215 results about "Frequency space" patented technology

The invention discloses an electromagnetic compatibility test data automatic acquisition and analysis method and system. The method comprises the following steps: automatically acquiring electromagnetic compatibility test data as an input signal and extracting a target signal; respectively extracting an amplitude component and a change rate component of the target signal, combining to obtain a complex eigenvalue, and performing time integration on the complex eigenvalue to obtain an eigenvector component of the target signal; dividing a frequency space into a low-frequency band and a high-frequency band, and calculating the power density of each frequency point of the target signal in a segmented manner; and carrying out quantitative analysis on the electromagnetic compatibility to obtain an electromagnetic compatibility score. According to the method, the target signal can be accurately extracted from the mixed input signal in real time, the multi-dimensional features are extracted from the target signal, the time domain and frequency domain features of the target signal are comprehensively described, the frequency spectrum power density is accurately calculated in a segmented and adaptive manner, the accurate quantitative analysis of the electromagnetic compatibility level is realized, and the accuracy of the electromagnetic compatibility is improved. And the accurate evaluation requirements of different test scenes on the compatibility level can be met.

The invention discloses an inter-Doppler interference suppression method based on a Gaussian learning factor particle swarm algorithm. The inter-Doppler interference suppression method comprises the following steps that pilot frequency and data symbols are coded to a resource grid of a two-dimensional time delay Doppler domain through orthogonal time-frequency space modulation; on a transmitter, mapping data on a time delay Doppler domain grid to a time-frequency domain through inverse symplectic finite Fourier transform to obtain a time-frequency domain signal; performing Hisenberg transformation on the time-frequency domain signal to obtain a time domain sending signal; obtaining a time domain receiving signal after the time domain sending signal passes through a wireless channel; performing Doppler compensation processing on the time domain receiving signal by using Doppler frequency shift to obtain a signal after Doppler compensation; then performing matched filtering on the signal after Doppler compensation and a received pulse, and sampling to obtain a matched filter output signal; and the matched filter output signal is subjected to the Sextile Fourier transform to obtain a time delay Doppler receiving signal. The method can realize suppression of inter-Doppler interference to a certain extent.

The invention provides a partial discharge mode recognition method based on multi-channel sound signal time-frequency space spectrogram fusion, and belongs to the technical field of partial discharge mode recognition. The problem that information redundancy and difference between existing multi-channel sound signals cannot be effectively fused and discriminant features cannot be extracted is solved. The method comprises the following steps: collecting and summarizing multichannel sound signal data corresponding to different partial discharge models as a data set; performing normalization processing on the original multichannel partial discharge sound signal, and mapping a time domain signal into time-frequency joint distribution to obtain a gray scale time-frequency spectrogram; performing multi-scale and multi-direction decomposition on the grayscale time-frequency spectrogram to obtain each channel sub-graph; different fusion strategies are used for fusing the channel sub-graphs obtained through decomposition; reconstructing a time-frequency space fusion spectrogram from the fused sub-graphs of each channel through inverse transformation; extracting features; identifying a partial discharge mode; the method is applied to partial discharge detection.

The present application provides a method for extracting surface wave dispersion curves based on strain fields, including the steps of: extracting strain data from seismic observation data; preprocessing the strain data according to the type of the seismic observation data to obtain strain components; converting the strain components from the time-space domain to the frequency-space domain through Fourier transform; converting the strain components from the frequency-space domain to the frequency-phase velocity domain through frequency-Bessel transform to obtain the surface wave dispersion spectrum of the strain components; and picking up the surface wave dispersion curves according to the surface wave dispersion spectrum. The present application fills the technical gap in extracting surface wave dispersion information from DAS data, provides a powerful tool for extracting surface wave dispersion information applicable to single-component or multi-component DAS data, has important theoretical significance and practical value for the development of surface wave dispersion imaging methods based on DAS observations, and provides ideas for extracting the dispersion information of surface waves or body waves such as Rayleigh waves, Scholte waves, and Love waves.

