36 results about "Time domain model" patented technology

The invention belongs to the field of stability analysis of a grid-connected system of a grid-building converter, and particularly relates to a grid-building converter grid-connected resonance risk analysis method considering virtual impedance, which comprises the following steps: S1, establishing a three-phase time domain differential equation and simplifying the equation into a single-phase equivalent time domain model; converting into a harmonic state space model of the main circuit; s2, constructing a harmonic state space model of a control system comprising an active power control loop and a reactive power control loop; s3, introducing a virtual impedance control link, and correcting the voltage amplitude reference phasor output by the reactive power control loop; deriving an expression of a modulation signal disturbance phasor; s4, obtaining a complete frequency domain admittance model YGSC of the network construction converter considering the influence of the virtual impedance; an open loop gain TGFM of the grid converter grid-connected system is constructed; and S5, drawing a Nyquist curve based on TGFM, and carrying out resonance risk determination. According to the method, the interaction dynamic characteristics of the network building converter and the power grid under the influence of the virtual impedance can be accurately represented, and the resonance risk of the grid-connected system is evaluated.

The invention discloses a long-time-domain predictive control and undisturbed switching method for a hybrid system networking converter, and belongs to the technical field of power system control. In order to solve the problems of poor dynamic performance and easy impact of mode switching of a grid construction / grid following converter hybrid system under new energy high-proportion grid connection, the method specifically comprises the following steps: constructing long time domain model prediction current control, replacing a traditional PI current inner loop, performing discrete modeling based on a dq coordinate system, performing double-step prediction compensation delay, and updating reference current through Lagrange extrapolation. The current tracking precision and the harmonic suppression capability are improved; designing an undisturbed switching strategy, unifying an alpha-beta coordinate system and a current control loop, locking a switching angle, synchronizing an initial value of an integrator, and dynamically adjusting reference voltage to ensure that variables are continuous; two strategies are integrated in a hybrid framework, and stable operation and smooth switching under strong / weak power grids and transition working conditions are realized. According to the invention, the total harmonic distortion rate of the grid-connected current is reduced to below 0.85%, and the method has the advantages of no voltage and current impact in switching and enhanced stability and flexibility of the power system.

The invention discloses a nuclear power station load tracking method and system based on hybrid time domain model predictive control, and belongs to the technical field of nuclear power station operation optimization. According to the method, a mixed time domain prediction model based on finite time domain accurate prediction and infinite time domain equivalent approximation is constructed and is used for uniformly representing complex multi-time scale dynamics under the action of multi-physics coupling of the nuclear power station, so that the operation safety and operation constraint of the nuclear power station are strictly guaranteed; the objective of the invention is to minimize a load tracking error in a full time domain range so as to realize rapid and smooth tracking of a power grid load instruction. The hybrid time domain model predictive control designed by the invention can accurately predict the dynamic response of quick change and slow change of the nuclear power station at the same time, and implement closed-loop optimal control through online rolling optimization, thereby not only being beneficial to guaranteeing the safety and stability of load tracking operation of the nuclear power station, but also effectively improving the operation flexibility of the nuclear power station participating in peak regulation of a power grid.

The application relates to the field of photonic device modeling, and discloses a parameterized optoelectronic joint simulation platform construction method for optoelectronic chip design, which is characterized in that, in an electronic design automation platform, a unified model framework of a photonic device is constructed based on a hardware description language, and conversion between frequency domain response and time domain response is realized in the model, including the following steps: a general VerilogA model framework is constructed based on the frequency domain response of the photonic device; a frequency-time domain numerical conversion mechanism is realized in the model; and for the photonic device with dispersion characteristics, a parameterized time domain model is constructed based on a finite impulse response. The application can directly embed the photonic device model into an electronic circuit simulation environment, co-simulate the electronic device, support time-frequency domain analysis of the cascade structure and the loop structure, thereby avoiding the complicated steps of separate simulation by relying on external simulation tools in the process of optoelectronic chip design, and further improving the design efficiency and iteration speed of the chip.

