25 results about "Response characteristics" patented technology

The invention discloses a power system frequency response characteristic parameter measurement method and a related device, and the method builds a parameter inversion method based on a frequency dynamic response characteristic by actively injecting power disturbance of a set frequency into a grid-connected point of a power system and combining the high-precision extraction of a system frequency variation. The equivalent inertia and the equivalent damping of the system can be quantitatively calculated; the injected disturbance signal has a fixed frequency and a settable amplitude, so that high-precision measurement can be realized in a normal operation state, a large disturbance event or environmental noise depending on a system is avoided, and good experimental repeatability and engineering adaptability are achieved; compared with an off-line evaluation method depending on fault disturbance, response testing and parameter estimation of the system in a non-fault state are achieved through active disturbance, the potential of online and periodic measurement and supporting capacity dynamic updating is achieved, and efficient technical support is provided for new energy field station grid-connected evaluation and dispatching access assessment.

The invention provides a DC system fault positioning method based on an improved variable frequency signal injection method, and the method comprises the steps: firstly, injecting AC signals of different frequencies into a bus of a DC system, and collecting the response current of each branch after the AC signals are injected; then, screening the response current through a signal processing algorithm to obtain a response characteristic quantity, and calculating a response ratio of each branch according to the response characteristic quantity; and finally, based on the response ratio of each branch, judging the branch with the fault through a numerical comparison method. According to the method, the frequency conversion signals are injected at the two ends, branch feedback detection and corresponding signal algorithms are combined, and the feedback result is processed by utilizing ratios, so that the operation steps are simplified, the requirements of detection equipment are reduced, the influence of interference signals on the final judgment result can be reduced through algorithm combination processing, and the overall detection accuracy of the method is improved.

Provided is a machine learning image processing method, wherein: a first frequency characteristic of a first teacher image is calculated; a sample frequency characteristic of a sample image, which serves as a sample of a low-quality image obtained by imaging with a low-image-quality endoscope, is calculated; a ratio of the sample frequency characteristic and the first frequency characteristic is calculated as a first frequency response characteristic; the first frequency response characteristic is compared with a predetermined second frequency response characteristic for student image generation; when a Nyquist frequency of the first frequency response characteristic is N2 and a Nyquist frequency of the second frequency response characteristic is N1, if N1 < N2, the image size of the first teacher image is reduced to generate a second teacher image; and if N1 ≥ N2, the first teacher image is reduced in image quality using a low-pass filter set on the basis of the second frequency response characteristic to generate a first student image.

The invention discloses a method and device for detecting screen body defects of a flexible OLED screen and a storage medium. The method comprises the following steps: dividing a to-be-detected screen body into micro-units and collecting optical reflection signals of the micro-units; applying a controlled deformation stress to the micro-unit and collecting an optical signal under the stress; calculating a local response curve based on response characteristics and extracting characteristic parameters such as amplitude change, slope, peak value and nonlinear fluctuation; comparing the characteristic parameter with a healthy area reference to generate a first defect sensitivity parameter and a defect type; performing consistency analysis in combination with the characteristic parameters of the neighborhood micro-units to obtain second defect sensitivity parameters; inputting the micro-unit thickness, the interface characteristics and the second defect sensitivity into a pre-configured local WVTR model, and calculating a local WVTR value; and finally, combining the second defect sensitivity parameter to generate and output defect data. According to the method, through stress response and neighborhood consistency analysis and in combination with a local WVTR model, micro-unit-level defect accurate identification is realized.

The invention provides an artificial intelligence-based industrial boiler coking prediction method and system. The method comprises the steps of infrared thermal image time sequence acquisition, multi-spectral dynamic threshold segmentation, acoustic impedance feature extraction, multi-modal working condition fusion, space-time attention prediction modeling and adaptive threshold decision triggering. According to the method, the local threshold values are adaptively calculated on different spectral bands such as short waves, medium waves and long waves, response characteristics of all temperature zones can be considered, the false detection and missing detection risks caused by the fixed threshold values are remarkably reduced, and high-temperature hot spots are extracted more accurately and reliably; acoustic impedance characteristics obtained through calculation quantitatively reflect the structure and viscosity change of a coking layer by using attenuation and time delay information of sound waves in an ash layer, a direct and fine physical basis is provided for subsequent rheological property inference, and the defect that mechanical changes of materials are difficult to capture through pure temperature monitoring is effectively overcome.

