130 results about "Frequency curve" patented technology

The invention relates to the technical field of audio signal processing, and discloses a room sound correction method, device and equipment for audio equipment and a storage medium, which are used for improving the accuracy and correction effect of correction parameters and effectively improving the acoustic effect of the audio equipment in a room. The room sound correction method of the audio equipment comprises the following steps: acquiring response data of a room to a multi-band preset test signal, and extracting room acoustic data by adopting a time-frequency conjoint analysis method, the room acoustic data comprising frequency attenuation, reflection paths, phase shifts and reverberation time information of different bands; based on the room acoustic data, performing compensation processing by using preset microphone calibration data to obtain a calibrated frequency response curve; performing fitting calculation on a preset ideal frequency curve and the calibrated frequency response curve according to an optimization algorithm to obtain specific correction parameters of the room; and correspondingly adjusting the output of the audio equipment according to the correction parameter.

The invention discloses a generator non-inductive access grid-connected method, device and equipment, and provides a reliable data basis for subsequent operation by collecting a power grid state and generator operation monitoring parameters in real time. Power grid frequency is calculated at multiple time points, and a real-time frequency curve is constructed and used for analyzing stability, predicting changes, comparing generator current output frequencies to identify frequency differences and evaluating coordination. Frequency synchronization is realized by using minimum difference time point detection, the time point is marked to optimize frequency control, and grid-connected stability and safety are guaranteed by combining dynamic frequency adjustment and synchronous frequency error estimation. In the aspect of power control, power fluctuation is reduced through transient power suppression optimization, and the adaptability of the generator is enhanced through dynamic feed-forward compensation control. In addition, manual intervention is reduced through intelligent non-inductive grid-connected optimization, an intelligent grid-connected engine is constructed, seamless butt joint of a generator and a power grid is achieved, grid-connected efficiency and safety are comprehensively improved, and system complexity and risks are reduced.

Disclosed in the present invention is a deep learning-based power distribution network load prediction method, comprising: acquiring regional load data and renewable energy power generation data to form a data set, and preprocessing the data set to obtain a first data set; using a convolutional neural network to extract a time series feature in the first data set, and converting the time series feature into a data form of a deep learning model by means of an embedding layer to obtain one-dimensional time series data; performing fast Fourier transform on the one-dimensional time series data to obtain a frequency curve, extracting amplitude values on the frequency curve to calculate corresponding periods, and selecting the corresponding periods to slice the one-dimensional time series data and form same into two-dimensional matrixes; using a two-dimensional convolutional network to perform feature extraction, reshaping the two-dimensional matrixes that have undergone feature extraction into one-dimensional arrays, and performing adaptive fusion on the one-dimensional arrays to obtain a first time series feature; and inputting the first time series feature into a fully connected layer for weight calculation and linear transformation to obtain a power distribution network load prediction result, thereby improving the stability and reliability of electric power supply.

The invention discloses an arbitrary digital signal synthesis method and system. The method comprises the following steps: analyzing a target parameter of a digital signal to be synthesized; generating a first multi-path baseband waveform by using a digital direct frequency synthesizer according to a modulation rate parameter in the target parameters, and reading pre-stored noise data to generate a second multi-path baseband waveform; selecting a plurality of appointed baseband waveforms, and modulating the plurality of baseband waveforms by using carrier frequency and bandwidth parameters in target parameters to obtain a plurality of instantaneous frequency curves; and integrating the multiple instantaneous frequency curves to obtain a phase stepping curve of each path, selecting a phase modulation curve according to a phase modulation type in the target parameters, and performing digital direct frequency synthesis on the phase stepping curve and the phase modulation curve of each path to generate multiple parallel digital synthesis signals. According to the invention, the synthesis process of the digital signals of different modulation types is uniformly decomposed, so that the coupling degree of the module and the complexity of the system are greatly reduced, and meanwhile, the resource consumption is reduced.

