156 results about "Adaptive matching" patented technology

This application discloses a wearable EEG signal processing method and device based on feature fusion. The method includes: synchronously latching the main channel EEG signal from bioelectric electrodes and multimodal auxiliary signals from various auxiliary sensor interfaces within a preset period; inputting the multimodal auxiliary signals into a pre-trained interference identification model, outputting a structured interference quantization vector, which includes the confidence and intensity of different interference sources; processing the main channel EEG signal according to the confidence and intensity of different interference sources and a preset parameterized anti-interference algorithm library to obtain the final EEG data; quantifying the quality confidence of the final EEG data, storing the ternary mapping relationship between the current period, quality confidence, and the final EEG data, and sending it to a downstream application. Using this application, adaptive matching of the processing strategy with the real-time interference scenario is achieved, effectively avoiding overprocessing or underprocessing, and greatly improving the data robustness and accuracy of downstream applications.

The application discloses a visual-based human motion intention recognition interaction method and system, and relates to the technical field of computer vision. The method comprises the following steps: acquiring three-dimensional scene modeling data, detecting object spatial distribution to obtain target spatial granularity, and constructing an adaptive three-dimensional spatial anchor frame accordingly; collecting facial and binocular feature points, and predicting a visual gaze track through a binocular parallax algorithm; calibrating and optimizing the track by using the three-dimensional anchor frame, outputting a target, generating an instruction after analyzing the motion semantics of the target, and sending the instruction to a robot interaction terminal. The technical problem of low computational efficiency and ambiguous intention association caused by anchor frame redundancy in a complex physical scene is solved for the traditional visual-based intention recognition method, the technical effects of self-adaptive matching of a three-dimensional spatial anchor frame with a scene physical scale, introduction of a calibration and optimization mechanism for a visual predicted track, accurate association of human motion intention and a target object, and improvement of the accuracy, real-time performance and reliability of intention recognition are achieved.

This invention relates to the field of correction control technology, specifically to an automatic correction control system for cotton web width on a drawing frame. The system includes a position detection module, a main control unit module, an auxiliary algorithm module, a drive control module, a motor execution module, a human-machine interaction module, and a process database module. The position detection module is used to collect the position and width information of the fed sliver in real time and convert it into a pulse equivalent signal. This invention uses a position detection module with dual sensors symmetrically arranged to collect sliver position and width information in real time and convert it into a digital pulse equivalent signal, improving the accuracy and reliability of cotton web status detection and providing high-quality data support for subsequent intelligent calculations. The auxiliary algorithm module integrates feature extraction, similar working condition matching, benchmark value calculation, dynamic correction, and constraint verification to achieve adaptive matching of correction parameters with multiple working conditions and continuously improve the accuracy of cotton web process distance calculation and the rationality of correction actions.

This invention relates to the fields of physiological signal processing and emotion recognition technology, and discloses a method for recognizing physiological and emotional states of diverse populations. The method includes: acquiring facial video streams, infrared thermal imaging, and electrodermal signals; performing spectral adaptive enhancement based on skin color to obtain a spectrally enhanced video stream; inputting the spectrally enhanced video stream into a spatially modulated attention network to obtain a remote photoplethysmography waveform; extracting temperature distribution features from infrared thermal imaging; extracting electrodermal response features from electrodermal signals; aligning the three signals spatiotemporally and constructing alternative features for the failed signal based on the signal-to-noise ratio; inputting the three signals and alternative features into a multimodal signal pattern recognition network for weighted fusion, outputting a fused physiological feature; inputting the fused physiological feature into a population-level verification network for population adaptive matching and individual baseline correction, outputting the final emotional state. This invention achieves robust, fair, and accurate emotion recognition for diverse populations.

