645 results about "Transfer function" patented technology

The invention relates to the technical field of data processing, and discloses a secondary equipment hidden danger mining method and system based on a wave recording file and monitoring data. The method comprises the steps of calculating a conditional probability and intervention probability difference identification causal relationship by analyzing a recording file in combination with equipment topology and protection logic to construct a correlation graph, and performing Fourier transform and wavelet decomposition on a sampling sequence to extract multi-scale features; small signal test excitation is injected, a system identification estimation transfer function is fused with monitoring data to form a health feature vector to judge a health state, and a correlation map and the health state are input into a map neural network to calculate weighted attention coefficients and aggregate neighbor information to predict a fault propagation path; and establishing a degradation model, correcting the failure rate, predicting the residual life and generating a graded early warning report. According to the method and the device, the transformation from passive post analysis to active predictive maintenance is realized, and the timeliness, accuracy and systematicness of hidden danger identification of the secondary equipment are improved.

The invention belongs to the technical field of electronic equipment thermal management, and discloses an electronic equipment thermal field rapid prediction method for multi-physical field strong coupling. According to the method, a layered heat source intensity distribution model is constructed, a grid mapping relation topological graph technology and a boundary node energy conservation compensation mechanism are developed, a multi-time scale coupling transfer function is designed, and a dynamic adjustment strategy based on phase deviation analysis is introduced. According to the method, the non-uniform heat source distribution and thermal diffusion dynamic characteristics under the high-frequency condition are accurately captured, the energy consistency of multi-physical field coupling is ensured, the thermal field prediction precision is improved, particularly, the method has outstanding advantages in the aspect of phase and amplitude prediction of transient thermal response, and meanwhile calculation resource consumption is greatly reduced.

The invention relates to the technical field of micro electro mechanical system sensors and signal processing, in particular to an acceleration sensor temperature drift compensation method and device and electronic equipment, and the method comprises the steps: obtaining the dynamic response data of an acceleration sensor at a plurality of working temperatures; fitting the dynamic response data to obtain a physical parameter and a continuous time transfer function of the acceleration sensor, and determining a digital filter coefficient according to the physical parameter and the continuous time transfer function; fitting based on the digital filter coefficient and the temperature to obtain a linear drift coefficient of the digital filter coefficient and the temperature, constructing a temperature offset compensation model according to the linear drift coefficient, inputting the working temperature of the acceleration sensor into the temperature offset compensation model, and outputting the digital filter coefficient by the compensation model, and performing temperature drift compensation on the acceleration sensor by using the digital filter coefficient. Therefore, the problems of output distortion caused by the dynamic characteristic of the acceleration sensor along with temperature drift, difficulty in realizing effective temperature self-adaptive dynamic compensation and the like are solved.

The invention discloses an MMC intelligent setting and cooperative control method and system based on deep reinforcement learning, and relates to the technical field of power transmission system regulation and control, and the method comprises the steps: obtaining the current operation state data of a converter in a power transmission system, the current operation state data comprising a system frequency, a frequency reference value, a frequency deviation and a frequency change rate; establishing a third-order active closed-loop small signal transfer function based on an active transient feedback compensation algorithm, and decoupling a damping coefficient and a primary frequency modulation coefficient in VSG control through the third-order active closed-loop small signal transfer function; inputting the current operation state data into the trained DDPG intelligent agent for processing, and obtaining an optimization result of the virtual inertia; the optimized virtual inertia is applied to a rotational inertia control link of VSG control, and self-adaptive adjustment of the virtual inertia is carried out through the trained DDPG intelligent agent; the problem that control parameters of a traditional virtual synchronous generator VSG are fixed and are difficult to adapt to system operation state changes is solved.

