27 results about "Distortion analysis" patented technology

The invention relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and an attitude restoration module. According to the method, the gray level change trend of each pixel and the adjacent points in the image is obtained, the high-reflection suspected interference area is identified, the edge response cancellation processing is executed, and linear interpolation compensation is carried out by combining the effective edge response values of the adjacent areas; after a continuous contour trend is constructed, clustering and sub-grouping division are carried out according to an included angle difference trend between contour geometric vectors, a three-axis direction response linear array variation amplitude is extracted to construct a distortion curvature mapping table, existence of non-equal-interval deformation is judged, reverse angle compensation is applied, and a three-axis intersection point convergence process is completed through a nonlinear optimization algorithm; and according to the three-dimensional coordinates, calculating a geometric dimension and outputting a detection result, thereby realizing self-adaptive detection of different postures and surface interference component dimensions.

The invention discloses a supply chain material inventory control method and system, and the method comprises the steps: carrying out the demand distortion analysis of the demand signal data of each node in a target supply chain, and obtaining the demand signal distortion amplitude of each node; if the demand signal distortion amplitude exceeds a preset distortion amplitude threshold, performing distortion degree classification prediction on the demand signal distortion amplitude to obtain a real-time demand prediction result of each node; performing sensitivity analysis on the real-time demand prediction result, and generating a safety inventory parameter of each node; generating a collaborative inventory distribution scheme of the target supply chain according to the safety inventory parameters and the information sharing evaluation indexes; and performing cooperative control on the material inventory of each node in the target supply chain according to the cooperative inventory distribution scheme. The flexibility and cooperation efficiency of the supply chain to adapt to the market change can be improved through the cooperation inventory distribution scheme, so that the risk resistance capability is enhanced, and the capability of the supply chain to cope with the market demand fluctuation complex scene is improved.

This invention relates to the field of laser processing technology, and discloses a method and system for femtosecond laser three-dimensional surface processing based on adaptive optics. The method includes: spatial topology reconstruction of the original point cloud data of the workpiece to be processed to obtain a three-dimensional digital surface; row spacing planning and optimization of the three-dimensional digital surface to obtain a spatial processing trajectory, and point wavefront mapping of the spatial processing trajectory to obtain pre-compensated phase distribution data; optical field distortion analysis of the surface reflected light signal of the workpiece to be processed to obtain the actual wavefront phase; encoding the pre-compensated phase distribution data into an initial wavefront control command for a beam shaping device, and iteratively optimizing the initial wavefront control command to obtain a wavefront supplement signal; and updating the spatial processing trajectory by combining the real-time contour data of the workpiece to be processed. This invention can improve the efficiency of femtosecond laser three-dimensional surface processing based on adaptive optics.

The present application belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of primary-secondary fusion circuit breaker, comprising: obtaining circuit breaker state data, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprint through nonlinear segmented harmonic analysis, constructing a multi-dimensional penetration feature matrix, and establishing a micro-scale electric-thermal coupling atlas; obtaining a nonlinear region situation table through impedance distortion analysis, obtaining a harmonic penetration curve through multi-frequency response analysis, and constructing a high-frequency harmonic penetration path spectrum; establishing a micro-region diagnosis algorithm, performing nonlinear impedance calibration, and generating a multi-level protection instruction sequence; adjusting the operating state of the circuit breaker, obtaining the circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; the present application realizes accurate identification and early warning of abnormal regions inside the circuit breaker, and improves the safe and stable operation ability of the primary-secondary fusion circuit breaker.

The embodiment of the invention provides a wall flatness detection method and system based on projection image distortion analysis, and the method comprises the steps: obtaining a plurality of groups of standard template images and a plurality of groups of deformation images of a to-be-detected wall under the condition that the perpendicularity self-calibration of detection equipment is completed; wherein the number of the plurality of groups of deformation images is consistent with that of the plurality of groups of standard template images, and the plurality of groups of deformation images are images formed on the surface of the to-be-detected wall by the plurality of groups of standard template images; based on the plurality of groups of standard template images and the plurality of groups of deformation images, performing pairing to obtain a plurality of groups of image pairs; feature extraction and fusion are carried out on the multiple groups of image pairs through a convolutional neural network to obtain a wall surface flatness map; based on the wall flatness map, flatness index quantitative calculation and compliance judgment are carried out, and a wall flatness detection result is obtained. According to the scheme, the accuracy and efficiency of wall flatness detection can be improved.