The invention relates to the technical field of vehicles, in particular to a vehicle frequency response characteristic evaluation method, device and system and a medium, and the method comprises the steps: obtaining an unsprung signal obtained through the uniform acceleration simulation of a long-wave road surface; extracting a low-pass filtering signal in the unsprung signal, and identifying an upper envelope line and a lower envelope line of the low-pass filtering signal; processing the unsprung signals based on the upper and lower envelope lines to obtain time-frequency spectrums, and generating a frequency-vehicle response characteristic curve based on the time-frequency spectrums of all the unsprung signals; calculating an evaluation index of a target frequency band in the frequency-vehicle response characteristic curve; through frequency conversion excitation signal processing, the frequency response characteristics of the vehicle under different road conditions and vehicle speeds are accurately reflected, and the comprehensiveness and accuracy of evaluation are improved.

This invention discloses a method and system for evaluating the effect of wellbore grouting based on change attribution, relating to the field of grouting quality evaluation technology. The method includes: acquiring pre-grouting and post-grouting data for the same detection well; extracting baseline defect characteristics from the pre-grouting data and establishing a pre-grouting defect template; constructing a non-grouting reference response based on the pre-grouting defect template and combining the response patterns of stable sections and adjacent background changes; extracting measured response characteristics from the post-grouting data; calculating the grouting action and residual defect amount using dual-channel quantization based on the measured response characteristics, the non-grouting reference response, and the pre-grouting defect template; identifying change attribution based on the grouting action and residual defect amount to obtain initial attribution results; and performing section-level continuity optimization based on the initial attribution results to obtain the grouting effect evaluation results.

The present invention discloses a method for power system regional division that takes into account the frequency and time-space distribution characteristics. The method models the equipment side and the network side of the new energy power system respectively to obtain a closed-loop frequency response model of the system, decomposes the frequency response into multiple components based on the spectral decomposition of the system hysteresis matrix; analyzes the response characteristics such as the lowest frequency point and the average change rate of each frequency component to quantify the frequency and time-space distribution characteristics; measures the frequency of the PMU configuration node when disturbances occur at different locations of the system through simulation, and uses the measured frequency response curve after modal decomposition and an improved spectral clustering algorithm to construct a similarity matrix and a Laplace matrix to extract the eigenvector of the modal frequency; finally, uses the DBSCAN clustering algorithm to cluster frequency curves with high similarity to achieve system partitioning; the present invention can quickly and accurately provide real-time system partitioning results, ensuring the consistency of regional frequency responses under various disturbances.

The invention relates to the technical field of performance testing, in particular to a frequency response characteristic testing method and device based on an FPGA, and the method comprises the steps: obtaining the test configuration information of a to-be-tested product, and carrying out the configuration of the frequency response characteristic testing device according to the test configuration information, the test configuration information at least comprises a test mode and a frequency response test parameter; generating a digital excitation signal based on the frequency response test parameter; determining a reference signal and a tested signal of the product to be tested according to the test mode and the digital excitation signal; and performing frequency response analysis on the product to be tested according to the reference signal and the tested signal to obtain a frequency response characteristic test result of the product to be tested. The method and the device have the effects of improving the frequency response characteristic test effect and the universality.

This technology offers advantages in improving control accuracy through feedforward control, even in environments containing disturbances with low reproducibility. [Solution] The control device includes a determination unit that determines the gain of the feedforward controller based on a control deviation data sequence showing the change in the control deviation of the controlled object and a response data sequence showing the response characteristics of the controlled object when a specific manipulated variable is applied to the controlled object. The determination unit generates a representative value data sequence consisting of representative values ​​of the control deviation of the controlled object at each time based on a plurality of control deviation data sequences acquired multiple times, and determines the gain based on the representative value data sequence and the response data sequence.

The application provides a kind of advertisement information service-oriented traffic load monitoring method, system and medium, by obtaining the service node load state record sequence corresponding to the time stamp of advertisement request stream data sequence in the preset monitoring period;Advertisement request stream data sequence is decoupled and rhythm extraction is carried out to request source, and the request impact conduction time sequence description is generated by cascading propagation in combination with advertisement position request propagation topological structure, and the time sequence distribution feature representation is extracted, while the load change feature representation is extracted to load state record sequence;Call traffic load collaborative analysis network to carry out collaborative interaction mapping to two kinds of feature representations, generate associated response characteristic representation;Associated response characteristic representation is carried out load bearing situation deduction, and load bearing capacity boundary description is obtained;According to the boundary description, generate traffic scheduling guide instruction and push to advertisement request distribution component to trigger request shunt adjustment.The application can improve the accuracy of load bearing capacity boundary determination.

The application discloses a mass detection method and system for the internal part of a slab track, and relates to the field of railway track engineering. The method comprises the following steps: constructing a multi-point excitation and multi-source sensing cooperative collection system in a target track section, applying a preset excitation load to the track slab, and synchronously collecting structural response data; combining the layered structure characteristics of the track, establishing an interlayer response transmission relationship, and mapping the response data into response characteristic parameters; performing disturbance sensitive feature extraction to obtain multi-dimensional response features; calling reference response features to compare and analyze the multi-dimensional response features to generate difference response characteristics; inverting and positioning the abnormal areas in the track structure to obtain defect position and degree data, and outputting the results. The application solves the problems of weak deep defect identification ability, inability to continuously quantitatively evaluate and easy to cause structural damage in the existing track internal quality detection, and achieves the effects of accurately identifying deep hidden defects, realizing global continuous quantitative detection and full-process non-damage.