The invention relates to the technical field of cell sorting, in particular to a sorting control system and a sorting method of a flow cytometer, the system comprises a data acquisition unit and a control unit, and the method comprises the following steps: acquiring a plurality of breakpoint images of liquid drops to determine whether the forming process of the liquid drops is qualified or not according to the pixel variance of breakpoints; determining whether the oscillation stability is qualified or not according to the oscillation area of the oscillation curve of the piezoelectric ceramic based on the unqualified droplet forming process so as to determine whether the sheath fluid flow velocity is obtained or not; determining a matching degree based on the flow velocity curve of the sheath fluid flow velocity and the frequency curve of the liquid drop to increase the sheath fluid pressure according to the fluctuation intensity of the fluorescence signal; determining a target liquid drop according to a fluorescence detection result, determining liquid drop delay according to the target liquid drop, and determining whether the target liquid drop can fall into the collecting pipe or not according to the initial deviation angle of the target liquid drop, so as to adjust the inter-plate voltage of the deflection plate. The sorting precision is improved.

The invention provides a dark crack detection method of an ultrahigh-strength steel plate stamping part for a new energy automobile, and relates to the technical field of stamping part detection, and the dark crack detection method comprises the following steps: obtaining a detection area and a reference area of a to-be-detected stamping part; injecting a group of same multi-frequency alternating-current excitation signals into the detection area and the reference area of the to-be-detected stamping part at the same time, and synchronously acquiring a first electrical response signal of the detection area under the multi-frequency alternating-current excitation signals and a second electrical response signal of the reference area under the multi-frequency alternating-current excitation signals; based on the first electrical response signal and the second electrical response signal, calculating a conductivity difference value of the detection area and the reference area at the same frequency point, and obtaining a conductivity difference value-frequency curve comprising a plurality of frequency points; and based on the conductivity difference-frequency curve, whether dark cracks exist in the detection area is judged. According to the detection method, the defect degree can be quantitatively evaluated, and the strict requirement of the new energy automobile industry for quality consistency is met.

The invention belongs to the technical field of rotating machinery signal processing, and discloses a multi-shafting rotating machinery rotating speed estimation method based on a displacement vibration signal, and the method comprises the steps: collecting the displacement vibration signal, and carrying out the short-time Fourier transform to obtain a time-frequency distribution matrix; screening out a safety harmonic set of each shafting based on the estimated rotating speed range; calculating a definition evaluation value of each safety harmonic wave and selecting an optimal harmonic wave as a target tracking harmonic wave; constructing a cost function fusing amplitude and frequency abrupt change penalty, and performing ridge line tracking in the local time-frequency matrix after noise reduction to obtain a preliminary estimation time-frequency curve; and constructing a demodulation phase function based on the curve, performing generalized demodulation and narrow-band filtering on an original signal, extracting a pure harmonic component, and finally reconstructing a final rotating speed curve of a corresponding shaft system through instantaneous phase differential. According to the method, high-precision and anti-interference decoupling and estimation of the rotating speed of each shafting under a strong interference background are realized.

The invention relates to an interconnection line parameter extraction method based on a layered medium Green function improved moment method and a program product, and the method comprises the following steps: setting a sweep frequency parameter and a layered medium structure parameter, constructing a layered medium Green function, and carrying out the calculation to obtain an approximate solution of the layered medium Green function; establishing an electric field integral equation under the layered medium, and performing discretization processing to obtain a corresponding matrix equation; and performing iterative solution on the matrix equation to obtain the overall current distribution of the model, calculating the current value and impedance / admittance value of a port, performing electromagnetic calculation in a frequency sweep mode to obtain different port parameter values, and finally obtaining a parameter-frequency curve to complete the extraction of the port parameters. Compared with the prior art, the stratified medium Green function is fused into the frame of the enhanced electric field integral equation, electromagnetic simulation calculation of the full wave band from 0 frequency to 20 GHz can be achieved, and the method has the advantage of being high in calculation and solving efficiency.

