1007 results about "Center frequency" patented technology

In a wireless local area network (WLAN) system, a transmission STA can transmit a PPDU via a 320 MHz channel, and a Medium Access Control (MAC) signal may be generated for the PPDU. The MAC signal may include puncturing pattern information and channel center frequency segment (CCFS) information for a 320 MHz band. The CCFS information may include a first CCFS field related to channel center frequency (CCF) information of a primary 160 MHz channel, and a second CCFS field related to CCF information of a 320 MHz channel.

The invention relates to the technical field of radar waveform optimization, in particular to a synthetic broadband waveform optimization method based on reinforcement learning. According to the method, a deep reinforcement learning framework is adopted, and end-to-end optimization is carried out on the center frequency and amplitude parameters of multiple sub-pulses. The method comprises the following steps: constructing a synthetic broadband waveform signal model, and parameterizing sub-waveforms to determine a search space of an optimization problem; converting a waveform optimization problem into a reinforcement learning form, and defining a state space, an action space, a reward function and a state transition mechanism; based on a deterministic soft action value iteration strategy algorithm, point spread function features are extracted in combination with a Transform encoder, and sub-pulse parameters are dynamically adjusted. Through the method, the main lobe resolution can be effectively suppressed and improved, the target detection performance of a radar system is improved, and the method has good global optimization capability and environmental adaptability and is suitable for cognitive radar and adaptive waveform design scenes.

The invention discloses a wide-dynamic-range diamond NV color center magnetic sensing method and system, and the method comprises the steps: (1) calibrating the initial resonant frequency and magnetic sensing coefficient of a diamond NV color center in an initial magnetic field environment; (2) in a to-be-measured magnetic field environment, a microwave generator applies frequency-modulated microwaves to the diamond NV color center with the current resonant frequency as the center frequency; demodulating the fluorescence signal in real time by using a phase-locked detection technology to obtain an error signal; calculating the detuning amount of the center frequency in real time according to the error signal and the magnetic sensing coefficient, and further calculating the variable quantity of the magnetic field intensity; meanwhile, the detuning amount is fed back to a microwave generator to track the resonance frequency of the diamond NV color center; and (3) continuously and repeatedly executing the step (2) to realize wide-dynamic-range magnetic field measurement. The method has the advantages of wide dynamic range, high detection capability on strong and weak field mixed signals in a complex application scene and the like while giving consideration to the magnetic sensing sensitivity.

Methods, apparatuses, and computer readable media for basic service set (BSS) channel operation are disclosed. Apparatuses of a station (STA) are disclosed, where the apparatuses comprise processing circuitry configured to decode a first frame, the first frame comprising an extremely-high throughput (EHT) operation information field, the EHT operation information field comprising a channel width subfield and a channel center frequency segment, the channel width subfield indicating a basic service set (BSS) contiguous channel width, and the channel center frequency segment indicating a channel center frequency for the BSS channel width on which the BSS operates in 6 GHz. The processing circuitry further configured to encode for transmission a second frame for transmission on a primary channel within the BSS channel width.

The invention relates to the technical field of signal processing, in particular to a radar antenna signal processing method and system, and the method comprises the following steps: collecting an antenna time domain echo extraction channel energy curve, calculating the initial phase attenuation curvature of a period length energy peak value, and building an interference characteristic parameter set; matching real-time echoes, judging homology, eliminating interference, extracting main echoes, extracting main peak position spacing through frequency spectrum transformation, calculating a judgment threshold, comparing, and judging and executing decoupling operation to obtain target frequency spectrum data. According to the method, by extracting Doppler channel coherent energy distribution and establishing a periodic interference characteristic parameter set, the intrinsic characteristics of periodic interference can be accurately described, rapid judgment and effective stripping of interference source homology are achieved, and by analyzing the Doppler center frequency change trend and generating a pulse delay compensation quantized value, the interference source homology can be quickly judged and effectively stripped. The stable target identification and frequency decoupling operation under the interference background is realized, and the target identification and frequency control level in the variable environment is obviously enhanced.

