11 results about "Windowed fourier transform" patented technology

The invention discloses a cable hidden damage fault positioning method and device and a computer program product, and the method comprises the steps: S1, obtaining the structural parameters of a detected cable, building a one-dimensional distribution parameter transmission line model according to the structural parameters, and dividing the whole cable into a plurality of normal sub-segments and defect sub-segments; s2, calculating a reflection coefficient spectrum of a cable head end reflection coefficient along with frequency change according to distribution parameter change caused by moisture intrusion; s3, performing spectrum analysis on the reflection coefficient spectrum by adopting windowing Fourier transform, inhibiting spectrum leakage and extracting a periodic component of the spectrum leakage; and S4, determining a defect position according to the extracted periodic component frequency in combination with the propagation speed of the electromagnetic wave in the cable. According to the method, the positioning precision of the hidden damage fault of the cable can be improved, the test frequency requirement is reduced, and the diagnosis robustness in different load environments is enhanced.

The present application relates to the field of sound system self-checking and assembly defect diagnosis, aiming to realize the automatic identification and tracing of speaker assembly defects. The core technology includes collecting the acoustic feedback of the speaker after frequency sweep excitation through the microphone, obtaining high-quality time-domain signals, and using signal energy window judgment and segmented windowed Fourier transform to extract frequency domain features. Based on the six-dimensional interpretable feature vector, a solidified weight full connection encoder is used to generate a squeak fingerprint code, realizing defect mode activation intensity analysis. Combined with the fault knowledge base, a multi-modal evidence package containing spectral highlights and natural language diagnostic conclusions can be output, and low-bandwidth compression and Bluetooth BLE protocol are supported for tracing the production line quality. This scheme improves the defect identification accuracy and diagnostic interpretability, facilitating production line automation and product quality tracing.

The invention discloses a target harmonic signal complex frequency estimation method based on frequency domain least square, and belongs to the technical field of signal processing, and the method comprises the steps: obtaining a geophysical observation time sequence containing a target harmonic signal; windowing Fourier transform is adopted to obtain an initial power spectrum, and a spectrum peak of the target harmonic signal is identified; selecting power spectrum values at a plurality of frequency points near the target spectrum peak, and obtaining complex frequency parameters of the target harmonic signal by using linear least square fitting; zero-filling expansion is adopted to increase effective frequency points of a power spectrum, and the estimation precision of complex frequency parameters is improved through multiple least squares. According to the method, Fourier transform and linear least square fitting are combined, high-precision estimation of the complex frequency of the target harmonic signal can be achieved, the method is simple, efficient and easy to implement, and the method is successfully applied to scenes such as earth normal mode frequency extraction and ocean partial tide parameter inversion and can be expanded to any time sequence signal analysis such as communication and biomedicine.

The present application relates to a kind of MMC valve electric stress equivalent calculation method, device and storage medium, wherein method includes: step S1: based on electromagnetic transient simulation obtains the time-domain waveform of each working condition under flexible converter valve bridge arm current;Step S2: select the time-domain waveform of any phase bridge arm current is obtained by windowed Fourier transform in preset time window, and further extract direct current component and fundamental frequency alternating current component;Step S3: draw electric stress curve;Step S4: based on the electric stress curve under each working condition respectively statistics first eigenvalue of the first characteristic value of the electric stress level of direct current component and the second eigenvalue of the electric stress level of fundamental frequency alternating current component;Step S5: obtain test direct current value and test alternating current value after combining safety factor.Compared with prior art, the present application accurately quantifies the electric stress requirement of flexible converter valve from system operating condition without relying on large-scale physical test.

The application discloses a kind of based on windowed Fourier transform's time domain modified heterodyne signal positioning method and device, it is related to signal processing technical field, including: obtaining local oscillator light signal and echo signal light signal, according to local oscillator light signal and echo signal light signal, obtain local oscillator light phase and echo signal light phase;According to local oscillator light phase and echo signal light phase, using balanced detector, after filtering direct current component, obtain optical heterodyne intermediate frequency current signal;Using windowed Fourier transform identifies the maximum of optical heterodyne intermediate frequency current signal spectrum peak value, determines the initial position of optical heterodyne intermediate frequency current signal;According to the characteristics of balanced detector, obtain phase difference, and phase difference is converted into time domain difference;Using time domain difference corrects the initial position of optical heterodyne intermediate frequency current signal, obtains the accurate initial position of optical heterodyne intermediate frequency current signal.The application can obtain more accurate range intensity image.

The present application relates to the technical field of atmospheric optical remote sensing, and discloses a method and system for detecting airglow gravity waves based on multi-stage filtering and deep learning. The method comprises the following steps: after the star difference of adjacent airglow images is removed, the background trend is extracted by median filtering and Gaussian filtering in turn, and an enhanced image is obtained by geographic projection and adaptive stretching; after the enhanced image is added with a Kaiser window, a cover image is obtained by multi-scale Gabor filtering; a gravity wave frame is input into a convolutional neural network for detection; the current frame region is intercepted by an extended frame, and a windowed Fourier transform is performed to obtain an amplitude spectrum; meanwhile, the group velocity is calculated by using cross-correlation matching; the peak value with the smallest angle with the group velocity direction is selected in the amplitude spectrum to calculate the wavelength and direction; and the group velocity direction is corrected according to the relationship between the phase velocity direction and the group velocity direction. The present application solves the problem of automatic recognition of weak airglow signals, and realizes high-precision automatic detection of gravity waves and multi-parameter quantization.