The invention provides a communication optimization method for topological table persistent storage in efficient parallel computing, belongs to the technical field of storage communication, and aims to avoid pseudo sharing by aligning memory allocation through cache lines, expand local topological coverage through a topological entropy increment driven prefetching mechanism, and improve the reliability of the topological table persistent storage. Boundary processing is accelerated through a pre-calculation period mapping lookup table and a frequency domain transfer function vector, synchronization overhead is optimized through a concurrency control mechanism perceived by a read-write ratio, targeted cache preloading is achieved through stability and jitter degree two-dimensional evaluation, bandwidth consumption is reduced through an increment synchronization mechanism, and the stability of the cache is improved. The communication template is selected or the communication parameters are generated through adaptive conversion by matching the matching degree decision, and the technical problem that the parallel computing performance is reduced due to the fact that the communication overhead is too large in the topological table persistent storage process is solved.

The invention relates to the technical field of semiconductor material photoelectric detection, and discloses a whole-course calibration method of a microwave photoconductive attenuation tester, which comprises the following steps: steady-state optical calibration: establishing reference mapping from light intensity to absolute carrier concentration; performing sweep frequency perturbation measurement at each concentration working point to obtain multiple groups of complex response data; separating an instrument transfer function from sample differential response sensitivity by adopting a system identification algorithm; an integral differential sensitivity reconstruction curve is converted into an absolute calibration model by using an anchor point; starting closed-loop feedback control to lock a specific phase, and verifying the model; and outputting an absolute calibration model and an instrument transfer function as a static reference and a dynamic operator. According to the invention, the absolute concentration anchor point is established through steady-state optical calibration, integral reconstruction is carried out on the differential response sensitivity decoupled by dynamic frequency sweep measurement, and finally, the anchor point is utilized to determine the integral constant, so that the accuracy and reliability of carrier concentration quantitative analysis are improved.

The invention relates to the technical field of suspension system detection, and discloses a suspension system sensor fault diagnosis and signal redundancy fault tolerance method and system, and the method comprises the steps: firstly collecting an unsprung acceleration signal and a vehicle speed signal, and obtaining an unsprung acceleration power spectrum through preprocessing and power spectrum estimation; knee point frequency is determined through piecewise fitting, then speed normalization roll-off frequency is calculated, final roll-off frequency is determined, piecewise power law pavement displacement power spectrum priori is established in combination with a vehicle dynamics model transfer function, and an expected output power spectrum is obtained. And dividing an analysis frequency band based on the roll-off frequency, calculating a single-channel normalized energy statistic, setting a fault threshold according to statistical distribution and a significance level, and judging whether the sensor fails or not. If the fault occurs, performing frequency domain regularization inversion by taking power spectrum prior as constraint to obtain pavement displacement power spectrum estimation and generate target channel virtual output; and finally, according to the difference between the statistical magnitude and the fault threshold, outputting a fault-tolerant result.

The invention provides a Prony algorithm-based cable segment wave velocity acquisition method, device and system, and a medium, and the method comprises the steps: testing a to-be-tested cable, and obtaining a cable signal transfer function; on the basis of the cable signal transfer function, in combination with cable joint distribution, constructing a cable signal approximation function based on a Prony method; constructing a linear prediction model of the cable signal based on the cable signal approximation function; performing denoising processing on the linear prediction model based on a singular value decomposition method to obtain a denoised linear prediction model; solving the denoised linear prediction model to obtain an attenuation coefficient; and calculating the segmented wave velocity of the cable based on the attenuation coefficient. According to the method, the Prony estimation method is combined with the singular value decomposition noise reduction algorithm, high-precision extraction of attenuation constants and segmented wave velocity decoupling are achieved, and then the electrical distance positioning precision is improved.

The invention provides a system platform and method for checking adjustment characteristics of a control system based on semi-physical simulation, and belongs to the technical field of power system control equipment detection. The system comprises an all-digital real-time simulation system (ADPSS), a water turbine governor to be tested, a physical interface communication module, a wave recording device and a signal interaction module. A full-electromagnetic example model constructed based on PSASP is built in the ADPSS, a closed-loop detection environment is constructed through the physical interface communication module and a water turbine governor to be detected, bidirectional signal transmission is achieved through the signal interaction module, and key parameters are recorded through the wave recording device. The method comprises the steps of simulation environment establishment, signal interactive transmission, multi-dimensional detection and check and result judgment and output. According to the method, multi-dimensional checking of the speed regulator acquisition and display function, the transfer function consistency, the grid-connected performance and the like and power grid stability influence verification can be completed without field installation, the coverage scene is comprehensive, the checking precision is high, and the method is suitable for performance detection of different types of speed regulators and has remarkable practical value.