The invention discloses a narrow-band-based smooth precession cone micro-motion extraction and scattering point identification method, and the method comprises the steps: building an equivalent scattering point model of a smooth precession cone target based on a narrow-band radar, estimating the number of echo signals, carrying out the order determination of a sliding window Pole Root-MUSIC algorithm, setting the window length, and carrying out the recognition of the scattering points of the smooth precession cone target. Estimating a micro-Doppler time-frequency curve of a target scattering point through a sliding window, carrying out IRadon transformation, positioning and identifying an energy gathering condition, distinguishing the micro-Doppler time-frequency curve of a cone top scattering point from the micro-Doppler time-frequency curve of a cone bottom scattering point, and realizing scattering point identification; and then Radon transformation is respectively carried out to obtain two corresponding trend lines, and the micro Doppler time-frequency curves of the target scattering points are respectively correlated and smoothed according to the trend lines to realize micro-motion feature extraction of the target. Under the condition of narrow-band radar observation, the micro-Doppler time-frequency curve can be directly and quickly obtained, and correlation is completed.

The invention discloses a reference crop evapotranspiration estimation method based on user data information, and the method comprises the following steps: S1, constructing a national database, and calculating the daily-scale reference crop evapotranspiration; s2, a user uploads meteorological data and geographic information, and necessary information of more than two users needs to be provided according to a data template; s3, calculating a cumulative frequency curve of each meteorological factor; s4, performing quantile sequence comparison, selecting 15-20 sites with the highest distribution matching degree, and obtaining a simplified data set; s5, the Euclidean distance is calculated, and a data group with the minimum distance is selected to enter an alternative group; and S6, constructing a reference crop evapotranspiration model to carry out evapotranspiration estimation. According to the method, the optimal machine learning modeling reference crop evapotranspiration method is customized for the user by using the meteorological data owned by the user, the calculation error is lower, the data information owned by the user is fully mined, and the customized and refined reference crop evapotranspiration model is really realized.

The invention discloses a water engineering scheduling runoff intelligent simulation method, which comprises the following steps: edge distribution function fitting: calculating a mean value, a discrete coefficient and a skewness coefficient by applying a moment method, and constructing a daily runoff frequency curve by adopting a P-III type curve; constructing a wisdom knowledge set: establishing the wisdom knowledge set of parameters in a mixed Copula set by using a time sequence model, and calibrating the parameters of the wisdom knowledge set by using a cooperative search algorithm and taking the minimum akaike information criterion of theoretical distribution and empirical distribution as a target; and daily runoff simulation: establishing a mixed condition Copula set based on a Bayesian rule, and generating long-sequence daily runoff by adopting Latin hypercube sampling. According to the method, the daily runoff simulation difficulty of the mixed Copula is reduced, the number of parameters is reduced, the fitting precision of the mixed Copula is improved, the construction speed of the mixed Copula set is increased, and a valuable technical tool is provided for drainage basin management.

The application discloses a stability analysis method of a photovoltaic energy storage micro-grid in an islanding scenario based on system admittance characteristics, and belongs to the technical field of distributed new energy grid-connected power generation. The method comprises the following steps: determining the main circuit filter type and control structure of a three-phase inverter of a power generation unit; establishing a second-order admittance model of the inverter based on a harmonic linearization method; decoupling the second-order admittance model to obtain linear admittance models under positive and negative sequences; establishing the voltage-current relationship at a system point of common coupling based on a node voltage method according to the topological structure of the micro-grid, and obtaining a system admittance matrix; drawing the amplitude-frequency curve and the phase-frequency curve of key items in the system admittance matrix, determining the key characteristic frequency corresponding to the minimum point of the amplitude-frequency curve, and determining the stability of the system according to the positive and negative of the slope of the phase-frequency curve at the key characteristic frequency. The method can accurately analyze the stability of the photovoltaic energy storage micro-grid in the islanding operation scenario.