The application discloses a kind of machine vision processor and method for industrial robot dynamic sorting system, including data acquisition module, parallel processing unit, logic control unit and shared memory unit, wherein, data acquisition module is used to real-time acquisition video image sequence;Parallel processing unit is used to extract trajectory based on input video image sequence, detect the appearance feature and motion feature of target, and predict the position distribution of next frame image based on the extracted feature, and calculate the adaptive matching cost matrix between trajectory and detection;Logic control unit is used to match and associate between target trajectory and new detection target based on the adaptive matching cost matrix, and output tracking information;Shared memory unit is used for data sharing and interaction between parallel processing unit and logic control unit.The application effectively solves the general processor computing power bottleneck problem, and is suitable for high-precision dynamic sorting of industrial robot in complex scene.

This invention relates to the field of geotechnical engineering monitoring and slope stability analysis technology, specifically to a method and system for the layout of slope monitoring points throughout the entire construction and operation cycle. The method acquires multi-source monitoring data and constructs a unified data warehouse through cleaning, format conversion, and spatiotemporal registration. Based on this unified data warehouse, a dynamic risk assessment model coupled with the limit equilibrium method and the finite element method is used to identify target risk areas, and key monitoring variables are identified through global sensitivity analysis. Finally, a multi-objective optimization algorithm is used to solve for the Pareto optimal solution set to determine the location and density of monitoring points. This invention achieves adaptive matching of the monitoring network to changes in geological conditions and dynamic engineering needs throughout the entire cycle, improving the targeting of monitoring and the efficiency of resource allocation.

The application discloses a remote sensing image water body extraction method based on physical statistical distribution guidance and large model space constraint, comprising the following steps: acquiring a remote sensing image and performing pretreatment, calculating a physical statistical feature map and performing probability density distribution analysis, automatically determining a scene category to which the remote sensing image belongs, adaptively matching a hierarchical threshold calculation strategy, and acquiring a seed threshold and a growth threshold; performing region growing processing based on the seed threshold and the growth threshold to generate a physical prior coarse mask; performing connected domain analysis and adaptive outer expansion processing on the physical prior coarse mask to form a prompt box; inputting the pretreated remote sensing image and the prompt box into a visual basic model to output a fine segmentation prediction map; constructing a physical constraint search area based on the physical prior coarse mask, performing cascade fusion on the fine segmentation prediction map and the physical constraint search area, and obtaining a high-precision water body binary mask. Based on this, the application realizes automatic water body extraction without training samples, with strong noise resistance and fine edges.

This invention provides a compressor pump body core-adjusting device and process, relating to the field of compressor manufacturing technology. It includes a frame, a compressor fixing mechanism mounted on the frame, a measuring fixing mechanism with slide rails that allows free vertical movement, a fixed scroll clamping mechanism controlled by a cylinder, and a measuring probe mounted on the measuring fixing mechanism. The core-adjusting process includes: fixing the compressor, pulling down the measuring fixing mechanism to a designated position, clamping the fixed scroll, bringing the measuring probe into contact with the fixed scroll, driving the compressor to rotate, detecting the movement of the fixed scroll, and tightening the fixed scroll bolt after the movement reaches a specified value. This invention utilizes the adaptive matching principle of the moving and fixed scrolls, using data as the final judgment standard, solving the technical problems of complex core-adjusting processes, cumbersome operations, and significant reliance on subjective experience in existing technologies.

This invention proposes an adaptive grinding method and equipment for arc welds based on a grinding robot. The adaptive grinding method for arc welds based on a grinding robot includes the following steps: S1, reference teaching and correction; S2, weld information acquisition and trajectory compensation; S3, adaptive matching of grinding parameters; S4, constant force floating grinding; S5, quality inspection. The grinding equipment includes a grinding robot and an information vision system. This invention achieves efficient and high-quality adaptive grinding of arc welds on large welded structural components, effectively improving grinding consistency and production efficiency, and reducing manual intervention and operational risks.

This invention discloses a variable-step automatic gain control method based on an adaptive window, applicable to signal automatic gain control in data acquisition systems. The method preprocesses the input signal and samples it using an ADC to obtain a digital signal, which is then fed into an FPGA. A zero-crossing detection method based on a hysteresis comparator is used to estimate the signal frequency, and the window length is calculated based on this adaptive amplitude matching. The average signal amplitude within the window is then calculated and compared with a preset automatic gain threshold range. The gain step value is dynamically matched and updated to the variable gain amplifier to complete closed-loop control. Finally, the gain value is used to perform an amplitude inverse calculation to restore the signal. This invention improves the detection accuracy and dynamic response speed of the system over a wide bandwidth and dynamic range, eliminates the hardware resource consumption of floating-point division operations, and accurately outputs a distortion-free original proportional signal stream.

