39 results about "Window function" patented technology

This invention relates to a method for extracting guided wavenumbers in variable thickness structures, belonging to the field of nondestructive testing technology. It utilizes an excitation signal to generate guided wave signals on the surface of the object under test. Based on a set window function and a set window length, the two-dimensional wavefield signal obtained by sampling the guided wave signal is divided into multiple local wavefield signals. A short-space Fourier transform is then performed on each local wavefield signal to obtain the amplitude-frequency-wavenumber array corresponding to each local space. A frequency range is then selected by summing the amplitude-frequency-wavenumber arrays of each local space, using the center frequency of the excitation signal as the midpoint. The weighted average wavenumber of each frequency point within the selected frequency range is calculated using the amplitude corresponding to the wavenumber sequence at each frequency point as the weight. The mean of the sum of the weighted average wavenumbers at each frequency point is then used as the wavenumber corresponding to the center position of each local signal space, and these values ​​are sequentially spliced ​​to obtain the wavenumber curve of the guided wave signal. This method solves the problem in existing technologies where the obtained guided wavenumbers cannot accurately reflect the thickness changes of variable thickness structures.

The application discloses a method for sidelobe suppression of single-bit quantization Chirp signal, and the main technical content of the method comprises sidelobe suppression of single-bit quantization Chirp signal based on a convolution window function. The technical content performs sidelobe suppression through the following steps: step S1, generating a Chirp echo signal; step S2, single-bit quantization of the Chirp signal; step S3, single-bit quantization of a Chirp signal matching filter and adding a convolution window; and step S4, pulse compression of the single-bit quantization Chirp signal. The application can achieve a good compromise between quantization order and pulse compression effect, single-bit quantization can reduce quantization complexity to the maximum extent, and the sidelobe suppression method based on the convolution window function can effectively solve the problem of the decrease of the main sidelobe ratio caused by single-bit quantization. For Chirp signals and other radar signals with large time-bandwidth product, the application can improve the pulse compression effect, improve the range resolution of the radar system, and has certain reference significance for improved design in radar engineering technology.

The application discloses a window function optimization-based windowed interpolation FFT harmonic analysis method and system, which comprises the following steps: performing equal-interval synchronous sampling on a power grid signal to be measured; constructing a multi-objective optimization model of an M-term cosine combination window, and setting a constraint condition; performing iterative optimization on the constructed multi-objective optimization model to generate a time-domain sequence of a customized optimal window function; performing p-order self-convolution processing on the time-domain sequence of the optimal customized window function to obtain a self-convolution optimization window; performing point-by-point windowing processing on a discrete sampling sequence according to the time-domain sequence of the self-convolution optimization window, performing fast Fourier transform on the windowed sequence to obtain a discrete frequency spectrum of the signal, locating frequency spectrum peaks corresponding to each harmonic / sub-harmonic in the discrete frequency spectrum, extracting four characteristic spectral lines near the peaks, constructing a weighted ratio variable, and solving a frequency offset through a pre-fitted odd polynomial. The application can solve the problem of the fence effect, and improve the spectrum leakage suppression capability and the anti-interference performance.

The application discloses a trigonometric function window generating method based on DSP, which comprises the following steps: converting the cosine term of the trigonometric function window into the n-th power form of the complex exponential fixed value based on the Euler formula; after the program initializes the calculation of the fixed value, generating the complex exponential term of each point sequence by recursive multiplication and storing the complex exponential term in the first-level storage space of the DSP; then, the SIMD parallel operation is realized by using the in-line function of the DSP, the first half of the window function values are calculated and stored; the first half of the window function values are inversely symmetrical copied to generate the second half of the window function values; finally, the hardware adaptive memory allocation is completed by combining the hierarchical storage architecture of the DSP, the stack is allocated to the first-level storage space, and the window function generation is completed by summarizing the data. The application greatly reduces the operation amount and the storage occupation, guarantees the calculation precision, deeply adapts to the hardware characteristics of the DSP, can efficiently generate the Hanning, Hamming and Blackman trigonometric function windows, and meets the real-time and high-precision requirements of the signal processing with large bandwidth and high sampling rate.