The invention belongs to the technical field of grid-connected inverter harmonic analysis, and particularly discloses a grid-connected inverter harmonic closed-loop transmission analysis method and system considering broadband coupling. The method comprises the following steps: respectively establishing a harmonic component transfer function of each module; based on the harmonic component transfer function of the sampling module, calculating to obtain harmonic active power and harmonic reactive power input to the power outer loop control module; based on a harmonic component transfer function of the power outer loop control module, calculating to obtain a harmonic current component in a reference current signal output by a power outer loop; based on a harmonic component transfer function of a current inner loop control module, obtaining a three-phase modulation voltage harmonic component and an inverter port voltage harmonic component through coordinate inverse transformation; on the basis of the inverter port voltage harmonic component, a main circuit harmonic transfer equation is combined, and a grid-connected point harmonic current component is obtained through calculation; the method overcomes the defects that a traditional analysis method cannot consider the control of a whole loop by a closed loop, and the broadband coupling is insufficiently considered.

The invention discloses an unmanned ship target tracking constraint control method based on an exponential time-varying performance function, and relates to the technical field of state tracking control, in particular to the technical field of performance constraint control, comprising the following steps: step (1), establishing an unmanned ship motion three-degree-of-freedom mathematical model; step (2): constructing an exponential time-varying function; (3) constructing an exponential time-varying performance function; (4) introducing a time-varying auxiliary function; (5) designing a transfer function; (6) designing a fixed time performance constraint heading controller based on an exponential time-varying performance function; (7) designing a fixed time performance constraint surging controller based on an exponential time-varying performance function; and (8) performing simulation verification. According to the method, mainly starting from the design of a novel time-varying performance function, the problem that the state error of the traditional performance function constraint control at the initial moment is limited by the performance boundary is solved, so that the transient performance and the steady-state performance of the state tracking error of the unmanned ship are remarkably improved; and the overall control performance of unmanned ship target tracking control is further improved.

The invention belongs to the technical field of wind power generation, and discloses a monitoring and sensing system and method based on a large wind driven generator. The method aims to solve the problem of load prediction deviation of a downwind unit caused by wake flow interference in a fan group array effect. According to the method, the wake flow propagation dynamic topological graph is constructed by obtaining the real-time operation state data of the fan group, and the space influence range and the intensity distribution of the wake flow are accurately represented. And based on the blade turbulence separation feature point set and the wake flow topological graph, identifying a wake flow interference sensitive area of the downwind generator set, analyzing a dynamic gain effect of wake flow interference through a vibration response transfer function, and generating a real-time load prediction correction model. The model is combined with prediction deviation adaptive optimization, and the prediction precision is ensured. Meanwhile, a fan group dynamic risk assessment model is constructed, the operation scheduling strategy is optimized, and the wake flow interference influence is reduced. According to the method, the load prediction accuracy, the unit operation safety and the overall efficiency of the fan group are improved.

The invention discloses a method, device and equipment for determining parameters of a proportional resonance controller and a medium, the proportional resonance controller is applied to a current controller of a three-phase grid-connected inverter, the parameters of the proportional resonance controller comprise a proportionality coefficient, a first damping coefficient and a second damping coefficient, the first damping coefficient is greater than the second damping coefficient, and the second damping coefficient is greater than the first damping coefficient. The three-phase grid-connected inverter further comprises a filter. The proportional resonance controller is low in parameter coupling, can be independently designed, and is simple in engineering implementation; in the target open-loop transfer function, the proportionality coefficient determines the basic proportional gain, the damping coefficient controls the attenuation speed of the corresponding resonance factor, the difference between the first damping coefficient and the second damping coefficient can influence the gain bandwidth, and the larger the difference between the first damping coefficient and the second damping coefficient is, the more significant the attenuation speed difference between the second resonance factor and the first resonance factor is. The wider the high gain interval at the specific frequency of the power grid is, the higher gain is still kept even if the frequency of the power grid fluctuates, and the adaptability and robustness to the frequency deviation of the power grid are improved.

