65 results about "Frequency curve" patented technology

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 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 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.

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.

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 provides a time-varying structure instantaneous frequency identification method based on variational synchronous compression transformation. The method comprises the following steps: acquiring a vibration response signal of a time-varying engineering structure; performing signal continuation processing on the vibration response signal; performing time-frequency transformation on the continued vibration response signal to obtain a time-frequency spectrum and a time-frequency coefficient; locking a high-energy region corresponding to a time-varying structure characteristic frequency band from the time-frequency spectrum so as to eliminate interference points caused by test noise; based on the time-frequency coefficient in the high-energy region, estimating an instantaneous frequency through a variational optimization method of introducing a regularization smoothing item, the regularization smoothing item being used for suppressing false peak interference; performing synchronous compression transformation on a time-frequency coefficient based on the instantaneous frequency estimation value to obtain a refined frequency band; and extracting an instantaneous frequency curve of the time-varying engineering structure from the refined frequency band.

The invention provides an overlapped multi-component signal instantaneous frequency estimation method, which realizes one-by-one extraction of instantaneous frequency curves in a target signal, and for any IF curve, frequency points of all moments are respectively estimated forwards and backwards one by one from an initial time frequency point and an initial direction angle thereof, so that the instantaneous frequency curve is extracted; wherein the estimation sum is based on the time frequency point sum, and the estimation sum is as follows: S1, extracting a smooth amplitude peak point under each instantaneous frequency; s2, under each instantaneous frequency, selecting a peak point with the minimum deviation as a candidate peak point; and S3, selecting the peak point with the maximum smooth amplitude from all the candidate peak points, and taking the instantaneous frequency and the direction angle corresponding to the peak point as the sum. According to the method, the IF direction is accurately screened in the overlapped time-frequency region through'multi-direction smoothing + direction continuity constraint ', error components are prevented from being tracked, and the switching problem of frequency-modulated signals can be effectively eliminated.

The invention discloses a frequency domain-time frequency domain adaptive time-varying filtering method with human-computer interaction characteristics, which comprises the following steps: manually selecting reference data points according to the energy distribution of signals in a time frequency domain, and obtaining an instantaneous frequency curve of a component to be extracted through cubic spline interpolation fitting; based on the short-time Fourier transform energy matrix and the cumulative distribution function, the instantaneous transmission band width at each moment is calculated in a self-adaptive mode; taking the instantaneous frequency as a center frequency and the instantaneous bandwidth as a transmission band boundary, constructing an elliptical digital band-pass filter bank, and forming a self-adaptive time-varying filter; performing time-frequency domain filtering decomposition on the original signal, and performing inverse short-time Fourier transform reconstruction to obtain a pure component signal; order spectrum / envelope order spectrum analysis is carried out on the components, and gear fault features are extracted. The method gives consideration to time domain and frequency domain information, achieves one-time filtering decomposition, is high in calculation efficiency, is high in anti-noise performance, and is suitable for the fault diagnosis of equipment with complex non-stationary signal features.

The application discloses a water engineering scheduling runoff intelligent simulation method, comprising: edge distribution function fitting: using the matrix method to calculate the mean, dispersion coefficient and skewness coefficient, and adopting a P-III type curve to construct a daily runoff frequency curve; wisdom knowledge set construction: using a time series model to establish wisdom knowledge sets of each parameter in a mixed Copula set, using a cooperative search algorithm, taking the minimum of the Akaike information criterion of the theoretical distribution and the empirical distribution as the target, and calibrating the wisdom knowledge set parameters; daily runoff simulation: based on the Bayesian rule, a mixed conditional Copula set is established, and Latin hypercube sampling is used to generate a long sequence of daily runoff. The method reduces the difficulty of daily runoff simulation by the mixed Copula, reduces the number of parameters, improves the fitting precision of the mixed Copula, speeds up the construction speed of the mixed Copula set, and provides a valuable technical tool for basin management.

The invention discloses a grid-connected oscillation judgment method, system and equipment of a power electronic converter and a medium, and particularly relates to the technical field of oscillation judgment, and the technical key points are as follows: constructing an amplitude-frequency curve and a phase-frequency curve by using the SISO impedance of a power grid and the SISO impedance of the power electronic converter obtained by broadband impedance measurement; in the amplitude-frequency curve, obtaining a frequency value when the SISO impedance characteristic amplitude of the power grid is equal to the SISO impedance characteristic amplitude of the power electronic converter, and obtaining a phase difference of the same frequency value in the phase-frequency curve; and combining the phase difference with a pre-constructed broadband oscillation criterion to obtain an oscillation judgment result of the converter grid-connected system. The SISO impedance characteristic of the power grid and the SISO impedance characteristic of the power electronic converter, which are obtained by broadband impedance measurement, are utilized to more conveniently and quickly judge whether the system has the risk of broadband oscillation caused by harmonic amplification of the system; meanwhile, a broadband oscillation criterion is provided, and a critical oscillation region is introduced, so that the grid-connected oscillation criterion is defined more clearly.

