114 results about "Time constant" patented technology

The invention discloses a server energy-saving system and method based on a lag compensation type dynamic thermal impedance model, and relates to the field of server energy saving.By collecting operation data of a server hardware bottom layer in real time, a multi-dimensional thermal-computing force coupling time sequence atlas is constructed, and based on the multi-dimensional thermal-computing force coupling time sequence atlas, a dynamic thermal impedance model is established. Calculating a heat conduction time constant of hardware in a current environment; establishing a lag compensation type dynamic thermal impedance model based on the heat conduction time constant; constructing a thermodynamic phase space according to operation data; analyzing a noise reduction evolution trajectory in combination with the lag compensation type dynamic thermal impedance model; the method comprises the steps of generating a weighted thermal resonance state vector, activating an adaptive gain MPC predictive damping scheduling strategy based on the weighted thermal resonance state vector, constructing and solving a dynamic weighted multi-objective optimization function, generating an optimal damping scheduling instruction, and thoroughly solving the fan asthma phenomenon that the fan PWM duty ratio fluctuates substantially in a sine mode under the constant computing power load.

The invention discloses a complex medium controllable source electromagnetic multi-parameter three-dimensional inversion method and system, and the method comprises the steps: carrying out the three-dimensional space discretization of an exploration region, and carrying out the multi-time iteration inversion of a discrete exploration region through initializing a multi-parameter geologic model based on a multi-parameter inversion target function, and obtaining a multi-parameter three-dimensional inversion result; wherein the multi-parameter inversion objective function comprises a data fitting constraint, a model constraint and a cross gradient constraint, and the multi-parameter model comprises resistivity, magnetic conductivity, a charging rate, a frequency correlation coefficient and a time constant; and a hexahedral mesh discrete calculation region is adopted in inversion, and a finite element linear equation set is obtained through a vector finite element method, so that multi-parameter three-dimensional forward modeling calculation is realized. According to the method, the induced polarization effect and the magnetic conductivity influence are considered at the same time, multi-parameter three-dimensional inversion is achieved, the application precision and reliability of the controllable source electromagnetic method under the complex geological condition are remarkably improved, and rich geophysical basis is provided.

The invention discloses a multi-modal robot control method and system based on space-time fusion and a liquid neural network. The method comprises the following steps: collecting asynchronous time sequence data of a multi-source heterogeneous sensor, and establishing a unified reference clock and time grid; through a neural phase-locked loop and soft-DTW, learnable synchronization is realized, and an alignment sequence, confidence and a residual error are output; after modal feature coding, fusion features are formed through confidence-gated layered space-time cross attention; a nominal control instruction is generated by the liquid neural network of the self-adaptive time constant; and the command is optimized and corrected in combination with CLF / CBF and QP, and a safe and feasible control command is output. According to the method, uncertainty caused by asynchronization, shielding and the like is effectively inhibited, the path deviation and the collision rate are remarkably reduced, and high precision, high robustness and provable safety are kept in a dynamic unstructured environment.

The invention relates to the technical field of industrial automation control and dynamic simulation, and discloses a centralized control console and 3D model linkage virtual-real simulation system, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit, the load response modulation unit performs energy consumption weight accumulation on all the virtual controlled objects in transient action to generate a global time scaling factor so as to correct an inertia time constant of the system in real time; the dynamic model evolution unit introduces a hard limiting boundary by using an amplitude limiting link and calculates a process variable; the virtual-real closed-loop feedback unit extracts a control deviation signal and drives a physical instrument to generate a nonlinear damping action, and by establishing a global load modulation model based on energy constraint, a discrete control system spontaneously emerges a nonlinear hysteresis characteristic conforming to physical energy conservation under the low calculation power condition without complex fluid network solution.

The invention discloses a vibration test and state monitoring method and system for an in-operation high-voltage circuit breaker, and the method comprises the steps: carrying out the energy propagation time sequence test of a multi-measurement-point vibration signal, constructing an energy flow direction topological graph, and precisely positioning a vibration source region through energy ratio analysis and path backtracking; acquiring a response time constant by adopting an impact response attenuation test, and converting a vibration source into a fault space positioning coordinate through space grid division and rate matching; a frequency-space mapping relation is established based on a fault position, and vibration characteristics are comprehensively described through peak frequency time sequence tracking and nonlinear component identification such as frequency multiplication, modulation and transient state; performing dispersion analysis on the continuous action impact peak value to form an action consistency deviation, and fusing a nonlinear feature set to quantitatively evaluate the mechanical degradation degree; the grading test density is generated according to the degradation state, the time period test unit is determined, the state grading test benchmark is established to realize mechanical state grade judgment, and the equipment operation reliability and the monitoring efficiency are improved.