The invention relates to the technical field of transformer detection, in particular to an intelligent state detection system for a dry-type transformer, and the system comprises a data obtaining module which is used for obtaining the environment parameters and operation parameters of the dry-type transformer; the load type determination module is used for determining the operation load type of the dry-type transformer based on the operation parameters; the potential fault positioning module is used for responding to a low load type and positioning a potential fault position based on the operation parameters; the detection path planning module is used for determining a detection path based on the potential fault position and the three-dimensional structure model; and the path adjustment module is used for determining a fault influence area corresponding to the detection position based on the fault detection result, and adjusting a subsequent detection path based on the fault influence area. According to the method, through the technical means of combining iron core vibration distortion analysis under the low-load working condition with dynamic path planning and adjustment, the beneficial effects of accurately positioning potential faults in the low-load period and adaptively optimizing the detection path are achieved.

The application discloses a kind of based on multimodal feature fusion's ultra-high-definition video AI repair method, it is related to video repair technical field, for solving the structure drift after reference frame pollution cannot be accurately identified, and the structure misplacement of repair area appears in continuous playing process Problem, by executing code rate fluctuation detection and adjacent frame jitter analysis to the video stream to be measured, to identify structure distortion state, video stream is decoded and extracted coding structure information, the frame level dependency graph corresponding to video frame is constructed, motion vector amplitude is collected and distortion intensity is generated in combination with frame distortion analysis result, the initial frame weight is dynamically regulated, to evaluate the propagation trend of distortion in reference frame link, fusion audio feature data and visual feature data execute consistency determination, in combination with distortion propagation trend mark candidate distortion area, and utilize AI image repair model to execute different reconstruction repair to candidate distortion area, avoid the structure misplacement problem caused by traditional local enhancement.

The present application belongs to the field of unmanned driving, and proposes a point cloud distortion correction method based on dynamic vehicle detection in an unmanned driving scene, which comprises the following steps: step 1, point cloud distortion analysis and data generation; step 2, point cloud global distortion correction based on laser radar motion analysis; step 3, point cloud local distortion correction based on vehicle motion analysis; and step 4, point cloud distortion correction in an unmanned driving scene. The method of the present application improves the accuracy of three-dimensional reconstruction and three-dimensional positioning in unmanned driving, and effectively overcomes the safety hazards of intelligent motion behavior of unmanned driving.

The present application relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and a posture restoration module. In the present application, by obtaining the gray level change trend of each pixel and its adjacent points in the image, the high reflection suspected interference area is identified and the edge response is invalidated, the linear interpolation compensation is performed in combination with the effective edge response value of the adjacent area, the continuous contour trend is constructed, the clustering and sub-grouping division are implemented according to the difference trend of the angle between the contour geometric vectors, the three-axis direction response line array change amplitude is extracted to construct a distortion curvature mapping table and judge the existence of non-equal interval deformation, the reverse angle compensation is applied, and the three-axis intersection point convergence process is completed through a nonlinear optimization algorithm, the geometric size is calculated according to the three-dimensional coordinates, and the detection result is output, so that the adaptive detection of the size of components with different postures and surface interference is realized.

The invention discloses a hidden perception spoofing attack detection method based on self-diagnosis space consensus. The method comprises the following steps: acquiring a state vector set reported by all user equipment based on own received signals; the state vector set comprises a state vector corresponding to each user equipment; the state vector comprises a position estimator, a speed estimator and a power measurement index; dividing the state vector set into a plurality of clusters by adopting a consensus clustering algorithm based on a kernel function; calculating a consistency metric for each cluster to determine an initial attack cluster; and carrying out feature structure distortion analysis and RCS consistency verification based on the initial attack cluster, thereby providing a detection method capable of effectively identifying hidden perception spoofing attacks such as cross-UE space collaborative spoofing, parameter adaptive time sequence camouflage and high-simulation physical layer signal replication.

