49 results about "Frequency axis" patented technology

The invention relates to a bridge structure vibration monitoring and analysis method based on artificial intelligence, and the method specifically comprises the following steps: setting an acceleration sensor network at a key part of a bridge, collecting and marking a vibration signal sample, and forming a data set; a high-resolution time-frequency matrix of sample adaptive optimal kernel time-frequency distribution is calculated, a damage sensitive resonance frequency band is positioned according to spectrum kurtosis, and the time-frequency matrix is enhanced by the resonance frequency band subjected to adaptive gain enhancement; dividing a matrix frequency axis multi-scale binary tree, calculating and normalizing sub-band average energy, quantifying energy distribution uniformity through information entropy, and splicing multi-scale entropy values into feature vectors; then constructing and training a bridge detection data model; and finally, preprocessing new data, inputting the preprocessed new data into the trained model, and automatically analyzing to obtain a bridge health monitoring result. Through time-frequency optimization, multi-scale entropy and deep learning technologies, the problems of large noise, difficult feature extraction and low automation and accuracy of traditional monitoring can be solved.

The invention discloses a mirror image rejection method and device based on spectrum entropy, and belongs to the technical field of radio frequency signal processing. Multiple groups of frequency spectrums are collected by moving a local oscillator, the frequency spectrums are mapped to a unified reference frequency axis to achieve frequency alignment, a spectrum entropy sequence of the same frequency point after alignment is calculated, and the problem that the spectrum entropy fluctuation of the same frequency point is large due to nonlinear deviation of the local oscillator frequency of a mirror image signal is solved. And accurate identification and suppression of the mirror image signal are realized due to the difference of spectrum entropy stability caused by linear offset of the useful signal. According to the method, multiple groups of frequency spectrums are mapped to a unified reference axis through frequency alignment, high-precision mirror image suppression is effectively realized by utilizing the characteristics of large fluctuation of mirror image signals and stable useful signals in a spectrum entropy sequence of the same frequency point, the distinguishing capability in a complex scene is improved, and the problems of high cost and insufficient robustness of an existing mirror image suppression method are solved.

The invention relates to the technical field of power equipment state monitoring, and discloses a partial discharge detection method and system based on synchronous compression wavelet-synchronous extrusion. The method comprises the following steps: preprocessing a partial discharge signal; calculating a coefficient through continuous wavelet transform and estimating an instantaneous frequency and a chirp rate; synchronous compression is carried out to compensate the phase, and scale remarking is carried out; energy is reallocated to a frequency axis through synchronous extrusion, and a high-aggregation-degree time-frequency diagram is generated; extracting a peak domain based on the saliency spectrum, demodulating along a ridge line, and estimating event parameters; and finally, robust judgment and auditing output are completed by using the joint statistics. According to the method, the sensitivity and robustness of partial discharge signal detection under the conditions of low signal-to-noise ratio and strong interference are remarkably improved.

The invention relates to the technical field of impedance measurement, in particular to an impedance measurement method and system for a common-mode inductor, and the method comprises the steps: obtaining voltage and current signals of the common-mode inductor in a test circuit, and obtaining frequency domain response atlas data containing impedance characteristics through time-frequency transformation; carrying out non-linear segmentation division on the frequency axis to form a plurality of frequency segmentation regions; extracting the phase amplitude of each segmented region, carrying out clustering segmentation, and recognizing an effective impedance frequency band; analyzing phase synchronization characteristics in the effective impedance section, and determining a common-mode resonant frequency point through clustering analysis; and fusing multi-section frequency region division, effective impedance section and resonance point information to finish accurate measurement of the impedance characteristic of the common-mode inductor. According to the method, through non-linear scanning and phase information joint analysis, the recognition precision of impedance response key characteristics in a broadband range is improved, the capturing capacity of parasitic parameters and resonance behaviors is enhanced, and efficient and high-precision comprehensive evaluation of the impedance characteristics of the common-mode inductor is achieved.

This application proposes a high-precision detection method and device for stationary human targets based on a radar life detector. The method involves performing an inverse Fourier transform on the radar's fast time to convert the frequency axis into the range axis, iteratively updating the low-rank matrix and the sparse matrix, updating the dual variables and modifying the penalty parameters, and obtaining the separation result between the target and the background after convergence. The background information is stored in the low-rank matrix, while the signal containing life characteristic information is stored in the sparse matrix, thereby achieving high-precision detection of stationary human targets.

