of real-time inference of multimodal large models by selectively enhancing spatial features, evaluating multidimensional constraint computing power and dynamically scheduling resources, lightweight cross-modal fusion, and multi-step inference attention calibration, combined with real-time decision-making and full-process data-driven evaluation parameters and dynamic updates of the model library. This ensures the real-time performance and reliability of inference results, while continuously optimizing system computing power evaluation and model adaptation, making multimodal inference more aligned with the resource constraints of heterogeneous computing and the real-time and accuracy requirements of actual business operations.

This invention proposes a reconfigurable metasurface beamforming design method based on CGAN and Gumbel-Sinkhorn. This method constructs a conditional generative adversarial network (GAN) as the inverse design network. The generator takes the target beam pattern as a conditional input to generate the corresponding encoding matrix. The Gumbel-Sinkhorn operator is introduced to discretize this continuous matrix, transforming it into an approximately doubly random permutation matrix. The encoding is sorted and selected by multiplying this permutation matrix with a predefined structure vector (SV), outputting a discrete 0 / 1 metasurface encoding array. A noisy forward prediction network is trained to predict the beam pattern corresponding to a given encoding array. In the training of the inverse design network, the discretized encoding matrix output by the generator is input into the noisy-trained forward prediction network. The mean square error between the predicted beam pattern and the target beam pattern is calculated as the target loss term to optimize the network parameters and accurately learn the complex mapping relationship from the beam pattern to the encoding array.

This invention relates to the field of intelligent management technology and discloses an intelligent maintenance plan budgeting system based on historical data. The system includes: mapping maintenance records to pipe bundle support units to reconstruct circumferential damage distribution; extracting eccentric wear and historical maintenance offsets from the pipe bundles; constructing an equipment state set based on component reachability depth and predicting future maintenance work packages; and using a particle swarm optimization algorithm to perform adaptive optimization based on pipe bundle residual failure risk, disassembly and rework costs, and time sequence imbalance, thereby decoding and generating a maintenance work quantity list. This invention identifies locally concentrated maintenance volumes, improving the rationality of resource budgeting and maintenance scheduling.

The application discloses a kind of sensor general-purpose matching integrated circuits based on intermediate relay and electronic equipment;It is related to the field of electronic circuit, solve the problem such as poor adaptability of sensor and PLC by hardware modification or special conversion board, debugging is complex, cost is high etc.The interface of present application can be accessed to multiple types of sensors, output interface adapts different PLC port, conversion unit realizes signal conditioning, level conversion and logic processing, realize seamless docking of upstream and downstream.Intermediate relay coil is driven by sensor signal, controls contact group action, completes level conversion and logic flip, acts as signal bridge.The circuit is realized by setting intermediate relay unit, power source homologous circuit and signal conversion circuit, signal compatibility of different types of sensors and control module is realized.By selecting the on or off path of intermediate relay contact, PNP / NPN, normally open / normal close logic conversion is completed, and the problem of industrial field device mismatch is solved.