The present invention relates to the technical field of seismic exploration. Provided are a three-component seismic data vector anti-aliasing interpolation reconstruction method and an apparatus. The method comprises: representing three-component seismic data in a time domain as pure quaternions for vector joint; transforming the pure quaternion data in a time-space domain to a frequency-space domain to obtain frequency-space domain data; transforming the frequency-space domain data into a frequency-wave number domain; in the frequency-wave number domain, using an inclination angle scanning strategy to construct a mask matrix; performing vector anti-aliasing interpolation reconstruction on the frequency-space domain data and the mask matrix, so as to obtain a frequency-space domain reconstruction result; and inversely transforming the frequency-space domain reconstruction result to the time-space domain to obtain a time domain three-component three-dimensional data anti-aliasing reconstruction result. The present invention can effectively solve the problem of vector anti-aliasing reconstruction for three-component seismic data that contain both irregular and regular missing traces, thus improving the accuracy of effective wave event identification.

The invention discloses an I SAR fusion imaging method, system and device based on centralized multi-station networking, and relates to the technical field of radar imaging, and the method comprises the steps: obtaining I SAR frequency domain echo data of each subsystem; performing frequency domain space matching on the frequency domain echo data based on the observation angle difference of each radar; performing frequency domain alignment processing on the matched frequency domain data; and fusion and imaging are carried out. According to the I SAR fusion imaging method, system and device based on the centralized multi-station networking, the imaging resolution is remarkably improved, multi-station frequency domain data are mapped to a unified local frequency space through a coordinate transformation matrix, non-uniform data are subjected to uniform reconstruction in combination with a self-adaptive interpolation algorithm, and the imaging resolution is remarkably improved. The frequency domain integration interval is effectively expanded, compared with a single-station I SAR which only covers a local area of the total rotation angle of the target, the range resolution is further optimized through multi-station bandwidth synthesis in the range direction, and high-fidelity reconstruction of the target in the complex shape is achieved.

A squeezed light generator may include a triply-coupled optical resonator having a triplet resonance with a split-resonant frequency spacing Ω, where the triplet resonance receives light at frequencies associated with at least one split-resonant frequency in the triplet resonance and generates squeezed light with at least another split-resonant frequency in the triplet resonance.

The embodiment of the invention relates to the technical field of computer vision, in particular to an RGBT target tracking method based on frequency space enhancement and time adaptation, which comprises the following steps: obtaining a training sample set which comprises a plurality of video sequences, and each video sequence is composed of a visible light image and a thermal infrared image which are paired; constructing an RGBT target tracking model based on frequency space enhancement and time adaptation, wherein the RGBT target tracking model is composed of a frequency space enhancement network, a cross-modal feature extraction network and an online score prediction network; performing iterative training on the RGBT target tracking model based on the training sample set until convergence to obtain a trained model; and inputting the target video into the trained model to obtain a tracking result of the target video output by the trained model. According to the method, the coping capacity of RGBT target tracking in challenging scenes such as background interference and thermal crossover can be well improved, and the accuracy, efficiency and robustness of RGBT target tracking are effectively improved.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter network node may generate a guard interval (GI)-based orthogonal time frequency space (OTFS) waveform comprising at least one defined sequence associated with at least one GI in a time domain corresponding to the GI-based OTFS waveform. The transmitter network node may transmit at least one signal based on the GI-based OTFS waveform. Numerous other aspects are described.

The invention provides a two-stage fractional order time delay and Doppler frequency shift estimation method based on an orthogonal time frequency space (OTFS). The two-stage fractional order time delay and Doppler frequency shift estimation method based on the OTFS is characterized in that the two-stage fractional order time delay and Doppler frequency shift estimation method based on the OTFS is provided; firstly, integer estimation of time delay and Doppler frequency shift is carried out by using a maximum likelihood estimation method, and the integer range of the time delay and Doppler frequency shift is determined; secondly, the Fibonacci sequence is used for determining the segmentation proportion, and the integer interval is segmented; and then, calculating an inner product of a sending signal subjected to channel influence and a receiving signal, selecting a segmentation point with the maximum inner product to generate a new search area, re-determining the segmentation proportion, and repeating the steps until the maximum iteration frequency is reached. And finally, calculating the distance and the speed of the target by using the obtained time delay and Doppler frequency shift. According to the OTFS modulation-based two-stage fractional order time delay and Doppler frequency shift estimation method designed by the invention, fractional order time delay and Doppler frequency shift can be accurately estimated, and an important theoretical basis is provided for realizing target perception in a communication and induction integrated system.