This invention provides a method for preprocessing and classifying satellite photometric curve data. The method includes: converting phase angle-magnitude curves with discontinuous observations and uneven sampling frequencies into fixed-dimensional window function feature vectors using a frame-segmentation and windowing preprocessing strategy; employing a random erasure data augmentation strategy on these window function feature vectors to generate different photometric curve feature vectors through multiple random erasures while simulating phase observation gaps; performing positional encoding of the phase angle features on the photometric curve feature vectors to obtain photometric features containing phase information; constructing query vectors, index vectors, and key value vectors using a transformer model to extract global features; and classifying the photometric curve feature vectors using a fully connected layer. This method effectively captures both local and global feature information of the photometric curves, exhibiting superior performance compared to one-dimensional convolutional neural networks.

This invention discloses an AI interaction system and method with multi-window task splitting and real-time task response. By designing multiple independent AI dialogue input windows, each pre-bound with specific functional instructions (such as analysis or memorization), the system can directly trigger the corresponding function after the user inputs task content, achieving synchronous execution of input and instructions, eliminating the redundant steps of the traditional "input-select instruction-execution" process. The multiple AI dialogue input windows are functionally independent and support parallel operation, avoiding task conflicts and significantly improving multi-task processing efficiency. Clear window function binding reduces the risk of errors in semantic ambiguity parsing, ensuring the accuracy of task execution. This invention overcomes the limitations of existing single-window multi-instruction interaction modes, achieving significant improvements in operational efficiency, interactive experience, task accuracy, and flexibility.

This application discloses a method and system for compressing and reconstructing borehole elastic wave signals based on segmented windowing and sparse coding, relating to the field of geophysical signal processing. The method includes segmenting the original borehole elastic wave time-series signal into multiple signal segments; applying a combined Hann window function to each signal segment for windowing and selecting effective signal segments; obtaining the sparse coefficient vector and atom index corresponding to each effective signal segment based on a pre-built dictionary; calculating the average sparse coefficient vector of all effective signal segments to obtain the average sparsity; reconstructing any effective signal segment according to the average sparsity to obtain a reconstructed effective signal segment; and performing inverse weighting processing using the Hann window function corresponding to the reconstructed effective signal segment to obtain the final reconstructed signal. This application achieves efficient compression and high-fidelity reconstruction of borehole elastic wave time-series signals.

This invention discloses a method for extracting transformer vibration features based on multi-point collaborative sampling and time-frequency matrix reconstruction, comprising the following steps: S1. Establishing a finite element simulation model based on the transformer structure and acquiring original vibration signals from multiple locations on the surface of the tank; S2. Performing normalization preprocessing on the original vibration signals and dividing them into multiple data samples through sliding window sampling; S3. Multiplying each data sample by a window function, calculating the Fourier transform of each window, and constructing the short-time Fourier transform time-frequency matrix of the vibration signal by spectral splicing; S4. Based on the short-time Fourier transform time-frequency matrix, calculating the instantaneous frequency after signal compression, and mapping pseudo-frequency components within a set width to the instantaneous frequency according to the mapping relationship, thereby obtaining a high-resolution time-frequency matrix reconstructed by synchronous Fourier compression transform. This invention has the advantages of high feature extraction accuracy and high reliability.

The present application relates to radar target detection and identification technical field, especially in kind, a kind of dual-rotor micro-doppler feature extraction method and system, first to the echo sequence of dual-rotor unmanned aerial vehicle carries out the micro short-time Fourier transform, obtains initial amplitude spectrum matrix;Secondly, according to initial amplitude spectrum matrix, calculate the gentle loss function of party damage;Then using gradient descent method, according to the window length of time window function in gentle party damage loss function adaptive closed loop iteration optimization, output the optimal window length of time window function;Finally, according to the optimal window length, determine the time-frequency feature map spectrum.The present application parameterizes and differentiable time-frequency transform process, uses gradient descent adaptive to find optimal window length, does not change analytical bandwidth with frequency, but is matched with global optimal bandwidth to target characteristic frequency, solves the problem that resolution and cross term cannot be considered in traditional method in dual-rotor signal processing.

The disclosure relates to a remapping unit (100) configured to remap a time-continuous signal to one or more time-frequency space coefficients, the remapping unit comprising: a transform unit (110) configured to receive the time-continuous signal and a frequency band of interest, and configured to multiply the received time-continuous signal with a window function having a window size, the window function comprising one or more basis functions; an integrating unit (120) configured to integrate the window function with infinitesimally small increments in the window size to obtain an integral; and wherein the transform unit (110) is configured to remap the time continuous signal to one or more time frequency space coefficients based on the integral. The disclosure further relates to a receiver, an inverse remapping unit, a transmitter, systems, a repeater, methods, computer program products, and a non-transitory computer-readable storage medium.