The invention discloses a new energy power system frequency supporting capability quantitative evaluation method and system based on frequency band analysis. Aiming at the frequency response difference of multiple types of power generation equipment in a new energy power system, a unified system frequency response model is established in a frequency domain, and the frequency supporting capability of the power generation equipment under different frequency bands is quantified by adopting a frequency band analysis method. Comprising the following steps: establishing a frequency response transfer function matrix based on a linearized dynamic equation of a multi-machine system; calculating a frequency band H2 / H infinity norm index in a selected frequency range to quantitatively characterize the stability performance of the system in inertia response and a primary frequency modulation stage; through normalization processing of the reference capacity and frequency of the system, comparison of frequency supporting capabilities of different devices and systems is realized. The response difference and contribution of the synchronous machine and the wind and light storage power electronic interface power supply in each frequency band can be accurately revealed, and a unified and effective frequency domain analysis method is provided for frequency modulation control design and frequency stability evaluation of a new energy power system.

The invention discloses a microwave device multi-physics field optimization method taking electromagnetism as a center based on a feature assistance and proxy model. The method comprises the steps of setting initial values of geometric design variables and multi-physics field design variables; the multi-physical field response with electromagnetism as the core responds at the solution point {xg, xm}, multiple pieces of parallel multi-physical field data are generated, and f represents the frequency; according to the multi-physics field data, constructing a feature-assisted multi-physics field agent model based on a neural network transfer function, and calculating a gradient optimization derivative of the feature-assisted multi-physics field agent model; and on the basis of the gradient optimization derivative and the optimization feature auxiliary multi-physics field agent model, obtaining an optimal solution of the variable. According to the method, the robustness and optimization design efficiency of a microwave device multi-physics field optimization algorithm taking electromagnetism as a core are improved.

The invention discloses a VSG grid-connected system control method based on an improved three-parameter wave trap, and belongs to the technical field of power system control, and the method comprises the steps: firstly building a single-input single-output small signal model based on a VSG grid-connected system containing power coupling, and calculating an active open-loop transfer function; an improved active damping resonance suppression method is introduced, so that the transient stability of the system is improved; the expected system stability margin under the system oscillation frequency is obtained, and the parameter design of the three-parameter wave trap is completed based on the subsynchronous frequency oscillation characteristics; the three-parameter wave trap is remodeled, and active steady-state deviation caused by the virtual damping coefficient under power grid frequency disturbance is eliminated. According to the method, the stability of the system is improved, the system is ensured to have a relatively good stability margin, and active steady-state deviation caused by power grid frequency disturbance of the grid-connected system can be completely eliminated.

The invention relates to the technical field of power system frequency stability control, in particular to a power system inertia online evaluation method and device, equipment and a medium, and the method comprises the steps: obtaining frequency deviation data and active power data of each node, carrying out the low-pass filtering of the frequency data, and calculating the amount of active unbalance; an inertia response model is constructed based on the rotor motion equation of the synchronous generator, and inertia and damping coefficients are estimated by using a least square method; constructing a transfer function and judging the stability of the transfer function, if the transfer function is stable, inputting an active unbalance amount to obtain a frequency deviation predicted value, and calculating a Pearson correlation coefficient with an actual frequency; different time periods are selected through a sliding window to repeat the process, finally, the inertia corresponding to the maximum Pearson's correlation coefficient is selected as a system inertia evaluation result, the inertia level of the system can be accurately evaluated on line through the method, and therefore data support is provided for frequency control, and the frequency stability and safety of the system are guaranteed.