The invention belongs to the technical field of mobile communication, and particularly relates to an orthogonal time-frequency air conditioning-based integrated waveform design method, which comprises the following steps of: constructing a receiving and transmitting filter bank with a frequency spectrum shaping characteristic on a time domain level, converting an item with a complex analytic expression in a traditional architecture into a scaling factor capable of being linearly processed, and carrying out linear processing on the scaling factor; architectural simplification of a sensing signal processing flow is realized; on a delay Doppler domain level, aiming at an inter-Doppler interference mechanism caused by static environment clutter coupling and a fractional Doppler effect, a pilot frequency sequence matrix with a strong self-correlation main lobe and a weak cross-correlation side lobe is innovatively constructed, and accurate separation of aliasing echoes is realized by using a sharp delay-Doppler resolution characteristic of the pilot frequency sequence matrix. According to the scheme, through the cross-domain cooperation mechanism, on the premise of maintaining the communication sensing dual-mode performance, double breakthrough of signal processing architecture simplification and pilot frequency overhead optimization is achieved, and an innovative design framework is provided for a communication sensing integrated system in a mobile scene.

The invention provides a signal detection method for a multi-antenna orthogonal time-frequency-space sparse code division multiple access system, which is characterized in that dimensionality reduction is carried out on time domain and time delay Doppler domain signals by utilizing sparsity of a sparse code division multiple access codebook, and prior distribution of the time domain signals is approximated by using Gaussian distribution. Preliminary detection is realized by acquiring cavity distribution of a signal in a time domain, and the posterior probability of the signal is calculated by using a sparse code division multiple access codebook in a time delay Doppler domain. Based on a transformation relation in a multi-antenna orthogonal time-frequency-space sparse code division multiple access system, information exchange between a time domain and a time delay Doppler domain is realized. The sparse structure of the time domain matrix in the multi-antenna orthogonal time-frequency-space sparse code division multiple access system is utilized, and the complexity of matrix inversion in the algorithm is reduced. By using the method, the complexity of algorithm implementation can be reduced while the signal detection performance is ensured by utilizing the dual sparsity of the multi-antenna orthogonal time-frequency-space system and the sparse code division multiple access codebook.

The invention provides an OTFS (Orthogonal Time Frequency Space) channel estimation method based on a bidirectional gating loop unit (BiGRU) and a multi-head attention mechanism, and belongs to the technical field of channel estimation. The method comprises the following steps: determining time delay-Doppler domain parameters according to a channel scene, and constructing a TDL (Tap Delay Line) channel model; designing a time-frequency domain pilot frequency structure; carrying out time-frequency domain modulation on a sending signal and adding high-power amplifier (HPA) nonlinear distortion; obtaining an initial channel state by using LS estimation; a BiGRU network and multi-head attention mechanism joint model is constructed, and channel state prediction is realized through bidirectional time sequence feature extraction and multi-dimensional attention weight distribution; and time delay-Doppler domain channel response reconstruction is completed by using the optimized model. Bidirectional dependency of channel time-varying features is captured through BiGRU, and a multi-head attention mechanism is combined to enhance the key path feature extraction capability, so that the channel estimation precision in a high-mobility scene is remarkably improved, and the influence of HPA nonlinear distortion on the system performance is effectively inhibited.

The invention provides a construction method and system of a non-reciprocal emission / absorption device with a Fizeau dragging effect. The construction method comprises the following steps: selecting a metal substrate, a dielectric grating and a two-dimensional material; applying a bias voltage in the x-axis direction to the two-dimensional material layer to generate a Fizeau dragging effect; the bias voltage is adjusted under TM polarization, so that the electron drift speed is close to the Fermi speed, asymmetric surface plasmon resonance is excited, and unequal emissivity and absorptivity are achieved; an adjustable singular point is generated in an angle-frequency space by adjusting the filling ratio of the grating, so that the numbers of spectral formants of emissivity and absorptivity near the singular point are different, and the wavelength integral nonreciprocity intensity is improved. The non-reciprocal heat radiation characteristic can be realized through voltage regulation and control without an external magnetic field.