The present application relates to a kind of wide frequency power grid harmonic fast extraction method based on multiscale collaborative measurement, belong to the field of power system harmonic analysis, including: construct multi-window parallel data buffer, utilize smooth transition function dynamically calculate the confidence weight of each window;Adopt adaptive window function strategy to load rectangular window and Blackman window respectively, and preliminary obtain full-band spectrum parameter in combination with zero padding FFT, introduce phase alignment algorithm based on time zero point to eliminate the phase drift caused by non-synchronous sampling;For random interference, use stability filtering mechanism to carry out effectiveness check.The present application realizes the unity of wide frequency harmonic transient fast locking and steady-state high-precision measurement by organically combining multi-window parallel processing with S-shaped smooth transition mechanism, significantly improves the dynamic adaptability and anti-noise reliability of measurement, and provides reliable technical foundation for new type power system wide frequency oscillation monitoring and control.

The invention relates to a method of determining a perceptual impact of an amount of echo or an amount of reverberation in a degraded audio signal on a perceptual quality of the degraded audio signal, wherein the degraded audio signal is received from an audio transmission system, the degraded audio signal being obtained by a transmission of a reference audio signal by the audio transmission system to provide the degraded audio signal. The method comprises performing a windowing operation on the degraded audio signal and the reference audio signal by multiplying the degraded audio signal and the reference audio signal with a window function to produce degraded digital audio samples and reference digital audio samples. A local estimate of the amount of echo or the amount of reverberation is determined based on the degraded digital audio samples and the reference digital audio samples.

The application belongs to the technical field of river surface flow velocity measurement, and discloses a method for predicting water flow surface flow velocity based on improved RAFT optical flow. Firstly, in the feature extraction stage, the feature descriptor information output by the SuperPoint network is fused, the representation ability of key features is strengthened, the reliability of feature matching is improved, and problems such as ambiguous optical flow estimation results are solved. Secondly, after correlation calculation, an evaluation module is introduced, the evaluation mode is used to calculate a matching quality evaluation index according to a 4D correlation body and a context feature map, and whether to enable a moving window function is judged according to the size of the evaluation index and a preset threshold value, so that the 4D correlation body is kept or updated. By introducing the moving window function, the problem of false features caused by optical flow discontinuity and noise in the water flow scene is solved, and the evaluation mechanism is constructed to dynamically decide the enabling time of the moving window function, so that the balance between the estimation accuracy and efficiency of the optical flow is realized.

The present application relates to the technical field of audio sound calibration, and discloses a room sound calibration method based on a mid-frequency reverberation time and related equipment, which is used for improving the accuracy of sound calibration results. The room sound calibration method based on the mid-frequency reverberation time comprises the following steps: obtaining a room impulse response of a target room and calculating a mid-frequency reverberation time; determining a recommended window length of a frequency-dependent window by querying a predefined mapping relationship according to the mid-frequency reverberation time, the mapping relationship being established based on the acoustic correlation between the room reverberation time and the analysis window length; determining an actual window length actually applied based on the recommended window length and in combination with a user setting mode; performing time-domain windowing on the room impulse response according to the actual window length and frequency-dependent transfer function estimation processing to obtain a window function weighted transfer function estimation; and generating filter calibration coefficients based on the transfer function estimation and applying the filter calibration coefficients to perform audio calibration.

The application provides an adaptive order spectrum analysis method for wind generator transmission chain fault diagnosis, and relates to the field of rotating machinery state monitoring and fault diagnosis. The method comprises the following steps: step S1, data acquisition and preprocessing, obtaining vibration acceleration signals and rotation speed pulse signals; step S2, performing adaptive instantaneous phase calculation on the rotation speed pulse signals to obtain an accurate instantaneous phase curve; step S3, based on the accurate instantaneous phase curve, performing angular domain resampling on the vibration acceleration signals to obtain an angular domain stationary signal sequence; step S4, performing autocorrelation analysis on the angular domain stationary signal sequence to adaptively select and generate an optimal window function sequence; and step S5, using the optimal window function sequence to perform order spectrum calculation on the angular domain stationary signal sequence to output the order spectrum. The adaptive order spectrum analysis method for wind generator transmission chain fault diagnosis is used, and the accuracy and robustness of vibration signal order analysis are enhanced.