The invention discloses a shaft scaling prediction method and system based on a transfer function and machine learning. The method comprises the steps that scaling prediction basic parameters such as fluid pressure, temperature, flow velocity and ion concentration in an oil and gas shaft are obtained and imported into an oil and gas shaft scaling dynamic analysis platform; calling a seepage coupling transfer function scaling prediction model to process seepage related parameters, and establishing a correlation between a fluid seepage state and a scaling initial trend; starting a dynamic transfer function out-of-bag scaling algorithm to dynamically iterate different depth parameters, and outputting a preliminary scaling amount; correcting a preliminary result through a chemical thermodynamic transfer function correction algorithm in combination with parameters such as temperature; and a machine learning model is adopted to train a corrected result and a shaft position parameter, a mapping model is established, a dynamic scaling prediction curve is output, and the platform carries out visualization processing on the curve. The system is matched with the method to realize parameter acquisition, processing, calculation, correction, modeling and display, and the scaling prediction accuracy and the dynamic adaptability are improved.

The invention provides a multi-gas sensing detection method and device based on microwave modulation FLRD, the multi-gas sensing detection device is built based on microwave modulation FLRD, and the method comprises the following steps: determining characteristic frequency and shortest switching time; establishing a multi-wavelength absorption physical model; a gas concentration vector is solved by adopting a regularization inversion algorithm, and regularization parameters are optimized through cross validation; and temperature compensation is realized through an adaptive Kalman filtering algorithm. Compared with a traditional time domain pulse measurement mode, the method can accurately obtain the intra-cavity ring-down time without a high-speed pulse light source and an oscilloscope. According to the method, a network vector analyzer is used for extracting a system transfer function, high-sensitivity and low-noise gas absorption measurement is realized, and the system cost and complexity are remarkably reduced. Parallel recognition of multiple gas components can be realized through frequency domain analysis and a regularization inversion algorithm; and the Kalman filtering algorithm with temperature compensation is combined, so that the measurement stability and the environmental adaptability are effectively improved.

The invention is suitable for the technical field of automatic control, and provides an MPC heating furnace oxygen-enriched combustion control system parameter optimization method based on reinforcement learning, which comprises the following steps: step 1, production line data is acquired, and the acquisition of the production line data is mainly to acquire real data of an actual cement production control production line, including MV, OV and DV data; and step 2, obtaining a state space model, the obtaining of the state space model comprising establishing a model of converting a first-order transfer function into a state space, the MPC parameter adjustment is performed by using the prominent learning ability and adaptive ability of a reinforcement learning (RL) method, the dynamic adjustment according to the change of the system can be realized, and the control accuracy of the system is improved. And training the current oxygen-enriched combustion control algorithm according to the state information under the existing decision-making condition so as to output the expected furnace temperature, and evaluating the effectiveness of the control algorithm through the prepared evaluation standard.

The invention relates to the technical field of microwave semiconductor testing, and discloses a dynamic calibration system for the sensitivity of a microwave photoconductivity tester, which comprises a dual-port orthogonal coupling resonant cavity module provided with a primary port and a secondary port which are orthogonally isolated; the variable capacitance-variable resistance composite modulation perturbation module is connected to the secondary port and is used for generating analog photoelectric response complex impedance disturbance; the vector microwave transceiving and demodulation module is connected to the main port and outputs I / Q signals; the complex impedance track fitting control module is used for driving the perturbation module based on a physical model; the dynamic vector calibration and signal processing module is used for calculating a system transfer function and executing vector projection denoising, the composite modulation perturbation module is used for generating complex impedance disturbance simulating semiconductor photoelectric response at a resonant cavity secondary port, and the vector receiving and transmitting module is combined to obtain a system instantaneous vector transfer function; a system drift error is eliminated by performing de-embedding processing on a measurement signal, and orthogonal noise is eliminated by using a vector projection algorithm.