The invention belongs to the technical field of new energy power generation and grid connection, discloses a grid-side converter fault ride-through control structure modeling method, system and equipment and a medium, and aims to solve the problems of difficult modeling, high cost, poor extrapolation and lack of universality caused by dependence on manufacturer internal logic or massive experimental data in the prior art. According to the method, disturbance input and current output data under a limited working condition are acquired, a dimension raising mapping function is constructed to map the input to a high-dimensional feature space, a Koopman operator is solved based on ridge regression to establish a global linear mapping model, active and reactive current reference components are predicted, and the current reference components are optimized. And finally, inputting the current inner loop time domain model to generate a current transient response curve during the fault period. According to the method, high-precision modeling and prediction can be realized only by a small number of samples, and the method has good extrapolation and universality and can be adapted to various fault ride-through strategies.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may report a time-domain model and parameters to indicate how one or more characteristics, such as a phase, of ports used to transmit reference signals can change across time. For example, the UE may determine one or more sets of transmission parameters associated with a reference signal type, where the one or more sets of transmission parameters can enable a receiving device to bundle reference signals of the reference signal type. The UE may transit an indication of these one or more sets of transmission parameters to the receiving device, where the indication can be associated with how a characteristic of the ports of the UE varies across time. Based on the indication of one or more sets of transmission parameters, the receiving device may receive reference signals and bundle (e.g., combine) the reference signals.

The invention relates to the technical field of aircraft flight control, in particular to a high-altitude cleaning unmanned aerial vehicle operation trajectory tracking control method, which constructs a cooperative control system of a self-adaptive prediction time domain model prediction control framework and an event triggering execution mechanism. A controller can select an optimal prediction time domain parameter according to the speed information of the unmanned aerial vehicle, the calculation complexity is effectively reduced while the trajectory tracking precision is ensured, an event triggering mechanism is introduced to intelligently regulate and control the rolling optimization process of MPC, and by setting the dual triggering conditions of a speed threshold and a trajectory tracking error threshold, the trajectory tracking precision is improved. And rolling optimization solution is only executed at the key control node, so that the real-time performance of the system is remarkably improved, and an innovative control architecture is provided for technical breakthrough of the unmanned aerial vehicle in the field of special operation.

The application discloses a hybrid system network converter long-time domain prediction control and non-disturbance switching method, and belongs to the technical field of power system control. In view of the problems of poor dynamic performance of a hybrid system of a network construction / following network converter under high proportion of new energy grid connection and easy impact of mode switching, the method is as follows: a long-time domain model is constructed to predict current control, a traditional PI current inner ring is replaced, a dq coordinate system is discretized to model, double-step length prediction is compensated to delay, a Lagrange extrapolation is used to update a reference current, current tracking accuracy and harmonic suppression capability are improved; a non-disturbance switching strategy is designed, an alpha-beta coordinate system and a current control ring are unified, a switching angle is locked and an initial value of an integrator is synchronized, a reference voltage is dynamically adjusted to guarantee variable continuity; the two strategies are integrated into a hybrid framework, stable operation and smooth switching under strong / weak power grid and transition working conditions are realized. The application reduces grid-connected current total harmonic distortion rate to below 0.85%, has no voltage and current impact in switching, and has the advantages of enhancing power system stability and flexibility.

The application discloses a CLLC resonant converter soft-start method, device, equipment and medium. The method comprises the following steps: a time domain model of a converter under PWM control is established, and a nonlinear mapping relationship between a voltage gain and a duty cycle is obtained by solving; the gain is set to increase linearly with time, and a nonlinear curve of the duty cycle changing with time is back calculated; finally, two-stage control is executed: in the first stage, the duty cycle is increased to a set maximum value according to the nonlinear curve every cycle under fixed high frequency, so that the output voltage linearly rises; in the second stage, the duty cycle remains unchanged, and the switching frequency is gradually reduced to the resonant frequency. The application can completely eliminate the current peak at the starting moment, shorten the forward starting time to one-tenth of the traditional time, realize smooth establishment of the output voltage without overshoot, and effectively reduce the high-frequency requirement of the device and the system cost.

The present application relates to electric bus charging joint scheduling technical field, provide electric bus fixed and dynamic wireless charging joint scheduling method and system. Electric bus fixed and dynamic wireless charging joint scheduling method includes that fixed and dynamic wireless charging coordination problem is modeled as limited time domain constraint Markov decision process, and then the power of fixed and dynamic wireless charging is determined as charging scheduling strategy based on system state, and the optimization objective function is constructed as minimizing cumulative expected energy cost within the set operation period; the optimization objective function is solved by using the rolling time domain model predictive control method, and the terminal SOC shortage cost is decomposed into the expansion and contraction of the stage cost by using the convex potential function, while keeping the optimal charging scheduling strategy, the end of the day requirement is internalized in the rolling time domain of the rolling time domain model predictive control method.