This invention relates to the field of medical device control technology, and discloses a method and system for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback. The method controls a fluid drive unit to operate in microcycles, dividing each microcycle into an active loading segment and a passive relaxation segment. In the active loading segment, pressure peak value and rise rate indices characterizing tissue stiffness are extracted, and a heterogeneity factor is calculated. In the passive relaxation segment, pressure decay indices characterizing tissue permeability are extracted. A multidimensional state vector is constructed by fusing stiffness and permeability characteristics to determine the physical condition. Based on the determined physical condition, the control target is retrieved, and execution parameters such as the duration of the active loading segment in the next cycle are dynamically adjusted using a closed-loop controller. By time-divisionally detecting the solid and fluid dynamic properties of the tissue, dense tissue and obstructive conditions are effectively distinguished, achieving real-time adaptive matching of injection parameters and tissue characteristics, thus reducing the risk of tissue damage while ensuring drug penetration efficiency.

The application relates to the technical field of flow measuring boxes, in particular to an assembled flow measuring box which comprises a machine box assembly, a floating part is vertically and slidingly connected to the inner side of the machine box assembly, driving plates are slidingly and clamped to the two sides of the floating part through connecting components, a driving hole is formed in one side of each driving plate, a sensor is slidingly connected to the inner side of each driving hole, the floating part moves the driving plates by the buoyancy brought by water flow, the driving plates change the positions of the sensors through the driving holes, the floating part changes the positions and the intervals of the sensors in real time through water level changes, the sound channel is always in the optimal position, and due to the angle changes of the sensors in the driving holes, the intervals and the positions of the sensors realize nonlinear self-adaptive matching, flow state disturbance and signal interference caused by the sudden shrinkage of the intervals under low water level are avoided, and the measurement range and the precision are considered.

This invention relates to the field of geophysical exploration, specifically disclosing a method for identifying geological body boundaries based on adaptive matching of multi-source gravity and magnetic data. The method includes: acquiring gravity and magnetic anomaly data; estimating the equivalent source depth; constructing a depth-response mismatch correction field based on the depth attenuation difference between gravity and magnetic potential fields; compensating for and registering the magnetic anomaly with remanent magnetization and demagnetization offset; constructing an adaptive coupling direction tensor based on the consistency of the local gradient structures of the two fields; performing anisotropic boundary enhancement on the two fields using the principal direction of the adaptive coupling direction tensor as a constraint and the coupling strength as a weight; and iteratively fusing the two fields through mutual verification using the adaptive coupling direction tensor as a constraint and the depth-response mismatch correction field as a weight, outputting the fine spatial location of the geological body boundary and an adaptive confidence evaluation result. This invention achieves adaptive registration and direction constraint enhancement in the depth domain of gravity and magnetic data, effectively improving the accuracy and reliability of geological body boundary identification under complex geological conditions.

The utility model belongs to wireless energy transmission technical field relates to a kind of unmanned vehicle wireless charging pile of self-adaptive matching, it include: ground fixed pile, telescopic support, torsional spring, charging emission plate, limit support and charging receiving plate, ground fixed pile is fixed in the ground or foundation of charging position by foundation bolt, the bottom of ground fixed pile and telescopic support is connected rigidly, the top of telescopic support is connected with charging emission plate by torsional spring, torsional spring is integrated between telescopic support and charging emission plate, charging emission plate is installed at the top of telescopic support, the lower end of limit support is fixedly connected with ground fixed pile, the upper structure of limit support is suspended and covers or surrounds the outer periphery of charging emission plate, the inner wall of limit support defines the movable boundary of charging emission plate, charging receiving plate is fixedly connected with vehicle chassis, and charging receiving plate is installed in the lower part of the chassis of unmanned vehicle.Full passive self-adaptive, high fault tolerance, self-recovery, easy to integrate, high safety.