A system, method, and computer-readable medium having machine instructions provides for predicting geometric shape accuracy of 3D printed products. Such a prediction may involve developing a model of an object and determining ways in which an actually-manufactured 3D object corresponding to the model differs in real life. These differences correspond to shape deviations. Shape deviations may be process dependent and / or path dependent, and different layers of the object as well as the manufacturing process to make the different layers may introduce shape deviations in layers of the object. By developing a transfer functions of the manufacturing process and associated interlayer effects of the layers and then appropriately offsetting inputs to the manufacturing process, the shape deviations may be ameliorated.

Technologies for a jitter injection generator and a spectrum hardware engine for measuring and assessing phase noise and a jitter transfer function are described. One communication device includes a timing and synchronization circuit that generates a signal with time-domain data, and a spectrum hardware engine that converts this data into frequency-domain data. The spectrum hardware engine has registers storing past outputs, multipliers for computing products using these values and a pre-computed coefficient, and a summation block for combining the current input with these products to get the current output. This output is sent to a computing device to estimate phase noise.

The invention discloses a bearing fault diagnosis method and system based on a multi-source weighted frequency spectrum reconstruction model, and the method comprises the steps: carrying out the Fourier transform of a bearing vibration signal, and obtaining a frequency spectrum; performing weighting processing on the frequency spectrum to generate a weighted entropy spectrum; dividing initial frequency boundary points; iteratively adjusting the initial frequency boundary point to obtain an optimized frequency boundary point; constructing a coupling transfer function; performing iterative calculation to obtain a unified frequency boundary point; constructing a filter bank based on the unified frequency boundary points, and performing sub-band segmentation on each weighted entropy spectrum to obtain a plurality of frequency spectrum sub-bands; overlapping and fusing the corresponding frequency spectrum sub-bands which belong to different weighted entropy spectrums and are in the same frequency range to obtain a reconstructed frequency domain signal; performing inverse Fourier transform on the reconstructed frequency domain signal to obtain a reconstructed time domain signal; performing envelope spectrum demodulation on the reconstructed time domain signal to obtain an envelope spectrum; and determining a bearing fault based on a preset bearing fault type table and the fault characteristic frequency in the envelope spectrum. The method is used for improving the accuracy of bearing fault diagnosis.

The invention discloses a pump station pressure pulsation and vibration response correlation analysis and coupling management method and system, and relates to the technical field of pump station operation state monitoring and intelligent operation and maintenance. A multi-source data sensor module is arranged, a synchronous acquisition mode is designed to acquire different types of signals, then data preprocessing and time-frequency domain joint feature extraction are carried out, a deep belief network-based association identification model is constructed, extracted features are input, a subspace identification method is adopted to establish a transfer function from pressure pulsation to vibration response, and a multi-source data sensor module is established. S3, performing coupling state evaluation based on a coupling strength index and a transfer function, dynamically regulating and controlling flow and pressure by adopting a model prediction control strategy, and feeding back regulated and controlled data to S3 to form a closed-loop management method of acquisition, analysis, evaluation, regulation and feedback; according to the pump station pressure pulsation and vibration response correlation analysis and coupling management method and system, feature information of industrial equipment can be automatically extracted, and the intelligence and accuracy of the equipment are improved.

The invention discloses a parameter identification method for a hydraulic six-degree-of-freedom parallel platform. The parameter identification method comprises the steps of kinematics inverse solution solving; an upper platform pose of the six-degree-of-freedom parallel platform is set, and the expansion amount L of a piston of a hydraulic cylinder is solved through inverse kinematics; a servo motor rotating speed signal is calculated through a controller module for displacement of the hydraulic control single-cylinder system; establishing a flow prediction neural network for predicting the output flow of a hydraulic pump in each single-cylinder system for each single-cylinder system; and establishing a transfer function of the hydraulic cylinder by taking the flow as the input and the displacement of the hydraulic cylinder as the output, and identifying the transfer function of the hydraulic cylinder through a least square method, thereby completing the parameter identification work of the platform. The parameter identification method for the hydraulic six-degree-of-freedom parallel platform has the advantages that the accuracy of identification of the transfer function of the hydraulic cylinder of the platform can be guaranteed, the goodness of fit between a mathematical model and actual dynamic characteristics is improved, the requirement for high-precision motion simulation is met, and the control performance of the platform is improved.