The invention relates to the technical field of signal processing, in particular to a high-speed unmanned aerial vehicle structure servo elastic coupling vibration suppression control method, system and device, a medium and a program product. Obtaining a target control loop causing resonance; spectral analysis is carried out, and double-center frequencies causing resonance are obtained; a cascade wave trap with double center frequencies is designed; and the servo elastic coupling vibration of the unmanned aerial vehicle structure is suppressed. According to the method, the problems of difficulty in structure modification, narrow notch frequency range and large low-pass filtering delay of an existing structure servo elastic coupling resonance solving method are solved, the performance of a control system cannot be reduced, and the flight safety is ensured.

The invention relates to a high-speed aircraft transition identification method based on a flight test high-frequency vibration signal. The method comprises the following steps: selecting high-quality measurement point data suitable for analysis from flight test high-frequency vibration data as a vibration signal to be analyzed; performing time-frequency analysis on the to-be-analyzed vibration signal, outputting a time-frequency diagram, and representing the change condition of energy in a frequency domain by using a centroid frequency and an envelope difference of the centroid frequency; carrying out preliminary identification on the transition occurrence moment; decomposing a to-be-analyzed vibration signal into a plurality of intrinsic mode functions with different center frequencies through variational mode decomposition; quantizing the change condition of the energy of each modal component along with time; and aiming at the change condition of the energy of each modal component along with the time, the transition is identified according to the energy of the mode excited by the transition, and the energy sudden increase point is the moment when the transition begins to occur. According to the method, the transition occurrence time can be effectively identified under the condition that no hole is formed in the surface of the aircraft.

The invention belongs to the technical field of new energy storage, and relates to a full-life-cycle capacity optimization configuration method for a photovoltaic-hybrid energy storage system. A traditional configuration method of photovoltaic energy storage does not accurately consider energy storage characteristics and whole life cycle cost, and is poor in economical efficiency and reliability. According to the method, a constraint model taking the minimum sum of modal estimation bandwidths as a target is constructed based on VMD decomposition, photovoltaic power is decomposed into different components, sorting is carried out based on modal center frequencies, and a differential power distribution strategy of high frequency-super capacitor, intermediate frequency-lithium battery and low frequency-vanadium battery is provided; the method achieves the precise matching of the energy storage technology and the power fluctuation characteristics, constructs a target function covering the whole life cycle investment, operation and maintenance, replacement and scrap cost, carries out the quantitative screening of an economical efficiency optimal scheme, and solves the limitation that a frequency demarcation point does not have a clear basis. Compared with two types of energy storage schemes which are divided into'high frequency and low frequency ', the'low-medium-high frequency' scheme is lower in comprehensive cost, and a technical scheme is provided for capacity configuration of the photovoltaic energy storage system.

The invention discloses a mixed regular variational mode decomposition method, device and equipment suitable for an unsteady flow field of an aircraft and a storage medium, and relates to the technical field of flow analysis, and the method comprises the steps: determining a bandwidth estimation value and a frequency separation weight coefficient based on the unsteady flow field, an expected mode number, a spatial mode and a time evolution coefficient, constructing a first regular term and a second regular term, weighting to obtain a mixed regular term, introducing a flow field reconstruction term to establish a flow field modal decomposition variational optimization problem, converting the problem into a frequency domain optimization problem through Fourier transform, and simplifying the problem into a sub-convex optimization problem by adopting an alternating direction multiplier method; an analytic solution is obtained through a variational method and iteratively updated to obtain a flow field space mode, a time evolution coefficient frequency domain representation, a center frequency and a Lagrange multiplier, the time evolution coefficient is obtained through inverse Fourier transform, a mode decomposition result is obtained, and therefore high-precision mode separation of the unsteady flow field is achieved. And the calculation efficiency and the iteration convergence speed of the variational optimization problem are improved.