The invention relates to a frequency converter dynamic performance optimization control method, and belongs to the technical field of power electronics. The method comprises the steps that frequency converter operation and device characteristic signals and external working condition correlation signals are collected in real time and integrated into a multi-dimensional operation data set, an analysis model is built, and a mapping relation is preset; extracting transient characteristics of a device switch, calculating a dynamic impedance parameter based on a mapping relation, and matching a parameter self-tuning rule base to generate a current loop proportionality coefficient, an integral time constant and a modulation wave duty ratio correction; a rotating speed and current double-loop fusion framework is built, the weight of an outer loop is dynamically adjusted according to rotating speed deviation and load sudden change, an inner loop adopts an adaptive reaching law and disturbance compensation, and a cooperative control instruction is generated through inter-loop interaction; monitoring instruction execution data to form feedback, correcting a model mapping relation and optimizing control parameters. The dynamic response precision of the frequency converter under complex working conditions is improved, the anti-disturbance capability is enhanced, and meanwhile, the device operation loss and the manual debugging cost are reduced.

The invention discloses a speed loop two-degree-of-freedom PI control method and device based on feedforward and a medium, and relates to the technical field of speed loop control methods.According to the method, on the premise that the bandwidth of an inner current loop is higher than that of a speed loop, a PI feedback steady state is adopted, and a disturbance observer is used for load disturbance estimation and compensation; feedforward forming is introduced to a given side, a'given-output 'closed loop is shaped into a first-order or critical damping second-order target model, and a disturbance observer time constant, a target bandwidth and a sampling period are systematically set. The device is composed of an error acquisition module, a PI feedback module, a disturbance observation module, a feed-forward forming module and an execution interface module. According to the scheme, under the condition that hardware is not changed, rapid low-overshoot tracking is achieved, the anti-interference performance is not weakened, parameters can be reused, and the method is suitable for servo scenes such as numerical control, robots and stabilized platforms.

The invention relates to the technical field of general control or regulation systems, and discloses an AI-based thermal load prediction and multi-heat-source optimization scheduling system, which comprises a source characteristic storage unit, which is used for dividing heat source equipment into an inertial base load group and an agile regulation group according to a response time constant; the load trend prediction unit is used for calculating a thermal load change slope by adopting a time sequence prediction model; the control instruction generation unit is used for decoupling the total heat load demand by utilizing a low-pass filtering algorithm according to the change slope; the collaborative scheduling unit is used for establishing a frequency division mapping mechanism, mapping a low-frequency base quantity demand to an inertial base load group and mapping a high-frequency increment demand to an agile adjustment group; and the feedback correction unit is used for generating a correction compensation amount and only superposing the correction compensation amount to a control instruction for the agile adjustment group when the change rate of the total return water temperature of the heat supply network exceeds the limit, and adjustment oscillation caused by heat supply network lag is avoided through frequency division decoupling and a targeted feedback framework.

This invention discloses a method for directional experimental verification and performance testing guided by computational simulation in materials chemistry, belonging to the field of materials performance testing technology. The method includes: acquiring the structural parameters of semiconductor devices and initial parameters of interface defects; calculating the characteristic time constant of carrier trapping by interface traps; simulating and generating a theoretical capacitance-voltage hysteresis loop; then performing bidirectional voltage scan tests within a sensitive scan rate range; finally, updating the inversion parameters and resimulating, iteratively adjusting until the characteristic deviation between the theoretical loop and the measured data meets the convergence condition, thus outputting an interface state density distribution map. This invention, through computational simulation-guided directional experiments, achieves accurate capture and non-destructive in-situ characterization of the dynamic response characteristics of interface states, effectively establishing the dynamic structure-property relationship between microscopic interface defects and macroscopic device performance, and significantly improving the accuracy and reliability of interface defect parameter inversion.

