1060 results about "Transfer function" patented technology

The invention relates to a high-altitude large steel structure corridor safety risk monitoring method and system and a medium, and belongs to the technical field of civil engineering structure health monitoring, and the monitoring method comprises the steps: collecting original monitoring data through a multi-source sensor group disposed at each node of a steel structure corridor; performing space-time alignment processing on the original monitoring data to generate a sensor data matrix; performing dynamic noise suppression on the sensor data matrix based on an environmental noise transfer function model, and outputting a pure signal matrix and a damage characteristic frequency band identifier; calculating a thermal stress sensitive factor, extracting a multi-physical field coupling feature associated with the damage feature frequency band identifier in the pure signal matrix, fusing to generate a high-dimensional damage feature tensor, inputting the high-dimensional damage feature tensor into a pre-constructed digital twinborn risk assessment model, and outputting an assessment result including a risk level label and a damage position coordinate; and matching the regulation and control strategy according to the risk level label, and generating a corresponding equipment control instruction. According to the invention, the scientificity and accuracy of risk decision can be improved.

The invention relates to an AI server cooling water pump vibration quantity self-adaptive calibration test method and system, an intelligent test platform integrates a six-dimensional force sensor and a temperature compensation vibration exciter, the platform rigidity is automatically calibrated, a water pump-pipeline system transfer function is obtained, and a rotating speed-lift-modal frequency three-dimensional mathematical model is established; a three-axis MEMS accelerometer array is arranged at sensitive parts such as a water pump bearing seat and a motor shell, and vibration, current and pressure signals are synchronously collected; carrying out time-frequency domain signal processing by adopting variational mode decomposition in combination with self-adaptive S transformation, and extracting a 128-dimensional full-frequency domain feature vector containing a modulation side frequency band; effective values of vibration acceleration, speed and displacement are calculated through a frequency domain integration algorithm, and current harmonic interference is corrected through an electromagnetic vibration compensation model; and finally, a vibration health degree evaluation model containing 18 characteristic parameters is established based on a support vector machine, the test system comprises an intelligent test platform unit, a multi-source sensing unit, an edge calculation unit and a data management unit, and microsecond-level synchronous acquisition and GB-level data throughput are realized through a time sensitive network. And online incremental learning and automatic generation of a test report are supported. The method has the effect of improving the water pump vibration quantity test precision.

The invention discloses a digital calibration system and method for dynamic response parameters of a surge protection circuit, relates to the technical field of power electronic protection and test calibration, and is used for solving the problem that an existing surge protection circuit calibration method cannot reflect device degradation and dynamic response mismatch. Surge event voltage and current waveforms are collected through a synchronous trigger mechanism, non-stationary signal features are extracted through combined time-frequency analysis, and a voltage-current phase trajectory diagram is constructed to generate a response feature matrix; performing phase-space reconstruction on the matrix, calculating Kolmogorov entropy quantification system stability, and establishing a material degradation transfer function in combination with an energy absorption sequence to generate a grain boundary degradation index; key parameters are screened through L1 regularization regression, and a quantitative relation between a grain boundary degradation index and a protection threshold value is established to realize adaptive threshold value calculation; and executing strategy switching from calibration to predictive maintenance according to the degradation trend and threshold fluctuation change, and outputting a maintenance signal to complete dynamic accurate calibration and reliable operation of the surge protection circuit.

The invention discloses a signal reconstruction denoising method for circuit breaker mechanical state evaluation and a storage medium. In order to solve the problems of multi-source signal aliasing and strong noise interference of the double-break vacuum circuit breaker, a technical route combining mechanical transfer function modeling and a double-flow deep network is innovatively adopted. A complex vibration source is analyzed by constructing a signal coupling model, environmental noise is accurately filtered by using a multi-stage noise reduction strategy, and a multi-dimensional state vector is constructed by fusing time-frequency domain features, so that accurate evaluation of the health state of the equipment is realized. Experiments show that the method is remarkably superior to the prior art in signal denoising, feature extraction precision and diagnosis accuracy, and an efficient solution is provided for intelligent operation and maintenance of power equipment.