The invention provides a multi-modulation signal robust identification method based on a time-frequency diagram and data enhancement. Original baseband signals of the traditional modulation mode and the novel modulation mode are generated and preprocessed; performing data set division according to a double sampling mode; performing STFT on the data to generate a time-frequency graph; performing enhancement operations of time axis offset, frequency axis offset, noise injection and tiny rotation on the time-frequency graph of the training set; a ResNet-18 model adaptive to single channel input is constructed; and training the model and carrying out a performance test of unknown signal modulation mode identification. According to the method, the novel data set comprising a traditional modulation mode and an emerging modulation technology is constructed, the defect that most of the current modulation data sets are the traditional modulation mode is overcome, a data basis closer to a future communication scene is provided for modulation recognition in a complex scene, multi-dimensional enhancement is performed on data, data diversity is improved, and the method is suitable for being applied to modulation recognition in a complex scene. The model generalization ability is significantly improved, and the identification precision of the modulation signal is also effectively improved.

The invention relates to the technical field of oil and gas exploration and development, and particularly discloses a robust mixed norm constraint high-dimensional seismic data reconstruction method and device, and the method comprises the steps: carrying out the Fourier transformation of five-dimensional data along a time axis, and obtaining the Fourier transformation data; unfolding 4D data of each frequency slice of the Fourier transform data along a mode-(m, n) to obtain a near-square matrix; a non-convex Frobenius / Nuclear mixed norm and L1 norm combined regularization constraint is applied to the near-square matrix, and a target functional of observation seismic data and reconstruction data is constructed; and alternately solving the target functional by adopting an ADMM algorithm, and carrying out inverse Fourier transform on a solving result along a frequency axis. According to the method, a high-dimensional tensor completion method under the robust Frobenius / Nuclear mixed norm constraint is introduced, accurate representation of nonlinear high-dimensional seismic data is achieved, the seismic data reconstruction and denoising precision is improved, and therefore regularized reconstruction and abnormal noise suppression of the seismic data with the low signal-to-noise ratio are achieved.

The application discloses a GIS device partial discharge wide-frequency electromagnetic signal characteristic analysis method and system, and relates to the technical field of partial discharge detection. The method comprises the following steps: collecting a GIS partial discharge wide-frequency electromagnetic signal, and adopting wavelet transform processing to obtain a time-frequency distribution matrix; uniformly dividing the time-frequency distribution matrix according to a frequency axis to obtain initial sub-frequency bands; calculating the effectiveness indexes of the sub-frequency bands and adaptively aggregating the sub-frequency bands to obtain candidate characteristic intervals; and performing collaborative contribution degree analysis on the candidate characteristic intervals to obtain optimal characteristic intervals. The technical problem that, in the existing GIS partial discharge wide-frequency electromagnetic signal characteristic extraction process, frequency band division relies on experience and lacks an adaptive optimization mechanism, resulting in inaccurate characteristic interval selection and weak anti-interference capability is solved, and the technical effect that the accuracy and anti-interference capability of partial discharge characteristic extraction are improved through adaptive sub-frequency band division of the wide-frequency electromagnetic signal and collaborative analysis of the characteristic intervals is achieved.

The application discloses a kind of railway bed moisture content quantitative detection methods based on low high-frequency energy ratio, comprising: setting multiple transverse detection channels to collect ground penetrating radar signal;The radar signal of each transverse detection channel is continuously wavelet transformed, and the frequency axis in the time-frequency transform result is divided into low frequency band and high frequency band according to preset boundary frequency, and the low high-frequency energy ratio is calculated;The low high-frequency energy ratio mean of each transverse detection channel is calculated in each test area, and the low high-frequency energy ratio mean of multiple transverse detection channels in multiple test areas forms joint sample;According to joint sample, regression model for representing the nonlinear mapping relationship between water content severity index and low high-frequency energy ratio is constructed;The digital determination threshold of different water content grades is calculated according to regression model using interclass geometric midpoint method, establishes bed moisture state grading standard, and outputs moisture state grade.The application can realize accurate quantitative detection and grading of railway bed moisture content.