The invention discloses an instantaneous frequency identification method based on short-time fractional Fourier multi-transform, and the method consists of four parts: time-varying component separation, short-time fractional Fourier transform and matching multiple synchronous extrusion transform, and specifically comprises the steps: firstly, carrying out the time-varying component separation through a binary image and a connected region mark; secondly, obtaining an estimated instantaneous frequency position through bandwidth optimization short-time fractional order Fourier transform, secondly, rearranging a time-frequency coefficient by matching a synchronous extrusion operator, and finally extracting an instantaneous frequency curve by using a local modulus maximum method. The method can effectively identify the instantaneous frequency of the time-varying structure.

This invention belongs to the technical field of hydrometeorological extreme value theory, and provides an unbiased estimation method for rainfall probability distribution based on least squares fitting. Existing parameter estimation methods are numerous, each with its own specific applicable scope and advantages and disadvantages. The choice of method significantly affects the accuracy of generalized extreme value distribution parameter estimation. This invention comprehensively considers the advantages of five parameter estimation methods: Bayesian, GMLE, L-moments, MLE, and MPS. Based on least squares fitting, it determines the optimal weight coefficients of a single method, establishing an unbiased and efficient ensemble parameter estimation framework. By integrating multiple parameter estimation methods, the bias and variance of individual methods can be reduced, improving the robustness and reliability of parameter estimation, and providing a reference for accurately determining the rainfall frequency curve and design rainfall.

The application discloses a shallow sea heavy mineral sand mine resource exploration method and related equipment, and the method comprises the following steps: obtaining pre-research data of a target shallow sea area, predicting an exploration scheme based on the pre-research data, and arranging a bottom seismograph in the target shallow sea area based on the exploration scheme; collecting passive source micro-motion data by using the bottom seismograph, and extracting original data from the passive source micro-motion data based on a preset data quality standard; constructing a horizontal and vertical spectral ratio curve based on the original data, performing frequency spectrum separation on the horizontal and vertical spectral ratio curve, and obtaining a low-frequency curve of a bedrock resonance peak; constructing a palaeotopographic map through bedrock surface depth inversion based on the low-frequency curve; obtaining a regional geological model of the target shallow sea area, superimposing and analyzing the palaeotopographic map and the regional geological model, and obtaining an evaluation result of heavy sand mine resource potential. The application can effectively improve the exploration directivity and the accuracy of resource potential evaluation by identifying the change of ore-controlling landforms, and can be widely applied to the technical field of data processing.

This invention relates to the field of artificial intelligence and discloses a displacement monitoring method and related device based on artificial intelligence and multi-view vision to improve the accuracy of displacement monitoring. The method includes: performing feature fusion and feature matching on multiple tunnel feature points to obtain multiple feature point pairs, and acquiring the feature point coordinates of each feature point pair; calculating attribute parameters of a visual displacement analyzer based on the feature point coordinates of each feature point pair; performing three-dimensional mapping of the gas pipeline tunnel based on the attribute parameters and multiple detection areas to obtain initial coordinate information, and performing coordinate transformation on the initial coordinate information to obtain first coordinate information; generating second coordinate information based on a second tunnel image, and calculating displacement and vibration frequency data based on the first and second coordinate information; generating a displacement-frequency curve based on the displacement and vibration frequency data, and performing safety monitoring of the gas pipeline tunnel based on the displacement-frequency curve to obtain safety monitoring results.

The application discloses a lightning disturbance discrimination method for flexible HVDC transmission line based on instantaneous frequency characteristics, and specifically comprises the following steps: step 1, extracting voltage and current data in a time window from 1ms before protection starting to 1.0ms after protection starting, and obtaining line mode voltage forward and reverse traveling waves; step 2, performing discrete S transform on the line mode voltage reverse traveling wave obtained in step 1 to obtain a mode time-frequency matrix, and extracting an amplitude-frequency curve at a fault occurrence moment; step 3, obtaining a maximum value number Q of the instantaneous amplitude-frequency curve, if Q=1, it is lightning disturbance, and the discrimination ends; if Q>1, it is a fault, and step 4 is entered; step 4, defining a frequency of a point with the maximum amplitude in the amplitude-frequency curve as a main frequency F1, comparing the main frequency F1 with a threshold value F set , and judging a fault type according to a comparison result. The discrimination method provided by the application is simple in calculation, and can accurately judge lightning disturbance and lightning fault.