The invention relates to the technical field of laser light source measurement, and discloses a wide-range narrow-linewidth laser wavelength and linewidth measurement system, which can be flexibly matched with the center frequency of laser to be measured through the arrangement of a tunable laser, breaks through the strict limitation of the existing beat frequency method on the center frequency, effectively expands the measurement range, and improves the measurement accuracy. By combining the synergistic effect of the absorption cell and the locking loop, the system stability is improved, the measurement precision of narrow linewidth laser is guaranteed, the integration time can be flexibly adapted without tedious adjustment of a delay optical path or change of parameters of acquisition equipment through the cooperation of the optical modulator and the delay optical fiber, the problem of inconsistent measurement resolution under different integration time is avoided, and the measurement accuracy is improved. And the accuracy of short-time measurement is obviously improved. The system integrates wavelength and line width measurement functions, can measure line width, center wavelength and long-time frequency stability of to-be-measured laser, is reasonable in structural design, retains the advantage of high precision of a beat frequency method, overcomes the defects that an existing method is narrow in measurement range and inconvenient to adjust integral time, and improves the measurement accuracy of the to-be-measured laser. And the measurement requirements of wide-range and narrow-linewidth laser are met.

The invention discloses a multi-bandwidth spectrum data signal adaptive extraction method based on a signal-to-noise ratio threshold, and relates to the technical field of spectrum signal extraction. The frequency spectrum data collection covers 30MHz-6GHz, the sampling rate is 20MHz, 16-bit quantization is realized, and the hardware fluctuation is eliminated through the dual-channel design; according to noise floor estimation, 50 frames of no-signal samples are taken, mean value calculation is carried out through a sliding window, then median filtering is carried out, and the noise power and confidence interval of each frequency point are obtained; basic values are set for a signal-to-noise ratio threshold according to frequency bands, dynamic adjustment is performed in combination with real-time noise standard deviation, and compensation is added to a known frequency band; for multi-bandwidth detection, wavelet packet decomposition is adapted to 100kHz-5MHz, candidate signals are marked when energy detection exceeds a threshold, and a range is determined by morphological filtering; extracting parameters such as center frequency, analyzing time-frequency characteristics through short-time Fourier transform, and calculating 4-order cumulants to establish feature vectors; coherent accumulation times are adjusted according to a signal-to-noise ratio, energy is superposed through phase alignment, and a purified signal is output through band-pass filtering. According to the invention, the signal detection precision and adaptability in a complex environment are improved, and misjudgment is reduced.

The present application relates to a kind of radiation elements, the radiation element includes: radiator, feed rod and parasitic element, the radiator is fed by the feed rod, wherein, the parasitic element includes conductive structure, the conductive structure includes serpentine conductive path, and coupling capacitance is formed between conductive structure and radiator, and wherein, the center frequency of the operating frequency band of the radiator is greater than the center frequency of the first operating frequency band of parasitic element.Radiation element according to some embodiments of the present application can at least reduce the coupling interference between each array, improve isolation performance.In addition, the radiation element according to some embodiments of the present application can also be used to reduce the size of radiation element itself, so that radiation element is more compact.In addition, the present application also relates to a kind of base station antennas.

The invention provides a narrow-linewidth single-frequency laser frequency stabilization system and method based on a Gaussian filter, and the system employs the Gaussian filter to reduce the optical power of single-frequency laser, and employs the frequency selection characteristic of the Gaussian filter, the frequency spectrum of the single-frequency laser is a single narrow peak, and the frequency stability of the single-frequency laser is improved. When laser frequency passes through a designed Gaussian filter (the fluctuation range of a frequency-stabilized laser source is only on the left side of the center frequency of the Gaussian filter), laser signals can be reduced according to a Gaussian function rule, and along with frequency change, attenuation degrees are different and monotonically change, so that output optical power is different, and the output optical power is changed. And the optical power is compared with the optical power of a preset frequency stabilization target (a half-high point on the left side of a Gaussian filter) to obtain the deviation of the laser source relative to the target frequency stabilization frequency, so that the laser frequency is correspondingly adjusted to achieve the frequency stabilization purpose. The high-sensitivity optical power detection is realized, the response speed and the frequency stabilization precision of the system are improved, and the system is simple in structure and low in maintenance cost.

The invention discloses an anisotropic noise generation method based on local tensor integral field feature modulation, and is applied to the technical field of computer texture generation. The method comprises the following steps: step 1, constructing a global tensor field of spatial anisotropy intensity and direction; step 2, calculating local tensor integral features in a support domain based on the support domain of a Gabor noise kernel function, the local tensor integral features including principal direction features and anisotropic ratio features; step 3, calculating a curvature penalty factor based on the deviation between the local tensor integral feature and the center tensor of the seed point; step 4, based on the local tensor integral features, performing weighted correction on the frequency domain center frequency and Gaussian envelope parameters of the Gabor kernel function; and step 5, generating a final noise texture based on the corrected kernel function. The Gabor kernel function parameter is subjected to weighted correction through the local tensor integral feature and the curvature penalty factor, modulation of the kernel function direction under the high-curvature tensor field is achieved, spectrum leakage, texture fracture and artifacts caused by inconsistent direction changes in the kernel function can be reduced, and the robustness of the kernel function is improved. Therefore, the topological continuity and the simulation fidelity of the anisotropic noise texture at the complex structure are improved.