The invention provides a 3D curved surface flexible photovoltaic dynamic topology reconstruction method and a 3D curved surface flexible photovoltaic dynamic topology reconstruction system based on zonal sector grouping and layered optimization, which are characterized in that elliptical Gaussian is used as a prior, and a Markov radius is used for depicting'zonal / sector 'structured grouping of an equal-irradiation isoline: a zonal band is formed along equal-irradiation rays, sectors are subdivided in the zonal band according to azimuth angles when necessary, and the zonal band and the sectors are subdivided according to the azimuth angles when necessary; the in-string irradiation tends to be the same, and the parallel mismatch is reduced; a minute-level template layer adopts rolling time domain model predictive control, and the comprehensive power is maximized, the mismatch is minimized and the switching cost is minimized when the bus voltage is stabilized to be a hard constraint; the second-level local layer executes improved simulated annealing of two-element exchange in a limited neighborhood with'in-band priority and few adjacent band crossing ', and power, mismatch, voltage penalty terms and switching cost are integrated by a unified cost function. The method supports battery-level or component-level topological optimization, can be expanded to multiple light spots and complex shielding, remarkably improves the daily generating capacity, and reduces the bus voltage violation rate.

The invention discloses a method for realizing full-bridge-half-bridge seamless switching of an LLC resonant converter based on hybrid modulation, and aims to solve the problems of resonant cavity energy abrupt change, output voltage fluctuation and resonant current impact caused by the difference of equivalent input voltage gain ratios of full-bridge (FB for short) and half-bridge (Half-bridge (HB for short) modes during topological switching of the LLC resonant converter. And meanwhile, the problems that the switching working frequency matching precision is low and the system is difficult to quickly enter a steady state due to lack of an FB and HB unified time domain model are solved, so that stable and efficient operation of the LLC resonant converter in a wide voltage gain range is realized. Meanwhile, according to the control method, the gain-frequency relation is solved in real time by constructing a time domain model with unified FB and HB modes, and continuous energy transition of the resonant cavity is guided in combination with hybrid modulation seamless switching control, so that the voltage gain adjustment range can be widened without introducing extra hardware, and the parameter adaptability and operation robustness of the control system are improved.

The invention relates to a vehicle-rail-bridge coupled vibration time-frequency hybrid analysis method, device and equipment, a storage medium and a program product, and relates to the technical field of vibration simulation analysis. The numerical calculation efficiency can be improved. The method comprises the following steps: performing analog simulation by utilizing a virtual excitation method based on a track model to construct a vehicle-track coupling frequency domain model, and inputting a track irregularity frequency spectrum into the vehicle-track coupling frequency domain model for solving to obtain a beam-track interfacial force frequency spectrum; inverse fast Fourier transform is carried out according to the beam-rail interfacial force frequency spectrum to obtain a beam-rail interfacial force time history, and whether the wheel-rail force difference value meets a threshold value condition or not is judged; if the wheel-rail force difference value meets the threshold value condition, analog simulation is conducted through a modal superposition method to construct a bridge time domain model, the vehicle-rail coupling frequency domain model and the bridge time domain model are coupled according to the beam-rail interface force and displacement of the current wheel, and a vehicle-rail-bridge coupling frequency domain model is obtained; and vibration time-frequency hybrid analysis is carried out through the vehicle track bridge coupling frequency domain model.

The application discloses a nuclear power plant load tracking method and system based on a hybrid time domain model predictive control, and belongs to the technical field of nuclear power plant operation optimization. The method is used for unified representation of complex multi-time scale dynamics under the multi-physical field coupling of a nuclear power plant, by constructing a hybrid time domain prediction model based on limited time domain accurate prediction and unlimited time domain equivalent approximation. On the premise of strictly guaranteeing the operation safety and operation constraints of the nuclear power plant, the method aims at minimizing the load tracking error in the full time domain range, so as to realize the fast and smooth tracking of the grid load instruction. The hybrid time domain model predictive control designed in the application can accurately predict the fast and slow dynamic responses of the nuclear power plant at the same time, and implements closed-loop optimal control through online rolling optimization. The hybrid time domain model predictive control not only is beneficial to guaranteeing the safety and stability of the load tracking operation of the nuclear power plant, but also effectively improves the operation flexibility of the nuclear power plant participating in the grid peak shaving.