The application provides a self-adapting time-frequency supported frequency modulation signal decomposition method and system, which comprises the following steps: calculating a parameterized time-frequency transform of a signal; extracting a rough instantaneous frequency ridge curve of a sub-signal with maximum energy from a time-frequency representation of the parameterized time-frequency transform of the signal; taking the extracted instantaneous frequency curve of the sub-signal as an initial instantaneous frequency of signal decomposition; calculating an instantaneous frequency kernel function matrix of the sub-signal according to the instantaneous frequency of the sub-signal; calculating a demodulation signal of the sub-signal; calculating an initial instantaneous frequency increment of the sub-signal; calculating an optimized initial instantaneous frequency increment of the sub-signal; and updating the instantaneous frequency of the sub-signal. The application realizes the decomposition of a complex multi-component signal with strong noise, can accurately estimate the instantaneous frequency (IF) of each sub-signal and reconstruct each sub-signal, effectively reveals the change rule of the original complex signal, can be applied to the actual engineering signal processing in many fields, and has strong engineering practical value.

The embodiment of the invention discloses a ground penetrating radar signal processing method for obtaining the thickness of a black soil layer, and the method comprises the steps: carrying out the detection in a detection region through a ground penetrating radar, and obtaining an original ground penetrating radar signal of each measurement point; the method comprises the following steps of: after preprocessing an original signal, decomposing the original signal into a plurality of intrinsic mode function components by adopting a variational mode decomposition method; and based on the time-frequency distribution characteristics of each component, eliminating noise components to obtain a de-noised signal, and determining the time domain position of the interface of the black soil layer by identifying a sudden change peak of an instantaneous frequency curve of the de-noised signal. And performing Hilbert transform on the preprocessed signal to obtain an envelope signal, determining the dielectric constant of the black soil layer according to an average envelope amplitude by combining a dielectric constant model, and calculating the propagation speed of the electromagnetic wave in the black soil layer. Determining the thickness of the black soil layer at each measuring point according to the time domain position of the interface of the black soil layer at each measuring point and the corresponding electromagnetic wave propagation speed; and based on the black soil layer thickness of each measuring point, black soil layer thickness distribution data of the detection area is generated through a spatial interpolation method.

The invention discloses a thermal power generating unit control method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring a frequency characteristic value of a main frequency conversion drainage pump and liquid level information of a low-pressure heater, wherein the frequency characteristic value is a key frequency boundary value; dividing the operating frequency range of the main variable-frequency drainage pump into a plurality of frequency intervals according to the frequency characteristic value, and setting a corresponding opening calculation rule according to the operating characteristic of each frequency interval so as to form an opening frequency curve; determining the target frequency of the main variable-frequency drainage pump according to the liquid level information of the low-pressure heater so as to control the main variable-frequency drainage pump to operate according to the target frequency; the initial opening degree of the recirculation regulating valve is determined according to the opening degree frequency curve and the target frequency; and the initial opening degree is corrected according to the outlet flow of the main variable-frequency drainage pump, the opening degree of the recirculation regulating valve is controlled to be the corrected opening degree, and therefore stable control over the liquid level of the low-pressure heater and safe operation of the main variable-frequency drainage pump are achieved.

The application belongs to the technical field of unmanned aerial vehicle remote control signal recognition system, and proposes an unmanned aerial vehicle remote control signal recognition system and method based on time-frequency distribution, which comprises a data acquisition and merging module, an analysis module, a signal extraction module, a noise elimination module and a signal recognition module, adopts data acquisition and merging, performs generalized rectangle transformation on the merged time domain signal to obtain GRD time-frequency distribution, eliminates random noise, samples time-frequency sequence, and based on a three-dimensional time-frequency curve similarity search method of curvature characteristics, recognizes the extracted time-frequency spectrum characteristics, and recognizes the unmanned aerial vehicle remote control signal. The scheme of the application breaks away from the limitation of traditional Fourier transformation single frequency domain description signal characteristics.