The invention relates to an MMC valve electrical stress equivalent calculation method and device and a storage medium. The method comprises the steps that S1, time domain waveforms of bridge arm currents of a flexible DC converter valve under all working conditions are obtained based on electromagnetic transient simulation; s2, selecting the time domain waveform of any phase of bridge arm current, performing windowing Fourier transform in a preset time window to obtain a frequency spectrum component, and further extracting a direct current component and a fundamental frequency alternating current component; s3, drawing an electrical stress curve; s4, respectively carrying out statistics on a first characteristic value representing the electrical stress level of the direct-current component and a second characteristic value representing the electrical stress level of the fundamental-frequency alternating-current component based on the electrical stress curve under each working condition; and S5, obtaining a test direct current value and a test alternating current value in combination with the safety coefficient. Compared with the prior art, the electrical stress requirement of the flexible direct current converter valve is accurately quantified from the operating condition of the system under the condition of not depending on a large-scale physical test.

The application discloses a target harmonic signal complex frequency estimation method based on a frequency domain least square, and belongs to the technical field of signal processing, and comprises the following steps: acquiring a geophysical observation time sequence containing a target harmonic signal; acquiring an initial power spectrum by adopting a windowed Fourier transform, and identifying a spectral peak of the target harmonic signal; selecting power spectrum values at multiple frequency points near the target spectral peak, and obtaining a complex frequency parameter of the target harmonic signal by utilizing a linear least square fitting; and adopting zero padding extension to increase effective frequency points of the power spectrum, and improving estimation accuracy of the complex frequency parameter by a multiple least square. The application combines the Fourier transform and the linear least square fitting, can realize high-precision estimation of the complex frequency of the target harmonic signal, is simple, efficient and easy to realize, has been successfully applied to scenes such as extraction of earth normal mode frequencies and inversion of ocean tide constituent parameters, and can be extended to communication, biomedical and other arbitrary time series signal analysis.

The invention discloses an image segmentation-based time-varying structure modal frequency automatic extraction method, and particularly relates to the field of time-varying structure modal frequency extraction. Windowing Fourier transform of a localized window function is introduced into noise-containing vibration response data; therefore, a noise-containing time-frequency spectrum image containing frequency component distribution of the time-varying structure response signal at different moments and corresponding amplitude characteristics is obtained; determining the position of a modal ridge line of the preprocessed time-frequency spectrum image and generating an annotation area so as to obtain an annotation data set, and training the annotation data set as a data set of a model to realize automatic segmentation of the ridge line area in the time-frequency spectrum image; performing short-time Fourier transform on the preprocessed vibration response signal under the excitation action to obtain a real time-varying structure time-frequency spectrogram; the preprocessed real time-varying structure time-frequency spectrogram is input into the model, then the model recognizes a ridge line area of the real time-varying structure modal frequency and outputs a segmentation result, the segmentation result is post-processed, and finally the time-varying structure modal frequency is obtained.

This invention discloses a method and system for locating cable defects by fusing reflection coefficient and impedance spectrum, relating to the field of insulation condition diagnosis and assessment technology for power equipment. The method includes: acquiring reflection coefficient spectrum data and impedance spectrum data from the cable's head end; extracting the imaginary part of the reflection coefficient spectrum and the amplitude information of the impedance spectrum and fusing them to obtain fused spectrum data; performing localization processing on the reflection coefficient spectrum, impedance spectrum, and fused spectrum based on windowed Fourier transform to construct a local defect diagnosis function; and analyzing the diagnosis curve to determine the defect location and severity. This invention significantly improves the identification accuracy of the location pulse by coherently enhancing defect information through spectrum fusion, suppressing background fluctuations at non-defect locations. It has advantages such as a location error of less than 0.3%, strong anti-interference ability, and low misjudgment rate, making it suitable for efficient on-site fault detection of power cables.

The invention discloses a method for automatically identifying PC2 geomagnetic pulsation, electronic equipment and a computer storage medium, and the method comprises the steps: obtaining magnetotelluric (MT) time series data containing magnetic storm data, carrying out the split-window Fourier transform of electromagnetic field components, and obtaining a frequency spectrum array of each electromagnetic field component in a frequency domain; calculating data quality evaluation parameters based on the spectrum array, wherein the data quality evaluation parameters comprise electromagnetic field linearity, a phase difference between an electric field and a magnetic field, and an amplitude of an electromagnetic field spectrum as an energy parameter; and according to the high-quality data type related to the magnetic storm, determining the distribution characteristic of each parameter of the high-quality data of the measuring point. The geomagnetic pulsation event is automatically detected by identifying MT dead band high-quality data, widely distributed MT observation stations are converted into a geomagnetic pulsation monitoring network, existing infrastructures are fully utilized, and the space weather monitoring cost is reduced.