Disclosed in the present invention are a wide-angle scanning imaging device, method and system. The device comprises a sonar probe and a device body. The sonar probe comprises an acoustic array and a transceiving processing module. The acoustic array comprises a transmitting array and a receiving array. The transmitting array comprises a group of transmitting transducers. Maximum response axes of the transmitting transducers are distributed in the vertical direction according to preset tilt angles, and a plurality of transmitted beams of the transmitting transducers form wide-angle coverage in the vertical direction. The receiving array performs resolution in the horizontal direction by means of beamforming, and vertical orientations of echoes are estimated by means of double-array output phase differences. The acoustic array performs rotational motion along the central axis of the device body. The transmitting array transmits broadband orthogonal pulses according to a preset period, the receiving array receives echo signals, and the transceiving processing module processes the echo signals according to the central frequency of the transmitted pulses of the transmitting array to obtain an underwater target imaging result. The present invention reduces the impact of underwater multipath interference and the like on phase estimation and improves the 3D imaging quality.

The invention relates to the technical field of biological radar signal processing, in particular to an FMCW radar-based heart beat interval estimation method, which comprises the following steps of: S1, converting a chest vibration echo phase time sequence obtained by irradiating a chest area of a monitored object by an FMCW radar into an acceleration time sequence by using a second-order time derivative; s2, dynamically mapping the center frequency and the wavelet order in a preset frequency analysis interval, constructing a self-adaptive wavelet dictionary, then executing multi-order wavelet time domain convolution operation on the acceleration time sequence by using the dictionary, and aggregating time-frequency energy distribution to generate a time-frequency energy diagram; and S3, performing a deconvolution operation reconstruction strategy based on an energy-guided multi-stage time-frequency feature screening technology and wavelet function conjugation, generating an approximate time domain signal of heart beat vibration, and completing heart beat information inversion. According to the method, the accuracy and robustness of IBI extraction can be effectively improved under the condition of low signal-to-noise ratio, so that stable monitoring of light and moderate HRV (heart rate variability) is supported.

The invention belongs to the technical field of magnetic variable measurement, and particularly relates to a power driving compensation method and system for magnetostrictive load characteristic monitoring, and the method comprises the steps: obtaining a reference zero point of magnetic performance evolution in a cold state environment of an electromagnetic system according to the center frequency of the electromagnetic system; calculating a current main frequency impedance module value and a phase difference through an electrical parameter characterization method, and obtaining a thermal drift index reflecting a hysteresis loop distortion degree in combination with a reference zero point; obtaining correction factors of all orders based on the thermal drift index and the average output power at the current moment, and dynamically updating a coefficient vector of the inverse model; and constructing a pre-distortion driving voltage signal capable of counteracting nonlinear interference by using the new coefficient and the ideal guided wave voltage sequence, and inputting the pre-distortion driving voltage signal to a power amplifier to drive the magnetostrictive transducer. According to the invention, the problem of predistortion failure under a variable-temperature working condition in the prior art is solved, and the signal-to-noise ratio of high-power long-distance guided wave detection is remarkably improved.

The invention discloses a resonant frequency tracking control method and system for a diamond nitrogen vacancy color center, and belongs to the technical field of quantum sensing. The method comprises the following steps: setting an initial center frequency output by a microwave source; in the tracking control process, fluorescence signal changes generated by the diamond nitrogen vacancy color center under the microwave frequency modulation effect are recorded, a full-amplitude demodulation amplitude value R is obtained through demodulation, and whether the full-amplitude demodulation amplitude value R is smaller than a dead zone threshold value or not is judged; if yes, the center frequency output by the microwave source is not changed; if not, calculating the microwave frequency regulation quantity delta f according to the full-amplitude demodulation amplitude R; determining the adjusting direction of the center frequency f0 of the microwave source according to the phase-frequency characteristic and the real-time demodulation phase difference delta phi in the current frequency tracking control process; according to the microwave frequency adjusting quantity delta f and the adjusting direction, the center frequency of the microwave source is adjusted for resonant frequency tracking; wherein the phase-frequency characteristic is the characteristic of the demodulation spectral line on the two sides of the resonant frequency. The robustness and the accuracy of the resonance frequency tracking method are enhanced.