The invention discloses a frequency domain Prony sine parameter estimation method and system based on an improved autoregression model, and a storage medium. The method comprises the following steps: firstly, based on a time domain model and a k-order autoregression model of a to-be-estimated FMCW radar signal, solving an autoregression coefficient equation containing a to-be-estimated sine parameter; the Kth sampling point of the signal time domain is used as a starting point to construct an autoregression matrix equation, non-causal items in the equation are eliminated, an optimized autoregression matrix equation is obtained, and K is determined according to the order k of an autoregression model; converting the optimized autoregression matrix equation into a frequency domain to obtain a simplified frequency domain autoregression equation set; solving the frequency domain autoregression equation set based on a least square method to obtain autoregression parameters; and finally, target parameters are solved through the correlation coefficients. According to the method, the calculation process is simplified, the operation time is shortened, the parameter estimation precision is better, the error is smaller under the low signal-to-noise ratio, the hardware system implementation capability and the data real-time resolving capability are achieved, and the method is highly applied to a sine parameter estimation scene.

The invention discloses an atractydin dispersion solubilizing method based on a deep neural network and strategy optimization, and aims to solve the problems that key quality attributes in online monitoring and closed-loop control in the preparation process are difficult to stably reach the standard, and batch difference and equipment safety are difficult to consider at the same time. According to the invention, uncertainty prediction is carried out by combining a multi-mode cross-attention depth model with energy sensing position coding and sensor reliability weighting and controlling affine and a Shenchang differential equation with physical constraints, and self-adaptive parameter adjustment of a rolling optimization driving actuator is predicted and controlled by a double-time-domain model of a probabilistic security constraint and control barrier function. The technical effects of online accurate prediction and stable standard reaching of key quality attributes (including the median diameter of the particle size, the polydispersity index, the electrokinetic potential and the dissolution curve), smooth action, energy consumption reduction and process and equipment safety control are achieved.

A method for analyzing the dynamic characteristics of an air spring is disclosed, establishing time-domain and frequency-domain models of its dynamic characteristics. The method includes: identifying parameters of the effective area and volume of the air spring through experimental methods; fitting the friction force using a friction model; establishing a differential equation for the internal air pressure change of the air spring and identifying the heat transfer coefficient through experimental methods; establishing a time-domain model of the air spring's dynamic characteristics; linearizing the time-domain model to establish a complex dynamic stiffness model of the air spring; and establishing frequency-domain models of the air spring's dynamic stiffness and hysteresis angle based on the complex dynamic stiffness. This invention offers the following advantages: it can predict the force-displacement relationship of an air spring under excitation at any frequency; it provides a method for identifying the heat transfer coefficient; and it can predict the dynamic stiffness and hysteresis angle of the air spring under different excitation amplitudes and frequencies.

The present application relates to the technical field of circuit protection, in particular to a DC filter protection method based on digital twinning, comprising the following steps: S1, setting current and voltage measuring devices in the filter circuit, collecting current signals and voltage signals; S2, constructing a digital twinning model according to the filter circuit, wherein the digital twinning model comprises time domain and frequency domain models established according to KCL and KVL laws; S3, calculating the predicted values of the current and voltage of the measuring point by using the digital twinning model of step S2, and performing normalized residual sum of squares on the measured current and voltage values collected in step S1; S4, judging the internal and external faults of the circuit according to the chi-square value of the normalized residual sum of squares of step S3, and determining the circuit protection action. The present application simultaneously uses time domain and frequency domain to distinguish faults, the frequency domain model is used to determine whether the filter has failed, the time domain model is used to distinguish internal faults and external disturbances, and the protection misoperation is prevented, so that the filter can reliably act and protect the safe and stable operation of the filter when the filter harmonic impedance changes, short circuit faults and other conditions occur.

This invention relates to the field of energy-saving planning technology, and more particularly to an energy-saving planning method for multi-segment driving of electric vehicles based on signal-sequential logic. The method includes the following steps: acquiring global topology information and dynamic traffic information of the target driving path; constructing a multi-layer weighted spatiotemporal graph model based on the global topology information and dynamic traffic information; collecting corresponding state information in real time, and constructing a fused mechanical-electrical-thermal coupled dynamics vehicle prediction model based on the multi-layer weighted spatiotemporal graph model and the real-time collected state information to predict the future vehicle state trajectory under different driving strategies; formalizing it into a temporal logic proposition within the signal-sequential logic framework and embedding it into a finite-time domain model predictive control problem; and generating a corresponding collaborative optimization sequence by solving the finite-time domain model predictive control problem with embedded temporal logic constraints, thereby achieving integrated energy-saving planning for driving, energy, and heat. This invention can significantly alleviate range anxiety in electric vehicles.