The invention discloses a broadband oscillation identification method and system based on a multi-band Nyquist criterion, and the method comprises the steps: dividing the frequency of broadband oscillation into a low frequency band, a middle frequency band and a high frequency band with overlapped frequency bands, and obtaining the oscillation signals of a monitoring node in a power grid in different frequency bands; respectively calculating the equivalent impedance of the non-overlapped frequency band of each frequency band and the equivalent impedance of the overlapped frequency band in the two adjacent frequency bands so as to construct the equivalent impedance of the low frequency band, the middle frequency band and the high frequency band with the overlapped frequency bands; establishing a Nyquist criterion of each frequency band based on a transfer function of dynamic characteristics of each frequency band in an open-loop state of the system; a generalized Nyquist criterion of the overlapped frequency bands is constructed by using the multi-frequency-band coupling matrix; constructing a comprehensive decision function according to the recognition result of the generalized Nyquist criterion on the system stability, the broadband oscillation comprehensive characteristic quantity and the change rate of the high-frequency-band impedance module value along with the frequency; and according to the value of the comprehensive decision function and a threshold value, a broadband oscillation identification result is determined, and the broadband oscillation identification capability is improved.

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 discloses a stability evaluation and optimization method for a multi-infeed series-parallel new energy station based on equivalent external characteristics of a network construction type converter, and belongs to the technical field of electric power automation. Comprising the following steps: constructing a new energy multi-infeed hybrid system stability analysis closed-loop dynamic model, and simplifying a network construction type admittance transfer function; based on a stability analysis closed-loop dynamic model of the new energy multi-infeed series-parallel system, simplifying the new energy multi-infeed series-parallel system into an equivalent single-infeed system, and evaluating the stability of the equivalent single-infeed system through a generalized operation short-circuit ratio and a critical generalized operation short-circuit ratio; analyzing and quantifying the influence of key parameters of the network construction type equipment on the stability of the system through a parameter sensitivity analysis method; a node participation factor is used as an evaluation index, and control parameters are optimized based on a stability optimization method of key parameters of network construction type equipment of system weak nodes. The method provided by the invention has good effectiveness and reliability, and can realize gradual improvement and refined regulation and control of the system stability.

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 belongs to the technical field of power system risk assessment, and particularly relates to a new energy station broadband oscillation risk redisk assessment method based on multivariate data, which comprises the following steps: performing data acquisition and data preprocessing on a new energy station-power grid coupling system to obtain a historical data set; extracting oscillation characteristic indexes to form index vectors; carrying out oscillation frequency source positioning analysis, calculating a time-frequency spectrum energy function to obtain an oscillation energy spectrum, carrying out main frequency energy track extraction, and introducing a frequency-power cross analysis mechanism to realize accurate identification of an oscillation source device; constructing a source-network coupled transfer function, performing stability margin calculation, and judging the stable state of the coupled system; and based on the index vector and the stability margin, carrying out oscillation risk grade division, and combining a source positioning result to generate an oscillation redisk map. According to the invention, panoramic recovery and risk quantitative evaluation of the broadband oscillation problem of the new energy field station can be realized.

The invention relates to the technical field of bolt length detection data processing, in particular to a bolt length detection system, which is characterized in that a three-dimensional data acquisition module generates a high-density point cloud and extracts a thread curvature extreme point, and a dynamic model matching module screens an optimal lead angle parameter based on a Hausdorff distance; and constructing an axial expansion model carrying phase offset gradient features. The projection mapping correction module adopts a genetic algorithm to optimize a compensation coefficient matrix, and generates a dynamic weight correction parameter to suppress geometric distortion; and the phase error correction module combines Fourier spectrum decomposition and an exponential decay weight coefficient to construct a frequency domain transfer function to eliminate an axial accumulative error. According to the method, the problems of projection distortion and phase deviation caused by the lead angle are effectively solved through geometric-phase double-domain correction, dynamic parameter iteration and an error collaborative suppression mechanism, and the spatial positioning precision of the feature points at the tail end of the thread is improved.