The present invention proposes an isotropic material plate impact positioning method based on a wavenumber domain response function, which belongs to the field of aircraft technology and solves the problems of low positioning accuracy and robustness of existing impact positioning methods. The steps include: calculating the dispersion curve of the guided wave according to the material properties and geometric dimensions of the detected part; selecting a preset frequency range, constructing a wavenumber-angle relationship function, and combining it with the frequency curve to obtain a frequency-angle function; constructing a wavenumber domain response function, and performing Fourier transform on the wavenumber domain response function to obtain a spatial domain response distribution function; mapping the pattern presented by the spatial domain response distribution function into an electrode of a piezoelectric crystal to obtain a directional sensor with a frequency component filtered according to direction; rigidly connecting several directional sensors to the detected part, outputting the 1dB bandwidth of the response signal, and constructing a fan-shaped area for each directional sensor, and using the intersection area of ​​all fan-shaped areas as the positioning result of the impact point.

The invention relates to a method, a device and equipment for determining the harmonic influence range of a vibroseis and a medium, and relates to the technical field of seismic acquisition data analysis, and the method comprises the steps: obtaining a scanning signal of the vibroseis, and carrying out the calculation to obtain the instantaneous frequency of the scanning signal; according to the instantaneous frequency, harmonic instantaneous frequency curves corresponding to harmonic signals of different sliding times and different orders are generated; generating a scanning signal instantaneous frequency curve corresponding to different dislocation time according to the instantaneous frequency; and determining the harmonic influence range of the vibroseis according to the intersection relationship between the harmonic instantaneous frequency curve and the scanning signal instantaneous frequency curve. According to the scheme, the harmonic influence range can be conveniently and efficiently determined, and the method is suitable for the situation that a nonlinear scanning signal or a scanning signal cannot be accurately expressed through an analytical expression.

The invention discloses a power system region division method considering frequency space-time distribution characteristics. The method comprises the following steps: modeling a device side and a network side of the new energy power system respectively to obtain a system closed-loop frequency response model, and decomposing frequency response into a plurality of components based on spectral decomposition of a system return difference matrix; analyzing response characteristics such as a frequency lowest point and an average change rate of each frequency component to quantify a frequency space-time distribution characteristic; the method comprises the following steps: measuring the frequency of a PMU configuration node through simulation when disturbance occurs at different positions of a system, and constructing a similarity matrix and a Laplacian matrix by using an actually measured frequency response curve after modal decomposition and an improved spectral clustering algorithm to extract a feature vector of modal frequency; and finally, the frequency curves with high similarity are gathered together by adopting a DBSCAN clustering algorithm to realize partitioning of the system. According to the method, the real-time partitioning result of the system can be quickly and accurately given, and the consistency of regional frequency response under various disturbances is ensured.

The invention relates to a target and outdoor environment electromagnetic scattering coupling suppression method, which relates to the field of testing, and comprises the following steps: carrying out a dot frequency RCS test on a target, if the target is abnormal and is caused by ground reflection, determining a strong scattering point distribution angular domain according to a dot frequency curve, and obtaining a one-dimensional distance image; performing positioning analysis on strong scattering points in the one-dimensional range profile, confirming abnormal strong scattering points, dividing the abnormal strong scattering points into two types, reflecting the ground back to a target and then scattering to an oblique incidence type strong scattering source in an antenna, and fitting a circular curve; directly reflecting the ground to a strong scattering source in the antenna, fitting an elliptic curve, and calculating the position of a strong scattering point; the method has the advantages that the ground reflection points are determined through one-dimensional high-resolution testing and ground reflection point distribution fitting, and therefore the target testing precision is guaranteed through the reflection point suppression technology.

The application discloses a flexible DC transmission line intra-zone and extra-zone fault discrimination method based on S transform, a method of waveform continuation is used to cover the subsequent wave with the wave tail of the first wave, the influence of the subsequent wave head on the frequency characteristics is reduced, the S transform is used to make the modulus time frequency matrix of the continued waveform, the row vectors of the modulus time frequency matrix are integrated, the corresponding amplitude-frequency curve is obtained, the energy operator is used to weight the amplitude-frequency curve to improve the proportion of high-frequency components, the energy accumulation of different frequency bands is constructed, the ratio of the high-frequency band energy accumulation and the total frequency band energy accumulation is taken as the intra-zone and extra-zone fault recognition criterion, when the ratio is greater than the threshold value, the intra-zone fault is determined, otherwise, the extra-zone fault is determined. The method meets the rapidity requirement of the flexible DC transmission line protection, has high sensitivity, and has important reference value for the development of the flexible DC transmission protection.