The application discloses a nonlinear time domain characteristic analysis method and system of a giant magnetostrictive transducer. The method comprises a segmented magnetic circuit magnetic field model of the giant magnetostrictive transducer under the consideration of a permanent magnet bias magnetic field, a solid mechanics model of the giant magnetostrictive rod under the consideration of a magnetostrictive effect of the giant magnetostrictive rod, and a pressure acoustic model of underwater vibration of the transducer, a coupling strategy of an electromagnetic field and a solid mechanics field is constructed, and a coupling strategy of the solid mechanics field and a pressure acoustic field is constructed, so that a nonlinear time domain model of the whole electric-magnetic-mechanical-acoustic coupling of the giant magnetostrictive transducer is established, time domain output characteristics of the transducer model are analyzed under different bias magnetic fields and prestress conditions, and thus a method is provided for the design of the giant magnetostrictive electroacoustic transducer.

The invention discloses a rapid optimization method for an output hose laying linetype under the action of multiple sea conditions considering storm correlation, and relates to the field of ocean oil and gas resource development, the method comprises the steps: generating a storm parameter sample with correlation based on Nataf inverse transformation, decoupling a design variable through parameter conversion, obtaining a design variable sample in combination with Latin hypercube sampling, and carrying out the optimization of the output hose laying linetype under the action of multiple sea conditions; constructing a sample matrix; establishing a full-coupling time domain model, and obtaining a hose response extreme value data set through time domain simulation; a multivariate input agent model is constructed based on deep learning and Bayesian optimization; and finally, rewriting the objective function, and incorporating the proxy model into an NSGA-II algorithm to complete multi-objective optimization to obtain a Pareto frontier solution. On the premise of considering the wind wave correlation, efficient and accurate optimization of the hose line type under multiple sea conditions is achieved, the safety and reliability of the hose structure are improved, and the method is suitable for optimization design of the oil and gas output hose of the offshore floating type production platform.

The invention relates to the technical field of process safety operation, in particular to a process continuous operation method and system, electronic equipment, a storage medium and a program product, and the method comprises the steps: constructing a time domain model according to a dynamic mechanism of a process system; converting the time domain model into a complex frequency domain model through Laplace transformation; solving a complex frequency domain optimal continuous operation variable based on the complex frequency domain model, and converting the complex frequency domain optimal continuous operation variable into a time domain optimal continuous operation variable through inverse Laplace transformation; and performing continuous operation based on the time domain optimal continuous operation variable. According to the process continuous operation method, an analytical method based on a complex frequency domain is provided, continuous working condition switching of a complex chemical system is achieved, compared with a subsection control strategy, the continuous control strategy can describe the real situation as much as possible, feature details of operation variables are clearly presented, higher information density is achieved, and the method is suitable for large-scale popularization and application. And therefore, the safety and the stability of the production process can be improved.

The application provides a state space-based multi-line DC power flow controller modeling and control parameter optimization method, the instability of the DC network ring network system caused by the addition of the DC power flow control is made up by adding the matrix E containing PI control, and the influence of the phase margin and the dynamic characteristic is considered, the game optimization of the control parameters in the dynamic time domain model is carried out based on the eigenvalue, and the application has high universality and strong portability, and has high guiding significance for improving the control performance and optimization ability of the line-to-line power flow controller. The application models the multi-line DC power flow controller, breaks through the barrier of the scale expansion of the DC power flow controller, has the advantages of simple structure, high universality, strong applicability and the like, and provides a model basis for the subsequent research of the DC power flow controller.

The application discloses a kind of circular or spherical part layout system convergence judgment method, electronic equipment and storage medium, using discrete element method to be dispersed into independent unit with each circle or ball in container;According to the degree of collision deformation selection model;Based on impulse principle, the contact force between circle or ball is calculated;The motion differential equation of single circle or ball in vertical direction is established, and the second-order transfer function is obtained;Respectively, time domain model and complex frequency domain model are established, and the convergence under single disturbance and multiple disturbance is simulated and verified;By adjusting the disturbance amount value, the angle between the center line of the two intersecting circles and the horizontal direction, repeat the steps to predict the convergence under different conditions. Different types of circular (spherical) objects can be used to provide efficient and accurate convergence determination for layout optimization, maximize the use of raw materials and reduce waste. Avoid the problem of layout divergence caused by unstable object movement.