The application discloses a model prediction control method of a multi-path switching Buck-Boost converter and relates to power electronic conversion control. The technical solution points are as follows: step 1: output voltage and current detection and preprocessing; step 2: voltage outer loop PI regulation and current reference value generation; step 3: current inner loop mode division model prediction control; step 4: double-state observer design and parameter estimation; and step 5: power supply switching logic and PWM signal generation. The application mainly detects input power supply voltage and load state, adaptively matches optimal working modes and control parameters, ensures synchronous and accurate control in all power supply switching and mode conversion processes, realizes smooth action of main switching devices and output voltage stability through one set of control architecture, and significantly improves system efficiency and robustness.

This invention relates to the field of notebook computer casing conveying technology, and particularly to a feeding device for notebook computer processing, comprising a feeding module, a worktable, a laser engraving module, a mounting bracket, a lateral centering module, a suspension, a loading module, an unloading module, a linkage module, a first loading belt, and a second loading belt. This invention achieves a continuous operation mode of simultaneous conveying and positioning by having the lateral centering module dynamically abut against the side of the casing during conveying, correcting positional deviations in real time, and pushing them towards the conveying centerline. This application constructs a mechanical dimension recognition and feedback system based on multi-level swing and limit, which can automatically trigger different levels of avoidance and positioning actions according to the actual width of the casing. Simultaneously, the loading module receives centering status feedback through the linkage module and automatically adjusts the suction distance of the pick-up suction cup and the airflow channel size of the vent valve, achieving dual adaptive matching of the gripping range and suction force.

This invention discloses a Marchenko multiple suppression method for tracking wave impedance interfaces, belonging to the field of seismic data processing technology. The method includes the following steps: S1, obtaining wave impedance inversion results across the entire depth domain based on surface observation seismic data and the background velocity field; S2, extracting the location information of strong wave impedance interfaces and identifying several key locations between these interfaces; S3, using a Bezier curve smoothing method to obtain the spatial location of the focal point that maximizes the penetration of the strong wave impedance interface; S4, determining the ascending and descending Green's functions for the spatial location of the focal point; S5, predicting interlayer multiples using seismic interferometry; and S6, obtaining the seismic shot gather for suppressing interlayer multiples through adaptive matched filtering. This invention does not require a precise velocity model, relying only on a macroscopic velocity model, and can obtain deep-domain strong wave impedance geological information, accurately predicting and suppressing interlayer multiples by combining wave impedance information.

This invention discloses a multi-source time-domain collaborative control method, system, and device for a virtual synchronous generator, belonging to the field of power electronics control technology. The method includes: synchronously acquiring multi-source time-series data from the grid connection point and the virtual synchronous generator itself; constructing a multi-source time-domain state observer based on the fusion of Kalman filtering and recursive least squares to estimate the equivalent inertia coefficient and equivalent damping coefficient of the power grid in real time; designing a collaborative controller including a model predictive control layer and a sliding mode control layer, using the estimated equivalent inertia coefficient and damping coefficient as feedforward correction quantities, continuously optimizing the solution for the optimal voltage reference vector, and generating a compensation control quantity; superimposing the optimal voltage reference vector and the compensation control quantity, and generating a drive signal through pulse width modulation. This invention, through multi-source time-domain collaborative control, achieves adaptive matching of the inertia and damping of the virtual synchronous generator, improves the speed and stability of frequency support, and enhances the power sharing capability when multiple generators are connected in parallel.

The application discloses a kind of unmanned aerial vehicle monocular vision inertial SLAM loop detection methods based on undergrowth trunk geometry, the method includes the following steps: step 1, trunk region segmentation and three-dimensional point cloud generation;Step 2, trunk clustering detection and position positioning;Step 3, triangular geometric feature construction and screening;Step 4, multidimensional similarity calculation;Step 5, geometric and visual joint decision and loop confirmation.This method extracts stable geometric information of trunk by driving depth data, constructs triangular features with invariance with trunk position as vertex to break through the dependence of visual texture, realizes double-path independent detection and joint decision by combining traditional visual bag-of-words model, balances detection accuracy and real-time through adaptive matching strategy, thereby effectively improves the accuracy, robustness and environmental adaptability of loop detection in undergrowth GNSS-free environment.