This application provides a dynamic parameter configuration method based on adaptive signal feature analysis, relating to the field of control or regulation system technology, including the following steps: obtaining a continuous digital sampling sequence and performing main characteristic frequency tracking to obtain the main characteristic frequency of the currently running signal, and detecting whether there are interfering characteristic frequencies; calculating an adaptive analysis window length based on the main characteristic frequency and interfering characteristic frequencies, which is an integer multiple of the period corresponding to the main characteristic frequency; and is also an integer multiple of the period corresponding to each interfering characteristic frequency; extracting data segments of the analysis window length from the digital sampling sequence and resampling them to convert them into a fixed data point sequence; applying a window function to the fixed data point sequence and performing a spectrum transformation to obtain an accurate spectrum including the main characteristic frequency component and the interfering characteristic frequency component; and obtaining a target configuration for adjusting the execution parameters of the controlled unit based on the main interfering frequency component identified in the accurate spectrum.

This invention discloses a method for characterizing deep carbonate reservoirs based on statistical level compression transformation. The method includes: first, inputting the seismic signal to be analyzed, selecting an analysis window function and setting the Taylor expansion order, and constructing a time filter. After calculating the short-time Fourier transform and weighted transform based on the frequency domain window function, convolution filtering is performed using the time filter to construct autocorrelation and cross-correlation statistics. Based on this, a system of linear equations is established to solve for the statistical group delay estimate, and then the short-time Fourier transform coefficients are rearranged in time and frequency to obtain the statistical level compression transformation result. The seismic data is then subjected to time-frequency transformation using the above method to obtain the statistical level compression transformation result. From the time spectra of different seismic traces obtained by this transformation, time series corresponding to constant frequencies are extracted and synthesized into profile maps to characterize reservoir reflection interfaces and delineate reservoir boundaries.

The application provides a loss measurement method and device based on frequency domain peak-valley difference and quadratic envelope compensation, acquires a time domain signal of fiber ring cavity ring-down, establishes an ideal exponential pulse attenuation model, performs frequency domain conversion and amplitude spectrum construction, analyzes and defines the peak-valley difference of frequency domain harmonic peak value and valley value characteristics, introduces a window function to truncate the pulse sequence, performs frequency domain response analysis, performs quadratic polynomial fitting of the frequency domain amplitude spectrum envelope, and performs spectrum compensation processing; without relying on complex microwave devices such as electro-optic modulators and network analyzers, the method can be directly integrated into an existing time domain FLRD measurement system, reduces the system hardware cost and implementation difficulty, and has a good engineering application prospect.

This application discloses an adaptive 3D Gaussian splash dynamic scene reconstruction method based on local time slice anchor points, belonging to the field of 3D reconstruction technology. The method includes: acquiring multi-view video and initial point cloud data; initializing standardized anchor points based on the initial point cloud; deriving 3D Gaussian primitives from the standardized anchor points to construct an initial representation of the dynamic scene; constructing time slice anchor points by introducing time parameters based on the standardized anchor points; limiting the effective interval through a lifecycle window function; comparing the model-rendered image with the real image; iteratively updating the model parameters; periodically calculating the image residual; locating the error region; and determining candidate optimization positions through back projection; selecting the anchor point to be optimized through an effective nearest neighbor matching method; executing a coarse-to-fine time segmentation strategy; modulating the effective opacity of the Gaussian primitives using relevant sets; performing screen-space Gaussian splash rendering; iteratively updating the parameters; and outputting a new perspective dynamic rendering video. This application can achieve high-fidelity reconstruction of complex dynamic scenes.

The application relates to the technical field of communication engineering and radio wave propagation, and discloses a communication system simulation optimization method and system based on radio wave propagation prediction, which aims at the problem of insufficient near-field calculation accuracy of the existing three-dimensional parabolic equation method when simulating an unmanned aerial vehicle air-ground communication link, divides a three-dimensional simulation space into a near-field MLFMM calculation region and a far-field HPE calculation region, accurately solves the near-field region by using a multi-layer fast multipole algorithm, and smoothes the result by window function processing and couples the result to the far-field region, finally obtains full-link radio wave propagation field distribution data, evaluates communication quality according to the field distribution data, and automatically adjusts system parameters for iterative optimization when the indicators are not met, until a design scheme meeting the requirements is output. The method effectively balances the near-field calculation accuracy and the far-field calculation efficiency, significantly improves the accuracy of path loss prediction, and provides an efficient tool for the design and automatic optimization of an unmanned aerial vehicle communication system in a complex environment.