The application discloses a large-scale PDE neural operator pre-training method based on a high-frequency enhancement module, a partial differential equation (PDE) data set is composed into a mixed data set, a large-scale PDE neural operator is constructed, preprocessed PDE data is mapped to a latent representation space through a space-time encoder, a frequency decomposition module is used for frequency space mapping, the frequency decomposition module includes parallel high-frequency branches and low-frequency branches, and high-frequency features and low-frequency features are obtained respectively; a multi-frequency fusion module (GFM) adaptively fuses the high-frequency features and the low-frequency features through a gating mechanism; finally, a prediction head is used for processing the fused features, and final output features, i.e., predicted physical features of a next time step, are obtained. The application firstly introduces an explicit frequency division and a high-frequency enhancement mechanism, the input field is divided into low-frequency and high-frequency parts, the low-frequency branches / high-frequency branches are used for processing respectively, and thus the model can simultaneously consider global trend modeling and local gradient detail reconstruction.

The invention provides an orthogonal time-frequency air conditioning communication system demodulation method based on deep learning. The method comprises the following steps: constructing an orthogonal time-frequency air conditioning communication system model and an interference model; according to communication system characteristics and anti-interference requirements, constructing a network structure combined by a convolutional neural network and a bidirectional long-short-term memory network; preprocessing the training data, and performing time sequence alignment on the input data and the label data; inputting the preprocessed data into a CNN (Convolutional Neural Network) to extract local spatial features, inputting the data into a combined network, capturing time-dependent features, calculating a mean square error loss function according to a predicted demodulation bit and a real bit, calculating a network parameter gradient by using a back propagation algorithm, and updating network parameters by using an optimizer according to the gradient; and carrying out model training until expected requirements are met. According to the invention, the advanced neural network architecture is innovatively combined, so that the communication reliability and robustness of the communication system in the interference environment are effectively improved.

The application provides a bridge damage assessment method and system caused by ship collision and a medium, and relates to the technical field of bridge health monitoring. The method comprises the following steps: collecting acceleration response signal arrays of different heights and positions of a bridge pier, and generating a time series matrix; drawing a time-frequency coherence spectrum under different base functions, and obtaining a coherence spectrum entropy; determining the optimal base function based on the information entropy principle; obtaining the local correlation coefficient of the time series matrix in the time-frequency space under the optimal base function, and drawing a time-frequency coherence spectrum; evaluating the correlation and dependence degree between time series according to the local correlation coefficient and the time-frequency coherence spectrum, and judging whether the ship-bridge collision damage occurs; if the collision damage occurs, calculating the time-frequency coherence damage factor of the time series matrix at different positions, and determining the collision position and the collision degree according to the maximum protruding value in the time-frequency coherence damage factor trajectory curve. The method can effectively separate the influence of environmental factors, and provides basic method support for establishing the ship-bridge collision damage assessment technology.

The present invention discloses a low-complex, reliable multidimensional orthogonal time-frequency space (ND-OTFS) modulation-based communication system for uplink and downlink wireless communication between resource-constrained Internet of Things (IoT) and machine-to-machine (M2M) devices comprising at least one transmitter configured to transmit bit stream involving N-Dimensional signal mapper and OTFS frame and at least one receiver configured to be integrated into said IoT or M2M devices, featuring a low-complexity detector for receiving the transmitted bit stream.

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

The invention relates to the technical field of seismic exploration, and provides a three-component seismic data vector anti-aliasing interpolation reconstruction method and device. The method comprises the following steps: representing three-component seismic data as a pure quaternion in a time domain, and carrying out vector combination; converting the pure quaternion data of the time-space domain into a frequency-space domain to obtain frequency-space domain data; converting the frequency-space domain data into a frequency-wave number domain; constructing a mask matrix in the frequency-wavenumber domain by using an inclination angle scanning strategy; performing vector anti-aliasing interpolation reconstruction based on the frequency-space domain data and the mask matrix to obtain a frequency-space domain reconstruction result; and inversely transforming the frequency-space domain reconstruction result to a time-space domain to obtain a time domain three-component three-dimensional data anti-aliasing reconstruction result. The method can effectively solve the problem of anti-aliasing reconstruction of three-component seismic data vectors containing irregular missing traces and regular missing traces, and can improve the accuracy of effective wave event identification.