Example embodiments of the present disclosure relate to full-duplex communications. A device determines a frequency offset between a first center frequency of a first subband and a second center frequency of a carrier. Within a time duration, the carrier is split into the first subband for reception and at least one second subband for transmission. The first subband includes a set of resource blocks on the carrier. The device also determines a target sampling rate based at least on a subcarrier spacing and the number of resource blocks in the set of resource blocks. The device further processes a signal received on the first subband based on the frequency offset and the target sampling rate. In this way, the sampling rate and the frequency offset can be adaptive to a bandwidth of the first subband, thereby improving the processing of the signal.

The invention provides a frequency point GNSS observation value determination method and device, and a storage medium. The method comprises the following steps: determining a satellite-ground distance difference value between a first frequency point of a known observation value and a second frequency point of an unknown observation value; according to the satellite-to-earth distance difference value between the first frequency point and the second frequency point, the observation value of the first frequency point, the state space representation correction number of the satellite and the center frequencies of the first frequency point and the second frequency point, the pseudo-range observation value of the second frequency point and / or the phase observation value of the second frequency point are / is determined, on one hand, the satellite-to-earth distance difference between different frequency points is fully considered; on the one hand, the precision of pseudo-range observation and / or phase observation values of the recovered frequency points is higher, the requirements for the first frequency point and the second frequency point are reduced, the universality of the method is improved, on the other hand, high-precision ionized layer delay in the SSR correction number and pseudo-range hardware delay and phase hardware delay of a satellite end are effectively utilized for error compensation, and the error compensation accuracy is improved. The implementation difficulty is reduced, and the feasibility of the method is improved.

The invention relates to a measurement and control signal intelligent sensing method based on a deep neural network, and belongs to the technical field of radio signal processing and artificial intelligence crossing. According to the method, a time-frequency graph data set of broadband measurement and control signal simulation and actual measurement data is firstly constructed, and then a target detection model is trained based on the mixed simulation and actual measurement time-frequency graph data set. In the reasoning stage, based on a bounding box obtained by a target detection model, the confidence coefficient of sub-signals and time-frequency parameters such as the signal starting moment, the duration, the bandwidth and the center frequency in original record data can be obtained, and intelligent sensing of broadband measurement and control signals is achieved. According to the method, the time-frequency sub-signal bounding boxes which are not overlapped with each other are randomly generated, and the bandwidth, the center frequency and the time domain position of the sub-signals are reversely controlled, so that the generation of the time-frequency graph target labeling information is more accurate and efficient.

The invention belongs to the field of non-contact vital sign detection, and particularly relates to a millimeter wave radar arrhythmia detection method based on particle swarm optimization variational mode decomposition and deep learning, and the method specifically comprises the steps: S1, obtaining a human chest micro-motion signal through a millimeter wave radar, performing static clutter filtering, phase extraction, unwrapping and detrending processing on the radar echo signal to obtain a chest displacement signal containing heartbeat and breathing information; s2, aiming at the thoracic cavity displacement signal, constructing a variational mode decomposition model, and carrying out adaptive optimization on a mode number and a penalty factor through a particle swarm optimization algorithm to obtain an optimal decomposition parameter and complete signal decomposition; s3, according to the center frequency and the energy distribution characteristics of each modal component, screening the modal components in the heartbeat frequency range and reconstructing the modal components to obtain heartbeat characteristic signals representing heart mechanical activities; s4, carrying out time sequence segmentation on the heartbeat characteristic signals, extracting local heart beat morphological characteristics by utilizing a convolutional neural network, and carrying out modeling on a long-time rhythm dependency relationship of the heartbeat signals in combination with a time sequence modeling network based on an attention mechanism to obtain heart rhythm depth characteristic representation; and S5, inputting the heart rhythm depth features into a heart rhythm discrimination model, analyzing the heart rhythm state of the detected person, and outputting an arrhythmia detection result. According to the method, adaptive selection of variational mode decomposition parameters is realized by introducing a particle swarm optimization mechanism, heartbeat signals and respiration and motion interference components are effectively separated, modeling is carried out on rhythm characteristics in combination with a deep learning model, and non-contact detection of arrhythmia is realized. The method does not need to wear an electrode or contact a human body, has the advantages of strong anti-interference capability, good adaptability and high detection precision, and has a good application prospect in the fields of heart rhythm health monitoring, disease screening and the like.