This application belongs to the field of rotating machinery signal processing technology, and discloses a method for estimating the rotational speed of multi-axis rotating machinery based on displacement vibration signals. The method involves acquiring displacement vibration signals and performing short-time Fourier transform to obtain a time-frequency distribution matrix; selecting a safe harmonic set for each axis system based on the estimated rotational speed range; calculating the sharpness evaluation value of each safe harmonic and selecting the optimal harmonic as the target tracking harmonic; constructing a cost function that fuses amplitude and frequency mutation penalties; performing ridge tracking in the denoised local time-frequency matrix to obtain a preliminary estimated time-frequency curve; constructing a demodulation phase function based on this curve; performing generalized demodulation and narrowband filtering on the original signal to extract clean harmonic components; and finally reconstructing the final rotational speed curve of the corresponding axis system through instantaneous phase differentiation. This method achieves high-precision, anti-interference decoupling and estimation of the rotational speed of each axis system under strong interference conditions.

An abnormality detection system (7) for a hydraulic rotary machine (1) according to an embodiment includes: a pressure gauge (71) that measures pressure relating to the hydraulic rotary machine (1); and a processing circuit (73). The processing circuit (73) performs frequency analysis of a pressure waveform, which is the measurement result of the pressure gauge (71), a plurality of times to create a frequency spectrum, records the pressure amplitude of a specific order component that is an integral multiple of the rotation frequency in the frequency spectrum, calculates the occurrence frequency of each value of the recorded pressure amplitude, and determines the presence or absence of an abnormality in the hydraulic rotary machine (1) on the basis of a temporal change in a frequency curve on a graph relating to the pressure amplitude and the occurrence frequency.

The invention relates to a consistency evaluation method for dynamic performance indexes of a multi-dimensional force sensor. Time-frequency domain dynamic performance indexes of the multi-dimensional force sensor are calculated on the basis of a frequency response function of the multi-dimensional force sensor. In the aspect of frequency domain performance indexes, a measurement frequency band and a response frequency band are analyzed and calculated by adopting a threshold comparison method according to an amplitude-frequency curve of each main channel of a sensor frequency response function, and modal parameters in the response frequency band are analyzed and calculated by adopting a peak search method and a step-by-step integral iteration method; in the aspect of time domain performance indexes, an inverse Fourier transform method is adopted to convert a frequency response function of each main channel and an inter-dimension coupling channel of the sensor into a time domain unit impact response, and the time domain unit impact response is directly subjected to linear convolution with a constructed unit step signal to reconstruct a unit step response of each channel of the sensor; step response rise time and adjustment time of each main channel are analyzed and calculated by adopting a threshold comparison method, and step response overshoot of the main channel and a dimensional dynamic coupling error of each coupling channel are analyzed and calculated by adopting a peak search and range conversion method; finally, the problem that the dynamic performance index evaluation of the existing multi-dimensional force sensor is incomplete under the finite dynamic calibration test condition is effectively solved.

The invention discloses a power grid frequency prediction method based on LSTM and time feature attention. The power grid frequency prediction method comprises the following steps: step 1, collecting multi-dimensional time sequence feature data of a power system before and after disturbance; 2, preprocessing the multi-dimensional time sequence feature data, and extracting high-dimensional time sequence features in the feature data obtained in the step 1 by using a time convolutional neural network T-CNN; 3, inputting the high-dimensional time sequence features extracted by the time convolutional neural network T-CNN into the time-feature attention module to obtain a focusing key feature and a weighted feature sequence of a key moment; 4, taking the weighted feature sequence obtained in the step 3 as input, mining a time sequence dependency relationship through a frequency prediction model of a long short-term memory (LSTM) network, and outputting a prediction curve of the inertia center frequency of the power system; and step 5, according to the predicted frequency curve, calculating a frequency lowest point deviation and a frequency change rate, and according to a preset frequency response danger level standard, outputting a frequency safety evaluation result of the power system.