The invention provides a dendritic pipe network thermal dynamic modeling method based on a transfer function, and belongs to the technical field of electric digital data processing. The method comprises the following steps: firstly, establishing an advection diffusion-heat loss control equation of a single pipeline, and deducing a frequency domain transfer function of the single pipeline through Laplace transformation; then combining theoretical analysis and high-precision numerical simulation to accurately calibrate and correct a turbulence temperature diffusion coefficient alpha and a temperature loss coefficient gamma, so that the physical consistency of the model is remarkably improved; the method comprises the following steps: for a dendritic pipe network topological structure, decomposing the dendritic pipe network topological structure into a plurality of independent branches according to heat user load nodes, and constructing a frequency domain expression of the return water temperature of the whole pipe network based on a flow weighting principle; and finally, obtaining a time domain response through inverse Laplace transformation. The method effectively solves the contradiction between the insufficient precision of a traditional node method and the complex calculation of a high-precision numerical method, considers both the modeling precision and the calculation efficiency, and is suitable for the real-time optimization scheduling of the heat supply pipe network in the comprehensive energy system.

The invention discloses a dynamic sound field partition control method based on Kalman filtering, and belongs to the technical field of vehicle-mounted audio and signal processing, and the method comprises the steps: dividing a space in a vehicle into a plurality of grid nodes, measuring a transfer function from a loudspeaker array to each node, and pre-calculating a corresponding filter coefficient when each node is used as a bright region, establishing a database; the method comprises the following steps: acquiring an ear image of a passenger in real time through a sensor, calculating an observation position, and processing the observation position by adopting a Kalman filtering model to obtain an optimal estimation position; and determining the grid node according to the optimal estimation position, calling a corresponding filter coefficient from the database to process the audio signal, and generating a driving signal to control the sound field. According to the method, complex calculation is offline, and accurate prediction and estimation are carried out in combination with Kalman filtering, so that the problems of inaccurate and unstable sound field control caused by sensor noise and operation delay in the prior art are effectively solved, and high-precision and high-real-time dynamic sound field partition control is realized.

The invention provides a method and device for calculating rudder deviation required by unit normal overload of a statically unstable aircraft, and the method comprises the steps: selecting a plurality of calculation state points, and obtaining a small disturbance linearization equation at each calculation state point; a stability augmentation control law is constructed, the pitching moment characteristic of the aircraft is changed by feeding back the attack angle, the pitching damping characteristic of the aircraft is improved by feeding back the pitching angle rate, and therefore the aircraft is not divergent under the control of the stability augmentation control law and has the expected stability and damping characteristic; establishing a calculation model of rudder deflection required by unit normal overload based on a stability augmentation control law and a small disturbance linearization equation at a calculation state point, calculating normal overload by the calculation model through a pitch angle rate, an attack angle and a vacuum speed, and processing the calculation model to obtain a transfer function from a control channel elevator instruction to the normal overload; and calculating a normal overload value generated by unit elevator skewness based on the transfer function, wherein the reciprocal of the normal overload value is the rudder skewness required by unit normal overload.

This invention discloses a method and system for monitoring abnormal data in power grid dispatching. The method includes: embedding multidimensional perturbation codes containing first-type (time-domain delay) and second-type (frequency-domain oscillation) features into dispatching commands; target devices generating physical ripples with specific time-domain fingerprint features in response to dispatching commands, and dynamically selecting a set of responding devices based on node impedance matrices and sensitivity coefficients; target devices and the set of responding devices collaboratively triggering responses with specific frequency-domain fingerprint features, and achieving spatial multiplexing verification through a time synchronization protocol; extracting time / frequency-domain fingerprint features from feedback data, and performing spatiotemporal consistency verification using a dynamic transfer function model and multivariate mutual information entropy. Furthermore, by periodically injecting false interference data, the survival verification of the monitoring system status is achieved. This invention can effectively monitor system failures and identify covert data injection attacks, significantly improving the security defense capabilities of power grid dispatching.