A method of operating a power plant that includes receiving a measured frequency of a power network to which the power plant is connected, and determining whether the measured frequency falls within a first frequency sub-band that overlaps a network-defined frequency deadband. Based at least in part on the measured frequency, a first control signal is output, indicative of either: a first power offset for application to a baseline frequency curve for the power plant to generate a set point for controlling a power characteristic of the power plant; or a set point for controlling a power characteristic of the power plant, the set point being based on a first power offset applied to a baseline frequency curve for the power plant.

The invention belongs to the technical field of digital signal processing in a radio frequency / microwave communication system, and particularly discloses a multi-frequency parallel compensation method for a nonlinear phase of a radio frequency device, which is characterized by comprising the following steps of: S1, acquiring a phase-frequency curve p (f) of an output signal of a radio frequency end of the radio frequency device; s2, converting the phase frequency curve p (f) into a plurality of amplitude-frequency responses amp (f), performing inverse Fourier transform on the amp (f) to generate a filter coefficient hp, and performing M-order truncation and N-bit fixed-point quantization on the hp to generate an all-pass filter coefficient hp (m); s3, performing orthogonal down-conversion on a digital intermediate frequency signal y (n) to be compensated to a baseband, inputting the digital intermediate frequency signal y (n) into the all-pass filter, and simultaneously completing phase compensation on all frequency components contained in the y (n) by utilizing a group delay characteristic; and the compensated baseband signal is recovered to the original intermediate frequency through quadrature up-conversion, and an output signal with a corrected nonlinear phase is obtained. Phase modulation can be carried out on multiple frequency signals at the same time, frequency measurement is not needed, and frequency and data alignment does not need to be considered.

The invention relates to the technical field of electric energy monitoring, and discloses an integrated electric energy quality intelligent monitoring method, system and device based on the global internet of things and a medium, and the method comprises the steps: comprehensively monitoring power equipment through the global internet of things, collecting electric energy quality parameters, and building a collection frequency curve; calculating resource allocation delay and transmission delay, and constructing a feature vector of response lag; carrying out weighted fusion on the data and an acquisition curve to generate a comprehensive fluctuation feature vector; analyzing the abnormal event and the load dynamic state through adaptive filtering, and obtaining the load amplification rate; performing fusion to generate a multi-dimensional pressure-bearing state vector, and performing normalization processing to obtain a pressure-bearing coefficient; and realizing graded early warning and resource allocation based on a dynamic threshold value. According to the method, the problems of long delay, response lag and weak risk prediction capability of traditional monitoring are solved, accurate sensing of abnormal electric energy quality, quantitative evaluation of the pressure bearing state and intelligent response are realized, and the stability and safety of an electric power system are remarkably improved.

The application discloses a multi-source time-frequency ridge extraction method based on synchronous extraction transformation, and comprises the following steps: acquiring a gearbox time-domain vibration signal; performing variational modal decomposition filtering on the time-domain vibration signal to obtain a characteristic modal component time-domain vibration signal; performing synchronous extraction transformation time-frequency analysis on the characteristic modal component time-domain vibration signal; extracting a rotating shaft rotating frequency and a gear meshing frequency time-frequency ridge according to a local peak value search algorithm; optimizing the time-frequency ridge based on a multi-source ridge fusion method to extract a rotating frequency curve; and tracking the order of the characteristic modal component time-domain vibration signal based on the rotating frequency curve to obtain a rotating shaft fault characteristic order from an angular domain order spectrum. The method improves the frequency mutation condition and has high IF fusion precision, obtains the fault characteristic order from the order spectrum of the signal after order tracking, improves the frequency ambiguity phenomenon, and optimizes the bearing fault characteristic extraction effect.

This invention belongs to the field of early warning technology for coal mine mining, and discloses a method and system for monitoring geological disasters in coal mines using lidar combined with meteorological early warning. The method deploys lidar combined with meteorological early warning geological disaster monitoring equipment in the three upper zones of the above-ground mining area, and collects the current motion frequencies of the three upper zones in real time to obtain motion frequency curves. The three upper zones include bending subsidence zones, fracture zones, and caving zones. Beidou GNSS is deployed in the three upper zones of the above-ground mining area to smooth the acquired motion frequency curves and eliminate the influence of atmospheric delay errors. The motion frequency curves, after eliminating atmospheric delay errors and smoothing, are applied to actual mining operations in the three upper zones of the above-ground mining area to obtain deformation information generated at a certain moment during actual mining operations. This invention achieves high-precision dynamic coupling monitoring of surface geological disaster deformation during coal mining activities.