The invention relates to the technical field of grid-connected inverters, in particular to a method for correcting positive virtual impedance of an LCL type inverter in a Nyquist frequency, which comprises the following steps of: accurately determining parameters of capacitor voltage feedback branches in an LCL filter, establishing an equivalent formula of virtual impedance, and adjusting parameters in primary differential feedback so as to correct the positive virtual impedance of the LCL type inverter in the Nyquist frequency. The method successfully widens the positive damping frequency range, optimizes the impedance characteristics of the inverter through the virtual impedance of the parallel proportional term, the primary differential term and the secondary differential term and the calculation of the total parallel impedance formula, and obtains the impedance characteristics of the inverter by drawing various impedance-frequency curves. Comprising a virtual impedance-frequency curve, a parallel impedance-frequency curve and a primary differential impedance-frequency curve, and an intuitive impedance characteristic analysis tool is provided for a system designer and an engineer; and finally, by drawing a total impedance-frequency curve and verifying whether the system maintains the positive resistance characteristic in the Nyquist frequency range, the stability of the system is ensured.

The invention provides a synchronous generator inertia time constant evaluation method based on data driving. The method comprises the following steps: acquiring nominal frequency, active power and frequency measurement data of a synchronous generator grid connection point; obtaining a frequency deviation value according to the nominal frequency and the frequency, and obtaining an evaluation moment when the frequency deviation value is equal to a frequency control dead zone; constructing an active average value expression based on the evaluation time so as to construct an active variation expression, and further constructing a frequency expression so as to obtain an evaluation function; reversely deducing a theoretical frequency curve according to the frequency expression so as to carry out time mark correction on the measurement data; and based on the average window integral, calculating an evaluation function according to the measurement data after the time mark correction to obtain an inertia time constant evaluation value. According to the evaluation method provided by the invention, on the basis of performing time mark correction on the measured data, the inertia time constant of the synchronous generator is reasonably and accurately evaluated by using the disturbed data, and the evaluation method has guiding significance for evaluating the real frequency supporting capability of a new energy station.

The application relates to a wire harness radiation simulation method and system based on the impedance frequency response characteristics of a magnetic ring, and the method comprises the following steps: selecting measuring points around an electromagnetic simulation coupling model of a magnetic ring, a wire harness and a metal structure around the wire harness; inputting an excitation condition data and a magnetic ring impedance characteristic notebook document to perform simulation analysis, obtaining a first electric field radiation value of the measuring points changing with frequency curve diagram, the above process does not need to set the magnetic ring in the actual vehicle for verification, the impedance frequency response characteristic curve of the magnetic ring is converted into an impedance characteristic notebook document, so that the electric field radiation value of the measuring points under different frequencies after the magnetic ring of the specification type is set is obtained; in addition, the specification and the installation position of the magnetic ring can be modified, and then simulation is performed again, so that the specification and the installation position of the magnetic ring meeting the requirements are quickly determined, and the test time is reduced; the simulation analysis result gives a reference for modifying and adjusting the specification and the installation position, avoids randomness of modification, and provides certain guidance for rectification of electromagnetic radiation exceeding of a direct current fast charging wire harness.

This invention relates to the field of aquatic environmental ecological risk assessment technology, and specifically discloses a method for assessing the risk of anthropogenic heavy metal accumulation based on zonal background and baseline values. The method includes the following steps: Step 1, Zoning and sample collection of the study area: Zonal sampling and multi-element determination: Obtaining representative sediments and determining the content of the target heavy metals; Step 2, Calculation of zonal background values: Automatically identifying the curvature abrupt change points of the cumulative frequency curves of each zone using the curvature extreme value method, and using these as the theoretical upper limit of the background element concentration; Step 3, Calculation of zonal baseline values, representing the natural background content of the area that is unaffected or minimally affected by human interference. This method for assessing the risk of anthropogenic heavy metal accumulation based on zonal background and baseline values ​​fully considers the spatial heterogeneity within lakes by constructing background and baseline values ​​through zoning, avoiding errors caused by using a single background value, and making the calculation of anthropogenic contributions closer to the actual situation.