The invention relates to an unmanned aerial vehicle physical layer secret key secret communication method based on an orthogonal time-frequency space. Comprising the following steps: establishing an unmanned aerial vehicle air-ground communication system consisting of a multi-antenna unmanned aerial vehicle base station, ground single-antenna legal users and ground passive eavesdropping illegal users; obtaining channel estimation vectors of all dominant paths by adopting a three-dimensional structured orthogonal matching pursuit algorithm; the method comprises the steps of obtaining a channel characteristic value of a communication channel through a path gain self-adaptive weighted moving average coding method, carrying out double-bit uniform quantization, carrying out Winnow key negotiation based on dynamic grouping and carrying out SHA-2 hash function confidentiality enhancement, and thus obtaining a physical layer key. According to the method, the channel dimension is converted through the orthogonal time-frequency space technology, the influence of Doppler frequency shift is effectively resisted, the channel reciprocity is improved, the key inconsistency rate is reduced, and the safety and stability of a communication system can be remarkably improved.

The invention relates to a frequency-space hybrid joint source channel coding method and an image transmission method. The method comprises the following steps: inputting an image to be transmitted into a joint source channel coder, and mapping the image into a channel input vector; an image block embedding module and a frequency space mixing module are sequentially arranged in each encoder layer of the joint source channel encoder, the frequency space mixing module independently divides a high-frequency feature and a low-frequency feature into two branches for parallel processing, and outputs of the high-frequency and low-frequency branches are spliced along a channel dimension and then are subjected to spatial feature modeling. The output of the frequency space mixing module is input into a next encoder layer; a channel adaptive attention mechanism is introduced into an encoder layer, real-time channel SNR is embedded into attention calculation of each encoder layer, and attention focuses are dynamically adjusted according to the real-time channel SNR. Compared with the prior art, the self-adaption to different channel signal-to-noise ratios is realized, and the reconstruction quality of two types of information of high-frequency texture and global semantics is effectively considered under the same code length.

The invention relates to the orthogonal time-frequency-space field of wireless communication, in particular to an OTFS wireless data-energy simultaneous transmission method based on a frequency domain equalizer in a high-mobility environment. A wireless information and energy simultaneous transmission technology is applied to an OTFS transmission system, a power distribution and frequency domain linear equalizer is introduced, a strict mathematical optimization model is established according to a system model and an SWIPT power division structure, an optimal power division factor and an optimal power distribution scheme are solved by using a convex optimization method, and the optimal power division factor and the optimal power distribution scheme are obtained. The objective of the invention is to maximize a partial signal-to-noise ratio or a signal-to-signal plus interference plus noise ratio of a receiving end of a system for information decoding. Simulation results show that the proposed optimal power allocation scheme obtains lower bit error rate performance, and meanwhile, compared with an OFDM transmission system, it is proved that OTFS transmission has better system performance in a high-speed mobile environment.

The present disclosure proposes a precoding method, apparatus and device, and a storage medium, the method comprising: a sending device determining N layers of first signal streams needing to be sent in an orthogonal time-frequency-space OTFS system, N being a positive integer; converting the N layers of first signal streams from a time delay Doppler DD domain to a time frequency domain to obtain N layers of second signal streams; pre-coding the N layers of second signal streams to obtain M paths of third signal streams, wherein M is a positive integer; converting the M paths of third signal streams from a time-frequency domain to a time domain to obtain M paths of fourth signal streams; and sending the fourth signal stream to a receiving device. The embodiment of the invention provides a pre-coding method which can be applied to the OTFS system so as to successfully realize signal pre-coding in the OTFS system.

The application discloses a core RQD segmentation method based on frequency-space feature enhancement and long-distance dependence, comprising: spatial feature coding is performed on a core tank image to obtain output features, and a core feature map is determined; a morphological center axis of a core instance mask is extracted, and an accurate pixel length is calculated; a plurality of cores satisfying a core length threshold are screened, and a rock quality index in a region corresponding to the core tank is calculated. The application reduces technical bottlenecks such as loss of micro-fissure features, limited long-distance spatial dependence perception, discontinuous long-strip core segmentation and complex background interference in core segmentation; the average precision mean on the NEU-Rock dataset reaches 95.5%, which significantly reduces the parameter quantity and calculation amount compared with the prior art; and the core image can be converted into an accurate rock RQD index in real time and with high fidelity, thereby providing objective and robust digital support for mineral exploration and rock mass stability evaluation.