The invention discloses an energy-saving water pump parameter adaptive scheduling method and system, and relates to the technical field of water pump control, and the method comprises the steps: collecting active power data of a frequency converter, pipeline pressure data, pipeline flow data and motor rotation speed data; performing time alignment processing; response feature extraction is carried out on the water pump operation condition data after time alignment processing, and dynamic response features are obtained; performing dynamic behavior distortion analysis according to a dynamic response reference model and the dynamic response characteristics to obtain a dynamic behavior distortion analysis result; and if the dynamic behavior distortion analysis result is that behavior distortion exists, cancelling the modification of the multiplicative correction coefficient on the water pump parameters. According to the method, behavior distortion can be analyzed in combination with water pump operation condition data and dynamic response characteristics, and water pump parameter modification is canceled, so that water pump parameter adaptive scheduling is realized, accuracy and stability are improved, and energy consumption per unit water volume is reduced.

The invention discloses a self-adaptive control method and system for an inverter. The method comprises the following steps: acquiring current operation sampling data, working condition parameters and device rated parameters of an arc load in real time; performing fast Fourier transform to obtain spectral characteristic data; based on the arc load model library, optimization parameter adjustment is carried out, and preliminary control parameters are obtained; inputting the current operation sampling data into a pre-trained support vector machine model to obtain a target control parameter; performing load adjustment based on a fuzzy logic control algorithm to obtain adjusted current operation sampling data; distortion analysis is carried out to obtain an adjustment result, and the initial control parameters are adjusted to obtain initial control parameters; working condition analysis and adjustment are carried out according to the environment temperature, the device rated parameters and the initial control parameters, and final control parameters are obtained. According to the method, self-adaptive control of the inverter on the arc load is realized, and sensitive and accurate control of stable combustion of the arc is realized.

The invention discloses a UWB space positioning method and system, and relates to the technical field of wireless communication positioning navigation.The high-precision positioning is achieved through a UWB label, multiple base stations, an intelligent temperature control clock module and a data processing center, the distance is calculated through the TWR technology, and the intelligent temperature control clock module is connected with a temperature sensor through a phase-locked loop circuit and a constant-temperature control unit; dynamically compensating the temperature drift to synchronize the clock frequency; the positioning method comprises the following steps: receiving base station distance data and signal characteristics, realizing multi-modal NLOS identification through signal distortion analysis, obstacle detection and motion continuity judgment in combination with environment perception and motion trail data, and screening candidate base stations; selecting a base station with the lowest NLOS probability as a reference, compensating and correcting distance data through Kalman filtering motion prediction, and fusing results of multiple base stations to determine a target position; and virtual reference points can be set to optimize positioning, so that the positioning precision and stability in a complex environment are effectively improved.

The invention belongs to the technical field of valve sealing performance testing, aims to solve the problems that in the prior art, microscopic symptoms of flow state transition cannot be captured in the extremely early stage of leakage development, and the essential type of a fault cannot be further deconstructed from the coupling relation of multi-source data, and particularly relates to a valve sealing performance testing system based on multi-source data fusion. Comprising an operation parameter acquisition module, a dynamic feature extraction module, a mapping analysis module, a distortion analysis module and a state evaluation module. According to the method, a reference coordinate system with a pressure zero crossing point as a time anchor point is constructed, a flow zero crossing point is mapped into the coordinate system, and traditional macroscopic magnitude comparison is converted into microstructure analysis of a pressure-flow coupling relation; the fundamental transformation of leakage early warning from'macroscopic threshold triggering 'to'microstructure distortion capturing' is realized, and the timeliness of early detection of leakage is remarkably improved.

The invention belongs to the technical field of information management, and provides an intelligent information service management system, which comprises the following steps of: acquiring full-link data of information transmission in a historical period by adopting an Flink stream processing framework, and constructing a full-link information analysis library; based on the full-link information analysis library, content distortion and aging distortion analysis is carried out on the distortion degree of information transmission in work, and the distortion degree of full-link data in work is evaluated; if the working full-link data distortion is serious, performing quantitative deviation analysis on all works with serious full-link data distortion in a historical period, evaluating hierarchical distortion risks in the works, identifying serious distortion hierarchies, and requiring a processor of the serious distortion hierarchies to re-check and supplement original information; according to the method, the serious distortion level in the whole link is positioned, and the risk is quantified by fusing the double dimensions of the distortion occurrence frequency and the severity, so that targeted rectification and level process optimization are realized.