The invention relates to a method for setting the parameters of a control of a pressure supply system of a hydraulic system, wherein the pressure supply system has a motor (4) and a hydraulic machine (2) that are controlled with a manipulated variable, wherein the control (160) is implemented by a control algorithm, wherein the control algorithm is parameterised by one or more parameters that can be set or changed during operation, the method comprising: carrying out (110), during operation of the hydraulic system, an estimation method based on a physical model in order to determine an estimated value for at least one characteristic variable of the hydraulic system, wherein the at least one characteristic variable includes a hydraulic capacity of the hydraulic system; determining (120) an adjustment time constant as equal to or greater than a target time constant, by means of which a maximum pressure build-up rate of the hydraulic system is achieved, which is determined by the estimated value for the hydraulic capacity and a maximum volumetric flow rate of the hydraulic machine; setting (150) at least one parameter of the one or more parameters, wherein the at least one parameter is determined (130, 140) by a respective function dependent on the setting time constant.

The invention discloses an intelligent control method and system for a heat supply system, and the method comprises the steps: calculating a temperature control response deviation ratio of each control period according to the difference between actual room temperatures and the difference between predicted room temperatures of adjacent control periods, calculating a response deviation duration index according to the time domain characteristics of a temperature control response deviation ratio sequence, and calculating the temperature control response deviation of each control period; according to mean value characteristics and fluctuation characteristics of a temperature control response deviation ratio sequence and a first-order difference sequence thereof, calculating a thermal characteristic change mode identification index, and combining the two to calculate update quantities of a heat transfer coefficient and a thermal inertia time constant; the room temperature of the next control period is predicted according to the updated heat transfer coefficient and the updated thermal inertia time constant, and an objective function of a multi-objective convex optimization problem is constructed based on the predicted room temperature and the valve adjustment amplitude of all users in the unit; and solving to obtain an optimal valve opening instruction to regulate and control the valve. The precision and stability of thermodynamic balance control are improved.

This invention discloses a method for the collaborative optimization of turbine governor parameters and hydraulic system parameters. The method involves synchronously collecting multi-source operating data from a hydropower station using a sensor network to construct a hydraulic-governing coupled state-space model. Based on the UKF unscented Kalman filter algorithm, the method identifies the water flow inertial time constant, water hammer wave velocity, and turbine integrated transfer coefficient online, and evaluates the reliability of the identification results using a parameter identification confidence index. In a joint high-dimensional space of the control parameter domain and the hydraulic parameter domain, the method uses regulation quality, hydraulic safety, and grid stability as three objective optimization functions to solve for the Pareto front candidate set, and selects robust parameter schemes using a robust stability margin index. A three-level differentiated push strategy is implemented based on the parameter change amplitude, and real-time monitoring and an automatic anomaly backoff mechanism are implemented during the gradual push process. This invention achieves full-cycle collaborative optimization and safe tuning of hydraulic system parameters and governor control parameters.

The invention discloses a circuit reduction method and system based on sparse processing, and the method comprises the steps: A, carrying out the node elimination of a circuit matrix through employing a time constant balance reduction (TICER) algorithm, and obtaining a matrix which is smaller in scale and is dense due to filling; b, deleting redundant non-zero elements by using a spectrogram sparsification algorithm, and meanwhile, keeping the core characteristics of the matrix to obtain a sparsification matrix; and C, judging the density of the matrix, if the sparse effect reaches the expectation, outputting a new matrix after reduction, otherwise, returning to the step of the initial matrix. By the adoption of the method, circuit reduction can be carried out through the method of combining spectrogram sparsification and the TICER algorithm, the matrix density degree is effectively reduced, and the simulation speed is greatly increased; and the circuit reduction effect can be ensured by setting a rollback mechanism.

The application relates to the technical field of industrial automation control and dynamic simulation, and discloses a virtual-real simulation system with linkage of a centralized control operation platform and a 3D model, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit. The load response modulation unit accumulates energy consumption weights of all virtual controlled objects in transient motion to generate a global time scaling factor for real-time correction of the inertial time constant of the system. The dynamic model evolution unit introduces a hard limiting boundary by using a limiting link and calculates process variables. The virtual-real closed-loop feedback unit extracts a control deviation signal and drives physical instruments to generate nonlinear damping actions. The application establishes a global load modulation model based on energy constraints, and under the condition of low computing power without complex fluid network solving, makes the discrete control system spontaneously emerge nonlinear hysteresis characteristics conforming to physical energy conservation.