The invention discloses a method and a system for generating a tunable flat-topped spectrum based on a Flokey singular point. The method comprises the following steps: forming two types of supermodes alternately arranged on a frequency axis by using a pair of coupled optical ring resonators; applying periodic dynamic complex modulation including real and imaginary components to the resonator; configuring the modulation frequency to be matched with the super-mode interval so as to construct a periodically quenched non-Hermite frequency lattice on the synthetic frequency dimension; and adjusting modulation parameters, and driving the quasi-energy band of the crystal lattice to present a linear dispersion relationship at the singular point, thereby generating the flat-topped spectrum. According to the method, the intensity and the broadening speed of the flat-topped spectrum are linearly controlled by adjusting the imaginary part modulation amplitude, and the flat-topped frequency comb formed by a single supermode is obtained by extracting signals at a specific moment in a modulation period. According to the method, flexible electric control tuning of the spectrum form, the broadening speed and the modal component is realized, the system can work under the weak non-Hermite condition, and the practicability and integration of the system are improved.

The application discloses a kind of wind power gear box fault diagnosis method, system, equipment and medium, it is related to fault detection technical field, including steps: the vibration signal of wind power gear box is collected, and the time-frequency diagram of vibration signal is obtained;Capsule feature tensor in time-frequency diagram is obtained, and a time-frequency two-dimensional network is constituted in space, and different convolution kernels are used to extract corresponding query tensor in time axis and frequency axis of time-frequency two-dimensional network;The dot product matching of corresponding query tensor and preset shared key-value pair is carried out respectively, the attention distribution of each query tensor is obtained, and the aggregation output in time axis and frequency axis direction is fused by attention distribution;Class activation mapping is carried out to aggregation output, determines the fault category of wind power gear box, and generates class activation map focusing on key time-frequency region by fault category, shows discrimination basis.The application can focus on key time-frequency region with clear physical meaning, significantly improve the discrimination transparency and engineering credibility of model.

The present invention provides an electromagnetic noise analysis device that: is capable of performing electromagnetic noise analysis of an arbitrary observation point on a circuit during electromagnetic noise analysis, of a frequency axis, that takes into consideration various operation conditions, such as current dependency and control, which have conventionally been difficult to express except by using a time axis; and is capable of achieving both shortening of analysis time and improvement of analysis accuracy. The present invention is characterized by comprising: a noise spectrum analysis unit for executing frequency axis noise analysis in which each switch is expressed by a voltage source or a current source of the frequency axis for an arbitrary observation point of a power conversion circuit in which at least two switches are connected between power sources; a voltage source / current source noise source parameter generation unit for generating a parameter table for expressing a switching operation by a voltage source or a current source of the frequency axis, the switching operation corresponding to an operation condition including the power source voltage, the gate resistance of each switch, or a current; a worst condition extraction unit for extracting a current amount and a phase relationship in which a noise amount can be a worst condition during an operation on the time axis of each switch as based on control; and a worst condition noise source model generation unit for setting a noise source parameter for the worst condition using an extraction result by the worst condition extraction unit.

The invention discloses a numerical control machine tool machining error modeling method and system, and the method comprises the steps: collecting temperature rise time sequence data at a key part of a main shaft, representing machining error frequency domain features through workpiece surface topography power spectral density (PSD), and constructing a thermal spectrum neural operator network model; and learning mapping between the temperature rise evolution and the PSD of the surface of the processed workpiece and outputting a prediction result of the PSD of the surface of the workpiece. The network adopts a four-stage structure of continuous time coding, frequency registration, optimal transmission measurement and energy calibration which are respectively used for adapting to non-uniform sampling and dynamic working conditions, modeling spectrum peak drift and frequency axis dislocation, depicting spectrum shape overall migration and local deformation, and ensuring PSD energy consistency through Parseval energy constraint. According to the method, intermediate frequency energy change, spectral peak drift and spectral shape distortion can be accurately described, interpretable support is provided for error traceability and process compensation, and precision and cross-working-condition generalization ability are improved.