This invention discloses a supply chain inventory control method and system. The method includes performing demand distortion analysis on demand signal data at each node in the target supply chain to obtain the distortion amplitude of the demand signal at each node; if the distortion amplitude exceeds a preset distortion amplitude threshold, classifying and predicting the distortion degree to obtain the real-time demand forecast result for each node; performing sensitivity analysis on the real-time demand forecast result to generate safety stock parameters for each node; generating a collaborative inventory allocation scheme for the target supply chain based on the safety stock parameters and information sharing evaluation indicators; and collaboratively controlling the inventory of materials at each node in the target supply chain according to the collaborative inventory allocation scheme. This collaborative inventory allocation scheme can improve the flexibility and efficiency of the supply chain in adapting to market changes, thereby enhancing its risk resistance capabilities and improving its ability to cope with complex scenarios of fluctuating market demand.

The invention discloses an electrolysis cooperative control method and system based on electrochemical state feedback, and relates to the technical field related to electrolysis control, and the method comprises the steps: monitoring a steady-state operation signal of an electrolysis unit, applying controlled perturbation excitation, synchronously collecting an unsteady-state response signal, and carrying out distortion analysis, transient impedance spectrum extraction and phase drift analysis on the unsteady-state response signal, so as to obtain an unsteady-state response signal; obtaining a dynamic feature set; in combination with the steady-state reference features, the combined features are mapped to a unified projection space for electrochemical state inversion, and a state feedback quantity is generated; and extracting state evolution characteristics and judging an evolution interval, and generating a cooperative control strategy according to the evolution interval to execute electrolysis cooperative control management. The technical problems that in the prior art, electrochemical state sensing is lagged and one-sided, dynamic information utilization is lacked, and multi-unit cooperative control is extensive are solved, and the technical effects that the state sensing real-time performance of the electrolysis process, cooperative control accuracy and foresight and the overall energy efficiency and service life of cooperative operation of multiple electrolysis units are improved are achieved.

The application discloses an adaptive control method and system of an inverter, and the method comprises the following steps: acquiring current operation sampling data, working condition parameters and device rated parameters of an arc load in real time; performing fast Fourier transform to obtain frequency spectrum characteristic data; based on an arc load model library, performing optimization parameter adjustment to obtain preliminary control parameters; inputting the current operation sampling data into a pre-trained support vector machine model to obtain target control parameters; performing load adjustment based on a fuzzy logic control algorithm to obtain adjusted current operation sampling data; performing distortion analysis to obtain an adjustment result, and adjusting the preliminary control parameters to obtain initial control parameters; and performing working condition analysis and adjustment according to the environmental temperature, the device rated parameters and the initial control parameters to obtain final control parameters. The method realizes adaptive control of the inverter on the arc load, and realizes sensitive and accurate control of arc stable combustion.

The invention relates to a video coding system and a video coding method, in particular to VVC (Very Video Coding), the system comprises a coding initialization module, a plurality of pixel prediction modules and a judgment module, the coding initialization module is used for sending prediction requests to the plurality of pixel prediction modules in parallel; each pixel prediction module is used for receiving a prediction request corresponding to each pixel prediction module, and performing pixel prediction on a coding unit pointed by the prediction request by adopting a plurality of intra-frame prediction modes based on the at least two prediction sub-modules to obtain prediction pixels corresponding to the coding unit in the plurality of intra-frame prediction modes; and the judgment module is used for performing rate distortion analysis on the prediction pixels corresponding to the multiple intra-frame prediction modes to obtain a target prediction pixel of the coding unit, a target intra-frame prediction mode and a first reconstruction pixel corresponding to the target coding tree unit. According to the invention, the efficiency of VVC intra-frame prediction coding is improved, and the implementation complexity is reduced.

A method of performing a quantum gate operation in an ion-trap quantum computing system includes identifying one or more error mechanisms that cause quantum computing errors in a quantum gate operation on a first trapped ion of an ion chain that includes a plurality of trapped ions, wherein the quantum gate operation is performed by applying a first Raman laser beam and a second Raman laser beam; calculating a first amplitude of the first Raman laser beam and a second amplitude of the second Raman laser beam such that effects of the identified one or more error mechanisms are addressed; and applying the first Raman laser beam with the calculated first amplitude and the second Raman laser beam with the calculated second amplitude on the first trapped ion to perform the quantum gate operation on the first trapped ion.