The invention discloses a federal space-time attention adaptive graph learning method and system, and the method comprises the steps: constructing a traffic prediction problem, constructing a space-time attention enhancement dynamic graph convolutional network model composed of a feature enhancement layer, a dynamic graph convolutional recursive network, a multi-head time attention module, a graph attention module and a space-time attention fusion module according to the traffic prediction problem; placing a traffic prediction problem in a federated learning scene, and setting privacy constraints of the model; on the basis of privacy constraints, an activation decomposition strategy is implemented on the model, and the activation decomposition strategy is that a transfer function is applied to a dynamic graph convolutional recursive network in the model; and performing traffic prediction on the traffic data acquired by the sensor by using the model which implements the activation decomposition strategy in a federated learning scene. According to the method, the problems of privacy leakage risk, high communication cost, limited model flexibility and the like in a traditional federal space-time attention adaptive graph learning framework are solved.

The invention discloses a transformer noise suppression method, system, equipment and medium, and the method comprises the steps: collecting the winding temperature, iron core temperature, cooling system working condition, load current and other operation parameters of a transformer in real time, constructing a multi-physical field coupling model covering electromagnetic, thermal and mechanical characteristics, and providing basic data for noise analysis; based on a heat conduction equation and a vibration acoustics theory, a mapping relation between a heat dissipation state and a transformer noise source is established, and dynamic influences of heat dissipation on noise amplitude and frequency are quantified; through combination of finite element simulation and a thermal network model, winding / iron core deformation caused by temperature change is analyzed, then a modulation rule of deformation on noise radiation characteristics is derived, and a heat dissipation state-physical deformation-noise characteristic transfer function is constructed; and based on the transfer function, dynamically adjusting operation parameters of the transformer by adopting a model predictive control and adaptive filtering technology, and minimizing noise output on the premise of ensuring heat dissipation efficiency.

The invention relates to the technical field of control regulation, in particular to a sludge drying treatment process control system based on coating backmixing, which is characterized in that a corrosion-resistant micro fiber grating sensor array is deployed to capture material deformation stress data in real time, and dynamic viscosity parameters are output through a transfer function; the temperature gradient monitoring module reconstructs space thermal field distribution; and the flow synchronization module generates a dynamic material balance report. And the plastic risk analysis module fuses multi-source data. A multi-agent decision module analyzes the risk signal, and a Nash equilibrium arbiter dynamically allocates weights to generate a Pareto optimal instruction set; and the equipment collaboration module executes distributed voting to verify the feasibility of the instruction. And a pulse neural network chip of the safety interlocking module implements triple modulation scale removal control. According to the method, a closed-loop optimization chain of perception, analysis, decision and execution is constructed, self-adaptive accurate regulation and control of the backmixing proportion are realized, and the drying efficiency and the operation stability are improved.

The invention provides an ocean vortex region one-dimensional wave spectrum inversion method based on a synthetic aperture radar, and the method comprises the steps: recognizing an ocean vortex through HY-2 fusion data, collecting a Sentinel-1 dual-polarized SAR image covering a vortex region, and obtaining WAVEWATCH-III wave mode data; a hydrodynamic modulation transfer function is improved, and a vortex shear flow influence factor is introduced; an XGBoost machine learning model is adopted, and an ocean vortex region SAR one-dimensional sea wave spectrum inversion algorithm is established; and verifying the accuracy of the SAR one-dimensional sea wave spectrum inversion algorithm. According to the method, the precision limitation of traditional wave theory inversion in a vortex region is broken through, and the one-dimensional wave spectrum inversion precision is improved.

A logarithmic amplifier system is disclosed. The system includes first and second amplifiers respectively having first and second gains; a first multiplier having an input connected to an output of the first amplifier, and being configured to output a first multiplied signal based on an output signal of the first amplifier and based on a received first multiplication factor equal to a value K; a second multiplier having an input connected to an output of the second amplifier, and being configured to output a second multiplied signal based on an output signal of the second amplifier and based on a received second multiplication factor equal to 1 minus the value K; a transition shaping circuit configured to change the value K from 0 to 1 with a filtered transfer function; and a summing circuit having inputs coupled to outputs of the first multiplier and the second multiplier.