This invention provides a real-time speed control method and system for injection in a die-casting machine. The system includes a human-machine interface, an Ethernet communication interface, an MCU controller, an FPGA high-speed execution unit, a sensor group, and an execution mechanism. The FPGA performs data acquisition, pressure / flow inner loop, amplitude limiting and slope limiting, and parallel drive of valves and pumps. The MCU obtains speed feedback based on the injection plunger position, servo pump speed, and injection chamber pressure change rate according to the outer loop scheduling cycle, and performs stage identification, online parameter identification, candidate model selection, expansion state observer disturbance compensation, and short-time domain model predictive control of the switching window. This method reduces stage switching impact and pressure overshoot by identifying the hydraulic execution channel pilot in the low-speed safety detection interval before injection, performing multi-anchor point curve superposition calibration, stage authorization token interlocking, and multi-source residual fault reconstruction, thereby improving injection accuracy, batch consistency, and operational safety.

The application relates to an adaptive online fault diagnosis method and system, and belongs to the field of fault diagnosis. The method comprises the following steps: constructing a time domain model and a frequency domain model; dividing a time domain vibration signal into a plurality of time sequence segments, and performing real number discrete Fourier transform on each segment to obtain a frequency domain signal; training the model by using the time domain signal and the frequency domain signal respectively to obtain a time domain source model and a frequency domain source model; initializing a target domain time domain model and a target domain frequency domain model based on source model parameters; replacing a batch normalization layer in the target domain model with an instance-aware batch renormalization layer; performing Fourier transform on an online small batch signal, and inputting the signal into the target domain model to calculate uncertainty loss and consistency loss; and traversing all small batch data to obtain a fault diagnosis result. The application solves the problem that under the conditions of online and passive data, the statistical estimation capability is weak due to the fact that time domain and frequency domain information cannot be used simultaneously.

The application discloses a model parameter identification method suitable for fuzzy PID control, and comprises the following steps: step (1), a first-order inertia plus pure lag FOPDT model suitable for adapting dynamic characteristics of a temperature control system is established; step (2), inverse Laplace transformation is carried out on a transfer function of the FOPDT model, a complex frequency domain model is converted into a time domain model, and a noise term e(t) is introduced in combination with interference factors existing in actual operation of the temperature control system to modify the time domain model. The application can realize accurate identification of dynamic characteristics of a controlled object in the temperature control system, provide a reliable model basis for adaptive setting of fuzzy PID control parameters, effectively solve the problem of poor parameter adaptability in traditional temperature control, guarantee high precision and long-term stability of the temperature control process, and can be widely applied to fields, such as industrial kilns, constant-temperature laboratories and semiconductor manufacturing, which have strict requirements on temperature control precision.

The invention relates to the technical field of digital image processing, and discloses a night vision image noise reduction method based on a double-domain joint model, comprising the following steps: acquiring an original Bayer domain image; inputting the images into a time domain noise reduction model and a frequency domain noise reduction model in parallel to obtain a time domain noise reduction image and a frequency domain noise reduction image respectively; the time domain model is a convolutional neural network, and random noise is suppressed in a spatial domain; the frequency domain model filters periodic noise in a frequency domain by learning a frequency domain mask; through an attention fusion mechanism, dynamically calculating weights according to the feature maps before fusion of the two models, and performing weighted fusion on the two noise reduction images to generate a target noise reduction image; the model performs end-to-end training by using a global loss function including time domain loss, frequency domain loss and domain alignment consistency loss. According to the method, the contradiction between mixed noise suppression and detail reservation is effectively solved, and the definition and visual quality of the night vision image are improved.

This invention belongs to the field of new energy power generation grid connection technology, and discloses a modeling method, system, equipment, and medium for grid-side converter fault ride-through control structure. It addresses the problems of difficult modeling, high cost, poor extrapolation, and lack of versatility in existing technologies due to reliance on manufacturer-internal logic or massive experimental data. The method acquires disturbance input and current output data under finite operating conditions, constructs an up-dimensional mapping function to map the input to a high-dimensional feature space, establishes a global linear mapping model based on ridge regression to solve the Koopman operator, predicts active and reactive current reference components, and finally generates the current transient response curve during the fault period using the inner-loop time-domain model of the input current. This invention requires only a small number of samples to achieve high-precision modeling and prediction, has good extrapolation and versatility, and can be adapted to various fault ride-through strategies.