The invention discloses an unmanned aerial vehicle noise elimination method and device for cross-medium direct acoustic communication, and the method comprises the steps: carrying out the sampling of a known detection signal and a receiving signal, obtaining a frequency domain expression, calculating a cross-medium sound pressure transmission function, and extracting amplitude response, phase response and group delay; based on a normalization ratio and local maximum detection method, identifying a center frequency set of unmanned aerial vehicle propeller noise; the notch depth, bandwidth, frequency compensation and phase compensation are determined by combining channel characteristic parameters, and a cascade notch filter is constructed; and inputting the channel characteristic parameters into the deep learning model, outputting a filter parameter correction amount, realizing dynamic updating of the filter, obtaining the filter capable of suppressing noise, and further obtaining a denoised communication signal. According to the invention, precise detection of propeller noise frequency and multi-dimensional adaptive adjustment of filter parameters can be realized.

The invention provides a Brillouin frequency shift extraction method and device, equipment and a storage medium, and relates to the technical field of optical fiber sensing, and the method comprises the steps: carrying out the algebraic conversion of a measured Brillouin scattering gain spectrum into a Brillouin center frequency curve; according to the Brillouin center frequency curve, the approximate value of the center frequency of the maximum value position of the Brillouin scattering gain spectrum is solved, then the center frequency of the Brillouin scattering gain spectrum is determined, that is, a frequency shift extraction result is given in a multi-center-frequency statistical mode, and the method has the advantages of being high in precision and stability. Meanwhile, a fitting tool does not need to be used in the calculation process, and the calculation complexity is extremely low; compared with the prior art, the method provided by the invention has the advantages that the method is not easily influenced by a multi-peak Brillouin form, and particularly, a high-precision result can be given for common bimodal form data, so that the technical problems of large error, high calculation complexity and great influence of an initial value on the fitting success rate and the stability are solved.

The invention relates to the technical field of navigation signal analysis, in particular to a QPSK (Quadrature Phase Shift Keying) non-cooperative navigation signal analysis method and a QPSK non-cooperative navigation signal analysis system for multi-domain feature joint estimation. Traversing phases in the phase sequence in sequence, and obtaining an energy threshold value in combination with the center frequency estimation value of the current section; performing iterative analysis on the frequency and the phase to obtain estimated values of the frequency and the phase; obtaining a complex baseband signal through the estimated values of the frequency and the phase; judging whether IQ code crossing occurs or not according to a cross-correlation relationship between the complex baseband signal and a local code stream sequence, and if the code crossing occurs, performing adjustment to obtain a corrected I-path baseband signal and a corrected Q-path baseband signal; adjusting the length of a chip through a code rate so as to reconstruct a code element sequence and obtain I-path and Q-path pure code element sequences; and taking the I-path and Q-path pure code element sequences as analysis results of the non-cooperative navigation signals. According to the invention, the accuracy of analyzing the non-cooperative navigation signal is improved.

The invention discloses a micro-scratch filtering method and device in wafer defect detection, equipment and a storage medium, and the method comprises the steps: extracting the frequency spectrum characteristics of a wafer image, carrying out the direction characteristic analysis based on the frequency spectrum characteristics, and carrying out the calculation to obtain the center frequency of a target region suspected to have micro-scratches; constructing a Gabor filter according to the center frequency, and reinforcing the target area by using the Gabor filter; respectively carrying out gray integration along the direction vector and the vertical direction vector of the linear defect of the strengthened target area, and calculating the strength attribute of the target area; and when the strength attribute is higher than a preset threshold value, marking the defect of the target area as a micro-scratch and filtering out the micro-scratch. According to the method, the micro scratches in the image can be accurately positioned and filtered out, and the influence of the micro scratches on the accuracy of wafer defect detection is prevented.