This vehicle control system, which is a system for controlling a vehicle, comprises a control force calculation unit that calculates a control input, and a frequency response characteristic adjustment unit that adjusts a frequency response characteristic in the control input. The frequency response characteristic adjustment unit adjusts the frequency response characteristic in a fixed-point frequency band determined on the basis of a fixed point at which the magnification of vibration from a disturbance and vehicle body vibration caused by said vibration does not change irrespective of the control input.

The invention discloses a rolling bearing fault modeling and response prediction method based on defect edge evolution, and belongs to the technical field of mechanical system dynamics and health state evaluation. Firstly, a rolling bearing dynamical model is established based on a lumped parameter method, a raceway defect is divided into three parts according to the running state of the defect of a rolling body, and independent parameters are introduced to describe the morphology characteristics of each part of the defect. And establishing a segmented time-varying displacement excitation function based on the geometric parameters, coupling the segmented displacement excitation function to a nonlinear contact model to form a kinetic equation containing local defect characteristics, and calculating the time-history response of the system. According to the method, time domain and frequency domain analysis is carried out based on a time history response result, prediction of bearing response characteristics under different defect morphologies and evolution processes is realized, the method has high prediction precision and good engineering applicability, and effective theoretical and method support is provided for fault mechanism modeling, state monitoring and service life evaluation of the rolling bearing.

The invention discloses a response characteristic-based multi-agent event trigger control transient state and sesame phenomenon analysis method, which comprises the following steps of: applying measurable input to a leader agent and each follower agent, acquiring output, identifying impulse response of the leader agent and the follower agent, and expressing the impulse response as a power function attenuation form; the convolution input and output relation is converted into an algebraic equation through orthogonal transformation, and a fractional order differential model of each agent is established; under an event trigger mechanism, control input is modeled as a segmented step function, impulse response is utilized to carry out convolution solution on output, a steady-state component and a transient component are separated, and a collaborative error model containing historical transient influence is constructed. And further constructing a positive definite Lyapunov function, deducing an additional threshold considering a historical transient component in combination with a fractional differential comparison principle, and solving a minimum safety triggering time interval. And when the adjacent triggering interval is smaller than the threshold value, false triggering caused by the transient state is judged, and the signal is shielded, so that the sesame phenomenon is effectively eliminated, and the communication overhead is reduced.

The application provides a gyro track level data correction method and system based on feature alignment, which comprises the following steps: collecting track level parameter signals respectively; aligning gyro data samples and inclination data samples by head and tail double-end constraint; calculating residual data of the gyro coarse alignment data and the inclination data samples, and dividing the residual data into multiple segments and marking the segments; identifying multiple feature wave bands of the gyro coarse alignment data in a non-screening interval, and searching corresponding wave bands matching the feature wave bands in the inclination data samples; adjusting the amplitude of the feature wave bands of the gyro coarse alignment data through the corresponding wave bands; and adjusting non-feature wave bands of the gyro data samples and combining the feature alignment gyro data samples. The gyro data of the application has good dynamic response characteristics and static precision matching the inclination data, and has strong robustness, high efficiency and high accuracy, which helps to obtain more accurate and stable track level data.

The present disclosure details a versatile system for providing a digital system that evaluates one or more responses received from a subject of the system. The system provides a subject profile, comprising subject-specific historical, functional, clinical, or operational data relevant to the subject. A query engine provides one or more queries, or adaptive guidance, for the subject—and a digital agent is provided to interact with the subject in real time via a query or adaptive guidance from the query engine. One or more sensor devices communicate(s) or record(s) a response characteristic of the subject during interaction with the digital agent, and evaluation engine evaluates unified data based upon the subject's response to a query or adaptive guidance, in combination with the response characteristic.

The present application relates to a kind of tunnel lining thickness and back cavity acoustic quantitative fast detection method and system, the method includes the following steps: collecting the tunnel lining vibration response characteristics measured by non-contact, obtains stress vibration time domain curve;Based on the stress vibration time domain curve, signal time-frequency domain conversion is carried out, the frequency domain distribution diagram of response characteristic is obtained, and peak value characteristic extraction is carried out, wherein the peak value characteristic includes radial characteristic peak value and longitudinal characteristic peak value;Based on the peak value characteristic and the frequency domain distribution diagram of response characteristic, the inversion calculation of tunnel lining longitudinal, radial size and back cavity state is carried out, realizes the acoustic fast quantitative detection of tunnel lining thickness and back cavity state.Compared with prior art, the present application has the advantages of non-contact approach, high detection accuracy.