The application provides an image adaptive quantization communication method and system, relates to the technical field of artificial intelligence and semantic communication, and comprises the following steps: performing feature extraction on an input image to form an initial code word representation; adopting an adaptive dynamic quantization mechanism to perform quantization processing on the initial code word representation to generate a code word index as a quantization feature; after the receiving end obtains the code word index of the sending end, performing inverse quantization by using a codebook knowledge base, and reconstructing a recovered image by using a decoder. The method and system provided by the application avoid representation collapse and realize adaptive matching and dynamic updating between codebook elements and semantic features through multi-codebook cooperation, a learnable linear transformation and a dynamic selection mechanism based on attention; and through quantization representation and transmission of the image and then decoding and recovery, the efficiency of image transmission is greatly improved, and an efficient and intelligent basic framework is provided for a next-generation semantic-oriented image communication system.

This invention discloses a variable frequency energy-saving screw vacuum pump, relating to the field of screw vacuum pump technology. It includes an energy-saving device, a pumping chamber, an air inlet, an exhaust port, and a drive component. The drive component drives the male and female screws within the pumping chamber to rotate. The pumping chamber compresses and discharges air, gradually evacuating the working space into a vacuum. It can work in conjunction with a frequency converter. During the operation of the screw vacuum pump, the compression ratio and bypass channel opening can be dynamically adjusted according to the changing pumping requirements at different process stages, allowing it to operate within a more ideal working range. During the vacuum pump start-up and shutdown transition phase, the bypass channel is opened and the compression ratio is reduced to minimize wasted work. During the pumping phase, the bypass channel is closed, and a lower compression ratio reduces energy loss, thus achieving energy savings. During the stable operation phase, the compression ratio is increased to ensure pumping efficiency, thereby achieving adaptive matching for different operating conditions.

This invention discloses a robust reinforcement learning-based intelligent scheduling method for energy flow in ocean-going island clusters, encompassing day and night dual-mode scheduling. The method includes: constructing a comprehensive energy coordination architecture integrating energy production and conversion on resource islands, cross-island transportation by battery-swapping vessels, and energy consumption on load islands; establishing a two-stage scheduling mechanism and differentiated optimization objectives based on day-night energy supply and demand differences; designing a reinforcement learning framework with robust constraints and constructing a robust Markov decision process; and employing a model-based robust adversarial reinforcement learning algorithm to solve the problem and output a real-time scheduling strategy. This invention fully considers the layout characteristics of island clusters, renewable energy endowments, and the mobile energy storage characteristics of battery-swapping vessels, effectively addressing uncertainties such as renewable energy fluctuations, achieving adaptive matching of load demand on load islands, and solving the problems of energy retention, supply shortages, and high operating costs associated with traditional methods. This provides technical support for energy self-sufficiency and sustainable development of ocean-going island clusters.

This invention discloses an atomic fluorescence spectrometer and an automated sample measurement system, belonging to the field of atomic fluorescence spectrometer technology. This invention effectively ensures stable instrument operation and efficient atomization reactions through a comprehensive self-checking mechanism combined with adaptive matching of different analyte types and detection modes. Simultaneously, through precise cup positioning, automatic sample sequence configuration, and orderly scheduling of the detection process, coupled with reference light baseline correction, multi-level blank measurement, and standard curve fitting to establish quantitative correlations, it fully covers the entire detection chain from automatic sample introduction, signal acquisition, signal optimization processing to concentration calculation and correction, effectively improving the accuracy and repeatability of sample measurement results. It achieves fully automated operation of the entire process—including power-on self-check, parameter matching, automatic measurement, data calibration, result calculation, and standardized report generation—without extensive manual intervention, adapting to the needs of multi-element, multi-wavelength simultaneous detection and improving the intelligence, standardization, and automation level of atomic fluorescence detection.