The invention relates to the technical field of pulse electric field measurement, and discloses a time drift compensation method of a pulse electric field measurement system based on model parameterization. According to the method, a parameterized model is constructed in simulation software, and the parameterized model is additionally provided with two servo zeroing compensation circuits on the basis of an original measurement system, and the two servo zeroing compensation circuits are connected to the output ends of two in-phase operational amplification circuits respectively to form a negative feedback loop used for dynamically suppressing low-frequency baseline drift; acquiring electric field time domain waveform data of the output end of the third in-phase operational amplifier circuit; calculating a transfer function of a pulsed electric field measurement system in the parameterized model, converting the transfer function from a frequency domain state to a time domain state through inverse Fourier transform, and then performing deconvolution on the transfer function of the time domain state and electric field time domain waveform data to obtain real electric field intensity; according to the invention, time drift caused by operational amplifier input imbalance, power supply fluctuation and temperature change is automatically compensated in real time, and the stability and precision of system measurement are improved.

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 provides a robust optimization method and device for a low-frequency sound absorption metamaterial, and relates to the technical field of punching, and the method comprises the steps: obtaining a response function of a target metamaterial through employing a linear one-dimensional rheological model; determining a target coupling region by using an imaginary part of a transfer function zero point corresponding to the response function or a size relationship between inherent loss and radiation loss as a coupling criterion, and determining a closed coupling region where a preset parameter point is located as an initial robust region; the target coupling region comprises a closed coupling region; the preset parameter point meets the one-dimensional frequency domain response of the target metamaterial; and determining the size of the initial robust region by using the Lexberg measure of the Euclidean space, and optimizing the robust region by maximizing the Lexberg measure of the initial robust region in the Euclidean space to obtain a target robust region. According to the method, the maximum robust region in the parameter space is found through maximum measurement, so that the response characteristics of the viscoelastic damping material under the actual working condition can be accurately described.

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 relates to a power decoupling control method, device and equipment for a network construction type converter, and the method comprises the steps: introducing virtual impedance into a topological structure of the network construction type converter, and constructing a target small signal model; determining a dynamic gain matrix based on the transfer function of the target small signal model, and obtaining an RGA number according to the dynamic gain matrix; the RGA number is used for representing coupling characteristics of active power and reactive power of the system; determining a virtual value of virtual impedance based on the acquired power grid data by taking the RGA number as a constraint condition; based on the virtual value of the virtual impedance, determining the virtual voltage of the network type converter after the virtual impedance is introduced; according to the virtual voltage, obtaining virtual active power and virtual reactive power of the network-forming converter; the virtual active power and the virtual reactive power have no coupling relation. According to the invention, power decoupling of the new energy power system is realized based on the dynamic gain matrix, and further development of new energy power is promoted.

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 provides a method and system for diagnosing high-frequency magnetic disturbance in a quasi-ring symmetrical star simulator, and relates to the technical field of star simulators, and the method comprises the steps: designing the three-dimensional size of a magnetic probe body in combination with a physical research target and a vacuum chamber space limiting condition, and preparing a magnetic probe entity adaptive to an experimental environment; designing a magnetic probe array space layout according to the triangular magnetic configuration characteristics of the CFQS star simulator to obtain a positioned magnetic probe array; a positioned magnetic probe array is utilized to construct a signal transmission link, and a calibration qualification system is formed; generating a multi-channel time domain voltage signal set according to a calibration qualified system; and performing frequency response correction on the multi-channel time domain voltage signal set in combination with a transfer function database, analyzing a disturbance mode structure and a propagation direction through time-frequency spectrum analysis and array phase difference, and finally outputting three-dimensional magnetic disturbance evolution characteristics. The three-dimensional high-frequency magnetic disturbance measuring device has the beneficial effects that the three-dimensional high-frequency magnetic disturbance measuring capability is realized, multi-channel high-fidelity signal acquisition can be realized, and the experimental data quality and the physical analysis capability are improved.