The invention discloses an IGBT aging monitoring method and apparatus, and an electronic device. The method comprises the steps of obtaining a pre-established first junction temperature expression, a first shell temperature expression and a model parameter conversion model of a to-be-monitored IGBT; the actually measured junction temperature and the actually measured shell temperature of the IGBT to be monitored and initial values of model parameters of the four-order Cauer thermal network model are obtained; fitting the first junction temperature expression in combination with the actually measured junction temperature to obtain a junction temperature initial value coefficient and a time constant; inputting different values of the junction temperature initial value coefficient, the time constant and the model parameter into a model parameter conversion model to obtain a shell temperature initial value coefficient corresponding to each value; inputting each value of the model parameter and the initial value coefficient of the shell temperature into a first shell temperature expression to obtain the shell temperature corresponding to each value; and evaluating the aging state of the to-be-monitored IGBT according to the model parameter corresponding to the shell temperature closest to the actually measured shell temperature. According to the invention, the aging state can be accurately evaluated in real time in different states.

Examples including a system described herein implement a novel liquid time constant neural network (LTC-NN) based architecture to recover an underlying model of physical dynamics from real world data. The automatic differentiation property of LTC-NN nodes overcomes problems associated with low sampling rate, the input dependent time constant in the forward pass of the hidden layer of LTC-NN nodes creates a massive search space of implicit physical dynamics, the physics model solver based data reconstruction loss guides the search for the correct set of implicit dynamics, and drop out in dense layer ensures extraction of the sparsest model. Further, to account for perturbation timing error, the LTC-NN based architecture of the system utilizes dense layer nodes to search through input shifts that results in the lowest reconstruction loss.

The application discloses a transformer operation state self-diagnosis method and system, relates to the technical field of state diagnosis, and comprises the following steps: acquiring and analyzing relevant data in the working state according to test conditions; judging the primary side circuit element state according to the primary side data and an RLC circuit step response time constant formula; calculating the voltage stability according to the secondary side data; calculating the delay duration of the tap switch and the damage degree of the tap switch according to the primary side data; dividing and outputting the state grade; and predicting the first fault time point according to the delay duration and a preset delay duration. The application realizes predictive maintenance by predicting the first fault time point, avoids power failure accidents caused by sudden failures, comprehensively integrates various data of the primary side and the secondary side, combines specific analysis of a circuit model and key components, forms a multi-dimensional and systematic diagnosis system, and realizes comprehensive, intelligent and fine management of the transformer operation state.

The application discloses a control method for primary frequency modulation in a power dead zone range of a hydroelectric generating set, and belongs to the technical field of hydroelectric generating set regulation. The method comprises the following steps: S1, calculating H1 and H2 of a water diversion system according to the water flow inertia time constant of the water diversion system and the mechanical inertia time constant of the generating set; S2, calculating a dynamic analytical expression of the generating set power when a frequency unit step disturbance occurs; S3, calculating a first-order differential link coefficient decomposed by a second-order correction link based on the dynamic analytical expression of the generating set power; and S4, calculating the output of a PID speed regulator in a current sampling period. The scheme calculates the oscillation link transfer function parameters in a dynamic process, and a second-order system correction transfer function of a frequency given value is designed on the basis, so that the oscillation phenomenon of the generating set power does not occur when the frequency given value of the generating set changes, the problem that the power exceeds the power dead zone in the dynamic process is prevented, and a limiting link is arranged at the frequency deviation value to ensure that the power steady-state value exceeds the power dead zone range.

The invention discloses a parameter estimation and adaptive control method, device, medium and product of a high-performance aircraft pitch angular velocity control system with stability margin self-configuration, and relates to the field of aircraft control, the method comprises the following steps: collecting the pitch angular velocity of an aircraft and the deflection angle of an elevator in real time, and calculating a tracking error; constructing a relation equation of system parameters and stability margin based on a PI controller, and performing approximate simplification by adopting a numerical approximation method; estimating system parameters and time delay on line by adopting an approximate nonlinear least square algorithm; and substituting the target stability margin, the system parameter estimation value and the time delay estimation value into a system frequency domain characteristic equation for solving to obtain a proportional gain and an integral time constant of a PI controller, and adjusting an elevator deflection angle of the aircraft in combination with a tracking error so as to control the pitch angular velocity of the aircraft. According to the invention, the autonomous configuration of the stability margin is realized, and the stability, robustness and dynamic adaptation capability of the control system are improved.