This application discloses a three-dimensional moving high-pressure water jet testing device, a trench morphology measurement system, and a testing method. The system includes: a three-axis sliding system for driving a high-pressure spray gun to perform precise three-dimensional movement above the test water tank; a high-pressure jet execution unit with a water pump frequency converter and an electromagnetic flowmeter for generating and closed-loop controlling the high-pressure jet; a data detection and collection unit including a multi-beam sonar and a high-speed camera for acquiring terrain and process image data; and a central control unit for integrating and controlling the aforementioned units. The testing method includes: S1, test preparation and initialization; S2, pre-scanning; S3, initial position positioning; S4, water pump power adjustment; S5, jet execution; S6, real-time monitoring; and S7, post-scanning and data analysis. This invention achieves adaptive matching of jet parameters and terrain, solving the problems of low automation and lack of terrain feedback in traditional testing methods, significantly improving the accuracy, efficiency, and reliability of the test.

The present application relates to the technical field of image processing, more particularly, the present application relates to a kind of workpiece visual positioning method and system based on contour key point matching, comprising: obtaining current image containing workpiece, and extracting the contour of the current image, based on Harris operator, extract multiple key points on the contour;The stability of each key point is calculated.The present application effectively eliminates the interference of light noise by constructing a stability evaluation model containing gradient, curvature and Harris response;Topological correlation strength combining geometric distance and polar angle constraint is first created, which quantifies the support ability of feature points to workpiece structure;Further, adaptive matching weight is constructed and applied to weighted RANSAC algorithm, which changes the traditional uniform sampling strategy, and realizes high robustness, high precision and high efficiency positioning of workpiece under complex industrial scene (such as occlusion, reflection).

This invention discloses a PLC-based collaborative control system for composite material molding production lines, belonging to the field of automated composite material molding technology. It includes a production line execution unit and a PLC collaborative control unit. The production line execution unit includes a front-end production line, which interfaces with shared equipment via a transfer module. The master station arbitration PLC, production line slave PLCs, and shared equipment are connected via a communication unit. The PLC collaborative control unit incorporates an automatic mold switching control module and a native PLC-based full-process motion learning unit. The master station arbitration PLC also performs global scheduling, global clock synchronization, global IO address mapping planning, mold switching, and motion learning. The production line slave PLCs communicate with each production line individually. This PLC-based collaborative control system for composite material molding production lines can achieve motion learning, automated mold switching, and dynamic collaborative control throughout the entire process from raw materials to finished products, adaptively matching the dynamic characteristics of the production line.

The application provides a multi-branch graph adaptive network for individualized motor imagery electroencephalogram signal classification and a method thereof. Through an adaptive matching technology, a graph convolutional neural network (GCN) is used to learn a mapping relationship between an EEG signal and an optimal time-frequency domain processing method, and an optimal processing method is matched for each individual. The multi-branch network comprises an original data branch, a CWT branch and an STFT branch, and corresponding feature extraction networks are respectively designed. A data enhancement method based on a super-resolution generative adversarial network is used to expand a training data set and improve the generalization ability of the model. Experimental results show that the method significantly improves the classification accuracy of individualized EEG signals and has practical application value.

This invention relates to the fields of materials informatics and data quality control, specifically a collaborative verification method for the quality of chemical formula sampling distributions in materials. Addressing the problems in existing methods for verifying the quality of chemical formula sampling distributions in materials—such as one-sided evaluation dimensions, decoupling from intrinsic performance characteristics, insufficient utilization of historical experience, lack of operability and interpretability of verification results, and neglect of multi-model prediction consistency—this invention achieves comprehensive collaborative evaluation of chemical and performance spaces through a multi-dimensional collaborative evaluation and adaptive intelligent verification framework. This includes adaptive matching of verification standards to performance sensitivity, full activation of historical data value, effective output of transparent diagnostics and precise optimization guidance, and quantitative improvement of multi-model prediction consistency. This provides reliable quality assurance for high-throughput material screening and improves R&D efficiency.