The application discloses a stratum absorption compensation method, system, device, storage medium and program product. The method comprises the following steps: converting an original seismic record into a frequency space domain seismic record; constructing a target function of a signal space prediction operator according to the frequency space domain seismic record and solving the target function to obtain a low-frequency signal space prediction operator; based on the frequency extendibility of the signal space prediction operator, a high-frequency signal space prediction operator is obtained by extrapolation of the low-frequency signal space prediction operator, and then a full-frequency signal space prediction operator is obtained; a full-frequency prediction error filter is obtained according to the full-frequency signal space prediction operator; and based on the full-frequency prediction error filter and the frequency space domain seismic record, a target function of stratum absorption compensation is constructed and solved to obtain an absorption-compensated seismic record. The application can inhibit the influence of noise interference on absorption compensation and improve the recovery precision of absorption compensation on seismic signals.

The application discloses a frequency-space domain alternating iteration seismic random noise suppression method and system, transforms a seismic signal from a time-space domain to a frequency-space domain, and obtains a frequency slice by taking data of a fixed frequency domain index; arranges the frequency slice into a Hankel matrix and performs singular value decomposition, selects singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix; obtains the reconstructed frequency slice, and takes the next frequency slice to complete spatial direction denoising; takes single seismic trace data of a fixed space domain index in the frequency-space domain data, arranges the single seismic trace data into a Hankel matrix and performs singular value decomposition, selects singular values and corresponding singular vectors to perform rank reduction reconstruction on the Hankel matrix; then, the reconstructed single seismic trace data is obtained through anti-diagonal average, the next seismic trace data is taken, the obtained frequency-space domain data after denoising is transformed back to the time-space domain, and a signal after noise suppression is obtained.

The invention discloses a large-scale PDE neural operator pre-training method based on a high-frequency enhancement module, and the method comprises the steps: forming a mixed data set through partial differential equation PDE data, constructing a large-scale PDE neural operator, mapping the preprocessed PDE data to a potential representation space through a space-time encoder, carrying out the frequency space mapping of the data through a frequency decomposition module, and carrying out the pre-training of the large-scale PDE neural operator. The frequency decomposition module comprises a high-frequency branch and a low-frequency branch which are parallel to obtain high-frequency features and low-frequency features respectively; the multi-frequency fusion module GFM adaptively fuses the high-frequency features and the low-frequency features through a gating mechanism; and finally, the fused features are processed through a prediction head, and final output features, namely predicted physical features of the next time step, are obtained. According to the method, an explicit frequency division and high-frequency enhancement mechanism is introduced for the first time, an input field is decomposed into a low-frequency part and a high-frequency part, and a low-frequency branch and a high-frequency branch are adopted for processing, so that the model can give consideration to global trend modeling and local gradient detail reconstruction at the same time.

The invention discloses a strain clamp X-ray image enhancement and defect identification method and system, and belongs to the technical field of image processing. The method comprises the following steps: acquiring an internal image of a wire clamp through X-rays, and performing feature reconstruction and defect modeling in a frequency space and a potential space; a multi-scale frequency encoder is adopted to extract detail features of a tension clamp image, a frequency domain structure selection module is combined to enhance defect edge response, and finally robust identification of an abnormal region is realized in a potential diffusion process. Therefore, good defect detection precision and boundary definition can be kept under the complex conditions of strong background noise interference, low image contrast and the like.

The invention belongs to the technical field of relay protection of a power distribution network of a power system, and provides a single-phase broken line grounding fault detection method for an ungrounded neutral system, which comprises the following steps of: 1, acquiring three-phase current signals of each feeder line; step 2, performing morphological filtering processing on the acquired negative sequence current signal; step 3, mapping the filtered negative sequence current signal to a time-frequency space with u as a variable; 4, searching an optimal twiddle factor according to the energy focusing characteristic of the time-frequency current signal; according to the method, the symmetric component method, the morphological filtering and the coordinate transformation technology are combined, so that the accuracy and the stability of single-phase broken line grounding fault feature extraction of the neutral ungrounded system are remarkably enhanced, and the precision and the reliability of fault detection are greatly improved; and meanwhile, the optimal twiddle factor is adaptively determined based on the feeder energy concentration ratio, so that the detection strategy can flexibly adapt to different fault conditions, and the fault detection efficiency and success rate under a complex power grid structure and variable operation conditions are effectively improved.