The invention discloses a temperature prediction method for a motor component, the motor component comprises at least one of a rotor or a stator, and the method comprises the steps that a motor controller obtains the instantaneous temperature and the current value of the motor component at a first moment, and inquires a first calibration table according to the current value and the position of the rotor, the steady-state temperature of the motor component and the time parameter of the motor component are obtained, and the time parameter comprises at least one of the winding time constant of the stator or the permanent magnet time constant of the rotor. And then, according to the instantaneous temperature of the motor component at the first moment, the steady-state temperature of the motor component and the time parameter of the motor component, predicting the instantaneous temperature of the motor component at the second moment. The data required by the method can be accurately obtained through measurement or query under different working conditions of the motor, so that the method has accuracy and universality.

The invention discloses an electric power simulation adaptability test processing method for a new energy unit, and relates to the technical field of simulation testing, the method comprises the following steps: obtaining PLL bandwidth and controller time constant upper and lower limits, and generating a plurality of parameter combinations; applying each combination to a model, simulating under the disturbance of a preset power system, and collecting dynamic response and numerical stability information for preliminary screening to obtain candidate parameter combinations; the method comprises the following steps: selecting a candidate combination, collecting simulation state information of the candidate combination, calculating a priority selection index, and selecting a group with the maximum index as a final optimization parameter. The optimal PLL bandwidth and controller time constant can be found to balance the dynamic response speed and stability of the electric power simulation model in the electric power system environment, and reasonable global balance is formed between the PLL bandwidth and the controller time constant, so that the applicability of the final electric power simulation model does not deviate to a certain side; and the reliability of behavior prediction of the new energy unit in the power system is improved.

A processing section of an instruction generating device provided separately from a general inverter performs the following processing. A rotation calculating section calculates a value related to rotation of a rotor of a virtual generator when the virtual generator is driven in accordance with a rotor model that calculates a value related to rotation of the rotor of the virtual generator based on simulation of driving the virtual generator and an effective power command. A target determining section determines a target value of a voltage frequency and a target value of an effective power based on the calculated value related to rotation. An instruction generating section generates a control command for the inverter based on the determined target value of the voltage frequency and the target value of the effective power. A time constant related to a synchronous force of the rotor model and a time constant related to a synchronous force of the alternator are identical.

This invention belongs to the field of artificial intelligence and digital data processing technology, and relates to a method and system for predicting the lifetime of LED driver circuits based on machine learning. The method includes: acquiring the ambient temperature, operating voltage, and current sequences of the circuit board containing the core components of the LED driver circuit; extracting the time features of the temperature sequences to determine the cumulative value of dynamic temperature fluctuations; determining a dynamic thermal time constant correction factor based on the cumulative value; reconstructing the temperature sequence according to the correction factor to determine a virtual core temperature condition variable; and inputting the voltage and current sequences as the main input and the virtual core temperature as the condition variable into a pre-trained conditional variational autoencoder to output the remaining lifetime prediction result. This invention can more accurately assess the cumulative effect of ambient temperature fluctuations, scientifically correct the influence of thermal inertia reflected in the heat conduction process, effectively solve the problem of feature decoupling distortion, improve the accuracy and reliability of LED driver circuit lifetime prediction, reduce the risk of unexpected failures, and ensure stable circuit operation.

This invention provides a method for the actual calculation of the inertial time constant of water flow in a hydropower unit. It defines a time-invariant inertial time constant based on rated operating parameters; establishes a rigid water hammer transient transfer function that includes the effects of pipeline hydraulic losses and the inertial time constant, thus avoiding the difficulties in measuring large-diameter flow rates in hydropower stations; establishes a transfer function model between the guide vane opening increment and the volute pressure increment based on the rigid water hammer transient transfer function; and establishes a calculation formula for the inertial time constant based on the measured transient data of the guide vane opening increment and the volute pressure increment, using the transfer function model. By performing tests and calculations near rated operating conditions, this method avoids the difficulty in calculating the overflow coefficient due to guide vane opening deviation, and solves the measurement difficulties caused by the fact that the influence of the inertial time constant only exists in the transient process and disappears in steady state.

The invention belongs to the technical field of electromechanical control, and discloses an electromechanical system soft start and soft deceleration method, which comprises the following steps of: setting a speed set value, a start or deceleration working condition moment value and a time constant; monitoring the actual operation time of the system; calculating an expected tracking signal according to the following formula; and controlling the dynamic response speed of the electromechanical system based on the expected tracking signal to realize soft start or soft deceleration. According to the invention, the impact current in the starting or deceleration process of the system can be effectively eliminated, and the impact torque of load machinery is reduced, thereby achieving the purpose of prolonging the service life of the machine.