The invention discloses a steady-state wind power grid-connected power system frequency instability risk quantitative evaluation method considering an active disturbance probability, and belongs to the field of power system stability analysis. The method comprises the following steps: inputting steady-state power flow information of each grid-connected power generation cluster into an XGBoost-based speed regulation system frequency modulation parameter identification model to obtain frequency modulation parameters, and obtaining a primary frequency modulation polynomial equivalent analysis model of each cluster; simplifying a calculation formula of an inertia center frequency deviation extreme value based on an active-frequency open-loop decoupling model; setting a multi-level inertia safety boundary by referring to various active disturbance occurrence probabilities; and establishing a piecewise linear thought-based steady-state frequency stability margin quantitative evaluation index for online evaluation of the inertia level of the system, and analyzing the steady-state system frequency stability margin and the frequency instability risk in real time. According to the method, the influence of wind power integration on the frequency response process of the power system is considered, online real-time accurate evaluation of the system frequency stability margin in a steady state is realized, and a reference basis is provided for formulating frequency stability control measures.

The invention relates to the technical field of power distribution, and particularly discloses a power distribution network monitoring system and a power distribution network, which are used for solving the problems that when a weak wave head, frequency dispersion, multi-branch reflection and time service jitter coexist in the prior art, unified setting and consistent time scales cannot be realized, missing detection, false peak preemptive, arrival time offset, unstable cross-end fusion and large positioning error are easily caused. The system comprises a synchronous transient sampling unit, a phase-mode decoupling unit, an MRSVD decomposition unit, a VMD decomposition unit, a feature statistics unit, a parameter management unit, an SDEO calibration unit, a time mark fusion unit, a data storage unit and a master station processor. According to the method, kurtosis K, entropy H and kurtosis entropy ratio are taken as a unified parameter source, phase mode decoupling, MRSVD, VMD, SDEO and time scale fusion are performed, a cross-unit collaborative setting and traceable distribution mechanism is constructed, line mode selection, singular value truncation, modal number and center frequency are linked, and a closed loop is formed by binding with topology and time service.

The invention relates to the technical field of optical fiber sensing signal processing, in particular to a DAS signal floor noise elimination method, system and equipment based on statistical analysis, and the method comprises the steps: initializing system parameters, and loading a DAS application field data matrix; performing slicing and frequency domain transformation on the DAS original data; dynamically determining a peak threshold value, and performing adaptive peak searching according to the peak threshold value; sorting the identified and screened local maximum values in a descending order, and selecting frequencies corresponding to the local maximum values as main frequency candidates; performing clustering analysis on the selected dominant frequency candidates; calculating the cumulative proportion of each main frequency in the total statistics, selecting a center frequency, and forming the multi-frequency band elimination of the monitoring unit by using band elimination frequency bands formed by different center frequencies; and adding the multi-frequency band elimination to a statistical filtering frequency band set of all the point locations, storing the statistical filtering frequency band set of all the point locations as a statistical model, and performing background noise elimination on the DAS original signal based on the statistical model.

The invention relates to the technical field of inertial sensor state data analysis, and discloses a frequency domain processing-based inertial sensor data analysis method, which realizes frequency domain analysis on actual error composition of an inertial sensor, thereby improving the accuracy of effective system performance analysis of the inertial sensor. The method specifically comprises the following steps: S1, acquiring an original output signal by adopting an MEMS inertial measurement unit of a sensor; s2, decomposing a time domain signal in the original output signal into a solid mode equation and a residual term through a mode decomposition algorithm; extracting a solid-state model equation by using a screening algorithm through empirical mode decomposition, and updating a residual error; selecting a center frequency by using signal characteristics and priori knowledge through variational mode decomposition, extracting a solid-state mode equation at the center frequency, and modeling as a function about amplitude phase frequency; s3, performing Hilbert-Huang transform on the components of the solid mode equation to generate a Hilbert spectrum in time-frequency domain joint distribution; and S4, constructing a sensor performance evaluation model based on the Hilbert spectrum.