This invention relates to the field of power system parameter monitoring technology and discloses a high-precision analysis method for electrical parameters based on a lightweight DSP algorithm, comprising the following steps: sampling and data buffering, lightweight DSP core processing, electrical parameter output, and code-level optimization. This invention suppresses spectral leakage through integer-cycle sampling combined with window functions, achieving harmonic measurement accuracy of ±0.5%. After Kalman filtering, data fluctuation is reduced by 80%, and steady-state accuracy is improved to within 0.1%, enabling high-precision measurement. Simultaneously, downsampling and integer operations reduce computational load, and code-level optimization keeps CPU utilization ≤15%, allowing it to run on low-cost MCUs such as the STM32F407.

This invention discloses a method and system for enhancing ultra-high resolution low-light images based on block overlap inference, belonging to the field of image processing technology. The method segments the ultra-high resolution image into sub-blocks with overlapping regions, and uses a deep learning model based on the UNet architecture to independently enhance each sub-block. The model incorporates a Feature Linear Modulation (FiLM) module to adaptively modulate the underlying features using target brightness parameters. It calculates the ratio of the local average brightness of the sub-block to the global average brightness, and uses logarithmic scaling to determine the local target brightness, ensuring brightness continuity. The overlapping regions are progressively fused using a cosine window function to eliminate block artifacts. This invention solves the problems of memory limitations, block artifacts, and brightness discontinuities in low-light enhancement of ultra-high resolution images, achieving high-quality real-time enhancement, and is suitable for scenarios such as wide-area monitoring and astronomical observation.

This application discloses a method, apparatus, device, and storage medium for generating order spectra, belonging to the field of fault diagnosis for rotating machinery. Under variable speed conditions, this application can generate high-quality order spectra. Specifically, this application converts the time-domain signal into an angular-domain signal through angular-domain resampling, and then performs time-frequency analysis on the angular-domain signal. This processing eliminates the influence of speed variations on order analysis. After time-frequency analysis of the angular-domain signal, a high-quality order spectra can be generated without energy smearing, facilitating fault diagnosis of rotating machinery by engineers. Furthermore, this application no longer relies on experience to select the window length, but determines the window length based on the equivalent noise bandwidth of the window function and the target order resolution. Because the method of determining the window length is more reasonable, the generated order spectra have higher quality stability.

The application discloses a machining center FANUC coordinate system protection method, comprising the following steps: step S1: dividing the coordinate system parameters according to the importance degree to divide the protection level, switching the parameter write protection control right to the PMC signal through the system parameter setting, and writing the permission judgment logic in the PMC ladder diagram; step S2: constructing the background parameter monitoring mechanism based on the macro program interruption function and the PMC window function, periodically reading the current value of each level parameter and comparing with the reference value; step S3: triggering the differential early warning and processing mechanism according to the safety level of the modified parameter, and automatically executing the parameter backup after the authorized modification confirmation; step S4: establishing the log buffer area in the PMC, and real-time recording the coordinate system related operation behavior and storing in the non-volatile area. The application can cover more than 90% of the FANUC system machining center on the market, and can be used for self-owned factory equipment batch upgrading, and can also carry out technical service, technical consultation and technology transfer.

This invention belongs to the field of river surface velocity measurement technology and discloses a method for predicting water surface velocity based on improved RAFT optical flow. Firstly, this invention integrates feature descriptor information output by the SuperPoint network during the feature extraction stage. By strengthening the representational ability of key features, it improves the reliability of feature matching and solves problems such as ambiguity in optical flow estimation results. Secondly, this invention introduces an evaluation module after correlation calculation. This evaluation module calculates the matching quality evaluation index based on the 4D correlators and context feature maps, and determines whether to enable the moving window function based on its magnitude with a preset threshold, thereby maintaining or updating the 4D correlators. By introducing the moving window function, it solves the problems of optical flow discontinuity and false features caused by noise in water flow scenarios. Simultaneously, it constructs an evaluation mechanism to dynamically decide when to enable the moving window function, achieving a balance between the accuracy and efficiency of optical flow estimation.