The invention provides a full-automatic batch test method and system for waveform parameters of a crystal oscillator, and belongs to the technical field of function test. According to the method, accurate transmission of a test state is ensured through a corresponding judgment mode in each step according to progressive test steps of frequency locking, amplitude locking and phase locking, and on the basis of successful locking of frequency, amplitude and phase, a total harmonic distortion value of a crystal oscillator to be tested is obtained according to a distortion analysis instruction. The real waveform distortion information of the crystal oscillator to be tested can be accurately captured, and the accuracy of a waveform parameter qualification judgment result is ensured. According to the invention, the dependence on manual instrument connection, parameter setting and instrument switching configuration one by one can be eliminated, the overall test period of the crystal oscillator is greatly shortened, and the test efficiency and the consistency and reliability of the test result under the scene of mass production or incoming material inspection are remarkably improved.

Methods, devices, and non-transitory computer-readable storage medium are provided for use in video encoding or decoding where at least one parameter of a cross-component sample offset filter is scaled to produce at least one scaled parameter, and the cross-component sample offset filter is applied to reconstructed pixels of a video frame to produce filtered pixels using the at least one scaled parameter. The scaling can be based on a scaling factor encoded in a compressed bitstream or on a bit-depth of the video frame. The scaling factor can be determined by an encoder using a rate distortion analysis and encoded into the compressed bitstream. The at least one parameter can include a quantization step and a plurality of offsets. The encoded scaling factor can be a 1-bit value indicating that the at least one parameter is to be multiplied by four.

Embodiments of the present application provide a method and device for recognizing text in a distorted document and a storage medium. The method comprises: segmenting text lines in a text image to be recognized according to a preset segmentation model to obtain a mask image of the text lines; performing distortion analysis on the text lines according to the mask image to determine a mapping relationship model between the text lines and horizontal text lines; correcting the text lines in a curved distribution according to the mapping relationship model to obtain text lines in a straight line distribution after correction; and recognizing text in the text lines after correction.

A method or system is disclosed to assess transmission errors in a visual media input. Domain knowledge is obtained from the visual media input by content analysis, codec analysis, distortion analysis, and human visual system modeling. The visual media input is divided into partitions, which are passed into deep neural networks (DNNs). The DNN outputs of all partitions are combined with the guidance of domain knowledge to produce an assessment of the transmission error. In one or more illustrative examples, transmission error assessment at a plurality of monitoring points in a visual media communication system is collected and assessed, followed by quality control processes and statistical performance assessment on the stability of the visual communication system.

The application relates to a bridge model design method and system based on static and dynamic information fusion, and belongs to the technical field of bridge design. The bridge model design method based on static and dynamic information fusion comprises the following steps: obtaining physical quantities of a prototype and a scale model of a bridge; determining static dimensionless parameters based on the physical quantities and a dimensional analysis method; establishing a multi-degree-of-freedom motion equation; determining dynamic dimensionless parameters based on the multi-degree-of-freedom motion equation and the physical quantities; determining a similarity relationship between the prototype and the scale model based on the static dimensionless parameters and the dynamic dimensionless parameters; performing distortion analysis on the scale model based on the similarity relationship, determining an actual similarity relationship between the prototype and the scale model, and completing scale model design based on the actual similarity relationship.

The invention provides a power line communication nonlinear distortion digital domain compensation method and system, and the method comprises the steps: carrying out the communication health degree monitoring based on a preset health degree index, carrying out the data collection and feature extraction of a power line communication link according to a monitoring result, and generating a communication distortion feature vector; constructing and training a communication distortion analysis model, inputting the communication distortion feature vector into the communication distortion analysis model, and generating an initial communication distortion compensation strategy through a producer sub-module and a consumer sub-module in the communication distortion analysis model; performing adaptive optimization on the initial communication distortion compensation strategy based on a double-delay depth deterministic strategy gradient algorithm to generate an optimal communication distortion compensation strategy; through the communication distortion analysis model and the decomposer sub-module, decomposition diagnosis is carried out on the compensation effect after the optimal communication distortion compensation strategy is executed, and feedback optimization is carried out on the communication distortion analysis model according to the decomposition diagnosis result, so that the efficiency and accuracy of power line communication nonlinear distortion compensation are improved.