The invention provides a multi-mode control-based servo drive comprehensive management method and system, and relates to the technical field of industrial automation control, and the method comprises the steps: firstly constructing an operation scene demand portrait containing operation constraint, power output and environment interaction requirements, and associating scene changes with control demands; then performing structured processing on the control mode to generate a mode feature set containing core functions, parameter adjustment and time sequence response features; then collecting real-time operation data, and calling a feature set through association analysis to construct a dynamic response network; generating a multi-mode linkage control instruction based on the dynamic response network, wherein the multi-mode linkage control instruction comprises a feature activation sequence, a parameter adjustment path and a time sequence cooperation scheme; and finally, optimizing the matching rule according to the execution feedback and updating the network link. According to the invention, self-adaptive control and multi-mode cooperation of the servo driving system in a complex scene are realized, and the control precision, the response speed and the system stability are remarkably improved.

The invention provides a control apparatus, a positioning apparatus, a lithographic apparatus, an article manufacturing method, and a storage medium. The control device controls the object on the basis of the feed-forward manipulated variable generated by the feed-forward controller. In one embodiment, an apparatus includes a determiner operative to determine a gain of a feed-forward controller based on a control error data string indicative of a change in a control error in an object and a response data string indicative of a response characteristic of the object when a particular manipulated variable is provided to the object. The determiner generates a representative value data string composed of representative values of control errors of the object at respective times on the basis of a plurality of control error data strings acquired a plurality of times, and determines a gain on the basis of the representative value data string and the response data string.

The application provides a kind of servo drive integrated management method and system based on multi-mode control, it is related to industrial automation control technical field, first, build the job scene demand image containing operation constraint, power output and environmental interaction requirement, and associate scene change with control demand;Then, the control mode is structured, and a mode feature set containing core functions, parameter adjustment and timing response characteristics is generated;Then, real-time operation data is collected, and a dynamic response network is constructed by associating and analyzing the feature set;Based on the dynamic response network, a multi-mode linkage control instruction is generated, including feature activation sequence, parameter adjustment path and timing coordination scheme;Finally, the network link is updated according to the execution feedback optimization matching rule. The application realizes the adaptive control and multi-mode coordination of servo drive system in complex scene, significantly improves the control accuracy, response speed and system stability.

The invention relates to the technical field of control or regulation systems, and discloses a control or regulation system for response characteristic calibration of logging equipment, which comprises a frequency spectrum characteristic extraction module, a topological form locking controller, a thermodynamic benchmark evolution module and an amplitude response calibration controller, a frequency spectrum feature extraction module is used for extracting power values of intrinsic background noise in a passband core frequency band and a stop band edge frequency band, a dimensionless frequency spectrum shape factor is constructed, a topological form locking controller adjusts bandwidth control parameters according to deviation between the factor and a topological constant reference, a physical bandwidth is locked, and the bandwidth is locked. On the premise of bandwidth locking, the amplitude response calibration controller adjusts gain in combination with the deviation between the theoretical target power value calculated by the thermodynamic reference evolution module and the actually measured total power, and the bandwidth is locked by using the intrinsic noise spectrum shape invariant through a double-closed-loop time sequence decoupling mechanism. And the problems of model mismatch and multivariable coupling control caused by no external standard source and aging of devices are solved.

A display device (10) is disclosed which is configured to: select a gaze focus area (Z) as a scan control start point based on a gaze focus position and foveated rendering information, where the gaze focus area (Z) is an area on which a user's gaze is focused; and first apply a scan signal (SC) to the gaze focus area (Z) as the scan control start point. This improves the response characteristics and reduces latency.

The invention relates to the technical field of data analysis, in particular to a chemical detection data analysis method and system based on cloud computing, and the method comprises the following steps: aligning fusion data based on time, extracting an exception generation instruction, archiving an analysis result, and uploading the result to a cloud end. According to the method, collaborative analysis is carried out on sensor data of different sources under a unified time reference, synchronous labeling and time alignment of multi-channel data are achieved by means of relative standard deviation calculation of timestamp differences, and after a multi-parameter structure is fused, a data chain with internal association is extracted through dynamic changes of section slopes; according to the method, the continuous mutation behaviors are recognized and classified and identified, abnormal response features are extracted, condition screening for instruction offset and response frequency is completed at the same time, and data processing has the capacity of cross-source collaboration, abnormal dynamic recognition and feedback linkage through dynamic adjustment of a threshold value. And a closed-loop data analysis process of unified processing, mutation recognition and linkage control of complex chemical detection data is realized.