The invention relates to the technical field of audio processing based on multi-order frequency adjustment, and discloses an audio processing method, system and device based on multi-order frequency adjustment and a medium, and the method comprises the steps: obtaining an initial audio; frequency division is carried out on the initial audio frequency to obtain initial frequency band data, and the initial frequency band data comprise low-frequency data, intermediate-frequency data and high-frequency data; performing denoising processing on the initial frequency band data to obtain target frequency band data; performing audio synthesis on the target frequency band data to obtain a to-be-adjusted audio; and based on target cavity characteristic data of the sound production equipment, performing frequency adjustment on the to-be-adjusted audio by adopting at least two EQ adjustment modules for multi-order frequency adjustment to obtain a target audio suitable for the sound production equipment. Therefore, the man-made effect of the frequency band edge is effectively avoided, the frequency curve of the finally output audio is more continuous and smooth, and the audio better meets the hearing requirement of a user.

The invention discloses a reactive equipment action frequency limit value setting method and system based on data mining, and relates to the technical field of data mining. The method includes: acquiring and preprocessing historical operation data of a power grid; obtaining new energy day-ahead load prediction, and determining a load value through an optimal objective function method; carrying out mining analysis on the preprocessed data to obtain a compensation equipment action frequency curve; carrying out reinforcement learning on the action frequency curve by adopting a deep Q network, and carrying out multi-scene training in combination with a Monte Carlo method; and obtaining an optimal action frequency curve according to a convergence condition. The new energy day-ahead load prediction is obtained, the load value is determined by adopting the optimal objective function method, load prediction is more accurate, mining analysis is performed on the preprocessed data, reinforcement learning is performed by adopting the deep Q network, multi-scene training is performed in combination with the Monte Carlo method, and the load prediction accuracy is improved. And the optimization effect of the action times of the compensation equipment is improved.

The present invention provides a passive ranging method and system for a bubble pulse sound source based on time-domain warping transformation, including: performing complex cepstrum analysis on a pulse signal to obtain a complex cepstrum signal; searching for peak points of the complex cepstrum signal, taking multiple points before and after the peak points for binomial fitting, and interpolating at the peak point according to the fitting result; returning the interpolated complex cepstrum signal to the time-domain signal; performing time-domain warping transformation on the time-domain signal to obtain (W hy )(t), and performing time-frequency analysis on (W hy )(t) to obtain (W hy )(f); extracting each order of single-frequency mode in (W hy )(f) through the Hough transform, and obtaining each mode time-frequency curve for each single-frequency mode through an inverse transformation function; comparing each mode time-frequency curve with the time-frequency analysis result of the time-domain signal; calculating to obtain each mode dispersion curve; substituting each mode time-frequency curve and each mode dispersion curve into a cost function to search for the minimum value. The present invention can achieve passive ranging of a bubble pulse sound source.

An unmanned aerial vehicle time-frequency image reconstruction method based on deep learning belongs to the technical field of radar signal processing and image reconstruction, solves the technical problem that unmanned aerial vehicle time-frequency images are difficult to identify and analyze under the condition of low signal-to-noise ratio, and comprises the following steps: S1, performing short-time Fourier transform on echo signals, and establishing an unmanned aerial vehicle radar echo model STFT; s2, designing a SelfNet model based on a convolutional neural network, and reconstructing an unmanned aerial vehicle time-frequency curve graph; s3, according to an unmanned aerial vehicle radar echo model STFT and a time-frequency curve output image, establishing an unmanned aerial vehicle time-frequency image data set, and performing training by using a SelfNet model; and S4, reconstructing the time-frequency image data set of the unmanned aerial vehicle by using the trained SelfNet model weight. The method can be used for actually measuring data, the precision of the time-frequency image of the unmanned aerial vehicle under the low signal-to-noise ratio can be improved, and follow-up multi-class classification and micro-motion parameter estimation of the unmanned aerial vehicle are facilitated.