The application belongs to the technical field of total temperature sensors, and provides a response compensation method and system for a total temperature sensor, which comprises the following steps: collecting historical temperature data of a transient wind tunnel, removing out-of-range data and noise through sliding window median filtering, verifying the stability of the sensor through RMSE difference comparison, and establishing a first-order lag dynamic response model; combining with working condition parameters, extracting real airflow temperature mutation points through residual verification and establishing a feature set; dividing the mutation amplitude space into a noise suppression interval and a standard compensation interval based on a cumulative distribution function; inversely compensating the noise interval and accelerating the response through dynamic adjustment of the time constant for the standard interval; and the application improves the response speed in short-time measurement scenarios such as transient wind tunnels through interval-based accurate compensation.

The invention discloses a temperature self-adaptive PI control method for flowing glue in a multi-section pipeline. The method comprises the following steps: step 1, identifying a system and setting initial parameters; predicting temperature drop of the steel pipe section; calculating the axial temperature distribution of the glue flowing through the steel pipe section by using a Schhoff temperature drop calculation formula to obtain the inlet temperature of the glue to the glue conveying pipe; establishing a heat balance model of the glue conveying pipe; analyzing the heat transfer characteristic of the glue conveying pipe, and establishing a dynamic balance equation including heating power, fluid heat convection and environmental heat dissipation based on a steady state condition and infinitesimal dynamic heat balance of unit length; feedforward compensation is controlled; on the basis of the heat balance model of the glue conveying pipe, according to a set target temperature, heating power needed for maintaining the temperature is calculated, and the heating power is converted into a duty ratio for feed-forward compensation; deducing a time constant Tdynamic; deriving a function relationship between a time constant T and quantitative flow in the first-order inertia plus pure lag model of the glue conveying pipe; adjusting a self-adaptive PI parameter; and the quantitative flow of glue is monitored in real time, the time constant T is updated, the proportional gain and the integral gain of the PI controller are dynamically adjusted in combination with a Lambda setting algorithm, and self-adaptive control is achieved. Through mechanism modeling, feed-forward compensation and self-adaptive adjustment, the dispensing precision and the system efficiency are remarkably improved, and the method is suitable for industrial application under the condition that the flow speed is frequently changed.

The invention provides a nonlinear predictive control method for a Novolens polypropylene process, and relates to the technical field of nonlinear predictive control of a chemical process, and the method comprises the following steps: S1, building a mechanism model corresponding to a controlled loop according to the internal reaction mechanism of the Novolens polypropylene process, and obtaining the real-time gain of the process; s2, obtaining a time constant and a lag time parameter of the controlled Novolens polypropylene process model; s3, constructing a corresponding mechanism state space model through the real-time gain, the time constant and the delay time; s4, on the basis of the mechanism state space model, state prediction of the controlled Novolens polypropylene process is obtained; s5, an objective function is introduced, and the optimal control input increment of the controlled Novolens polypropylene process is obtained; and S6, performing calculation according to the optimal control input increment to obtain optimal control. The method is used for accurately realizing optimization control of the Novolens polypropylene process.

This invention discloses a fast quasi-peak detector simulation method for EMI receivers based on pulse detection coefficient fitting, comprising: acquiring the amplitude result of the target signal after processing by a peak detector; establishing a quasi-peak response model and determining the pulse detection coefficients; calculating the quasi-peak detection result corresponding to the target signal using the mathematical mapping relationship between quasi-peak voltage and peak voltage; and using the quasi-peak detection result as a fast predictive output to replace the time constant integration of traditional quasi-peak detection circuits for electromagnetic interference assessment. This invention is beneficial for the electromagnetic compatibility design of power electronic equipment and solves the problems of electromagnetic compatibility array testing time and cost.

The invention provides an automatic gain control method for realizing a high dynamic range receiver. The automatic gain control method comprises the following steps: acquiring an intensity value of a signal; determining a signal processing mode according to a threshold region where the intensity value of the signal is located; calculating a gain step value and a self-adaptive time constant through a dynamic gradient gain adjustment algorithm according to a signal processing mode and a threshold region where a signal intensity value is located; and executing signal gain control according to the gain step value and the adaptive time constant. According to the invention, the technical problems of slow response, poor stability and insufficient convergence performance of a traditional AGC scheme in a high dynamic range signal environment are solved.