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 discloses an order-lifting sliding mode robust control method for an active-passive vibration isolation system, and belongs to the technical field of vibration isolation system control, and the method comprises the steps: introducing a feed-forward control path, predicting the vibration frequency and amplitude at a future moment based on the historical state information of a controlled system, building an overall vibration isolation target model based on the prediction, and carrying out the control of the overall vibration isolation target model. Resolving a target transfer function of an active execution mechanism through kinetic analysis of the active-passive vibration isolation system, so as to calculate a feedforward control signal; the method comprises the following steps: modeling an active-passive vibration isolation system, constructing a nonsingular terminal sliding mode surface, collecting system state error information, and generating a feedback control signal of an actual controlled system through integral controller design; a feedforward control signal and a feedback control signal are reasonably coupled and superposed to serve as control input of a controlled system. According to the order-lifting sliding mode robust control method for the active-passive vibration isolation system provided by the invention, the anti-interference capability and the stability of the active-passive vibration isolation system 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 present invention discloses a method and system for online calibration of the control loop phase error of a hemispherical resonant gyroscope. The method comprises the following steps: constructing a drive modal transfer function for the hemispherical resonant gyroscope and plotting an amplitude-frequency characteristic curve and a phase-frequency characteristic curve based on the drive modal transfer function; performing frequency domain analysis on the drive modal transfer function of the hemispherical resonant gyroscope based on the amplitude-frequency characteristic curve and the phase-frequency characteristic curve to obtain analysis results; and online calibrating phase error parameters based on the analysis results to compensate for the control loop phase error. The method is simple to operate and requires no external instrumentation. The hemispherical resonant gyroscope only requires normal operation; the remaining calculations are performed by a program. Furthermore, the method is adaptable, as component inconsistencies do not affect the testing process. Therefore, the method is suitable for measuring the phase errors of drive and detection signals in closed-loop control gyroscopes.

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 relates to the technical field of civil engineering, and discloses a roadbed filling quality parameter optimization analysis system, which comprises a full-period data acquisition module used for acquiring vibration time sequence signals and equipment operation spatio-temporal data of a road roller in the operation process in real time; the working condition self-identification and model self-calibration module is used for controlling the road roller to send out a diagnostic excitation signal before the compaction operation or under a specific working condition; the soil body state real-time estimation module is based on the self-adaptive configured physical inversion model in the conventional compaction operation; the forward prediction module is based on a state transition function of the self-adaptive configuration; the multi-target constraint control decision module is based on the prediction result. According to the technical scheme, a diagnostic excitation signal is adopted to actively detect a filling material, the working condition characteristics of the filling material are automatically recognized, and then a physical model is adaptively configured, so that the technical effect of tailoring type modeling for specific soil quality is achieved, and the defects that the model is poor in universality and the calculation precision is low when the soil quality changes are overcome.

This application discloses a conformal coating detection method, apparatus, electronic device, storage medium, and product, relating to the field of nondestructive testing technology. The disclosed conformal coating detection method includes: obtaining a terahertz reflection signal from a chip under test and generating a time-domain spectrum of the terahertz reflection signal; converting the time-domain spectrum into a frequency-domain spectrum, and constructing an initial transfer function based on the frequency-domain spectrum and a preset reference frequency-domain spectrum, wherein the initial transfer function is the ratio of the frequency-domain spectrum to the reference frequency-domain spectrum; performing a frequency-domain reconstruction operation on the transfer function using a preset autoregressive model to obtain an optimized transfer function; and calculating the characteristics of the conformal coating of the chip under test based on the optimized transfer function. This application can ensure high-precision measurement of conformal coatings.

Described are concepts, systems, system architectures, circuits, methods, and techniques directed toward power management and control. In particular, described are concepts, systems, system architectures, circuits, methods, and techniques for implementing power converters that may not have a right-hand pole zero in their linearized, averaged control-to-output transfer function, but that may still have buck and boost functionality.