The invention discloses a micro-motion exploration frequency dispersion curve extraction method, device and medium, and relates to the technical field of micro-motion exploration, and the method comprises the following steps: S1, calculating the average cross-correlation spectrum of each station pair according to the recorded data of a plurality of stations in an observation array; s2, aiming at the average cross-correlation spectrum of each station pair, identifying a first intersection point frequency of the average cross-correlation spectrum and a frequency axis; s3, based on the first intersection point frequency, performing piecewise fitting on the average cross-correlation spectrum to extract a phase velocity: for a frequency band not greater than the first intersection point frequency, performing fitting by adopting a zero-order Bessel function J0; and for a frequency band of which the frequency is greater than the frequency of the first intersection point, performing fitting by adopting a first-class zero-order Hankel function H0 (1). In a single method, the contradiction of artifact interference in a high frequency band and insufficient detection depth in a low frequency band in the prior art is overcome at the same time, the accuracy and reliability of frequency dispersion curve extraction under the sparse array condition are improved, and the detection depth of micro-motion exploration is effectively expanded.

The application relates to a kind of beam transverse operating point measurement method and device, method includes: in time sequence to Schottky signal sampling;Current frame power spectrum is obtained based on current frame data;Unified physical frequency axis under current frame target power spectrum is obtained based on current frame power spectrum;Adaptive smoothing filtering is carried out to obtain the smoothed target power spectrum of current frame;The frequency coordinate of the smoothed target power spectrum of current frame is normalized to dimensionless operating point coordinate to obtain the normalized power spectrum of current frame;The normalized power spectrum of current frame is resampled to obtain the resampled power spectrum of current frame;Determine the reference power spectrum of current frame and the reference transverse operating point of current frame;Determine the candidate transverse operating point of current frame;The reference transverse operating point and candidate transverse operating point of each frame in frame sequence are determined by current frame, the preceding several frames of the current frame, and the optimal estimation value of the transverse operating point of the current frame is determined.

The invention discloses a signal modulation method and system, and the method comprises the following steps: defining basic parameters of a signal, including a sampling rate, signal duration and a generation time vector; generating a plurality of signals through the basic parameters of the signals; random frequency offsets are added to the frequencies of the different modulation signals; by setting the length of a window time period, windows are moved to the open end position of a signal and the center position of the windows for windowing processing, and the overlapping proportion between the windows is set; fourier transform is carried out on each segment of sample signal to obtain a time-frequency analysis chart of each segment of sample signal, each segment of time-frequency analysis chart is sorted according to time, and a time-frequency characteristic chart of the underwater acoustic signal on a time-frequency axis is obtained; and extracting image features from the time-frequency feature map. According to the method, the one-dimensional signal is subjected to visualization processing through time-frequency analysis, and the two-dimensional image with obvious features is obtained, so that a subsequent neural network can conveniently extract the image features.

The application discloses a kind of non-stationary wind field high-efficiency simulation method based on dynamic interpolation setting point strategy, including determining simulation point number and its space position;According to the time-varying fluctuation power spectrum model of typhoon, the evolution power spectrum density matrix is calculated;Determine the time range and frequency range of simulation, and it is evenly dispersed into P and Q nodes on time axis and frequency axis respectively;In these discrete nodes, the interpolation node coordinates are selected by dynamic interpolation setting point strategy;By Cholesky decomposition to the evolution power spectrum at interpolation node, the spectral decomposition matrix at the place is obtained, then combined with interpolation method, the spectral decomposition matrix at non-interpolation node is obtained;According to the formula of harmonic superposition method, generate fluctuating wind speed sample.The application is based on classical harmonic superposition method, constructs a kind of dynamic interpolation setting point strategy, can accurately, conveniently select the interpolation node of frequency dimension, effectively reduces the amount of calculation, significantly improves simulation efficiency.

A radar device includes a transmitting antenna unit, a modulator, a receiving antenna unit, a receiver, and a processor. The transmitting antenna unit includes transmitting antennas. The modulator generates transmission signals respectively provided to the transmitting antennas by executing phase-shift keying through diverging the common signal into diverged signals having the number being equal to the number of the transmitting antennas and rotating respective phases of the diverged signals. The receiving antenna unit includes at least one receiving antenna. The receiver generates a received code of at least one received signal. The received code is acquired by encoding an appearance pattern of a peak of at least one received signal on a Doppler frequency axis. The processor generates information related to an object, according to the received code generated by the receiver. The modulator executes the phase-shift keying by using a linear block code as an assigned code.

This invention discloses a method and system for analyzing the characteristics of broadband electromagnetic signals of partial discharge in GIS equipment, relating to the field of partial discharge detection technology. The method includes: acquiring broadband electromagnetic signals of partial discharge from GIS equipment; processing these signals using wavelet transform to obtain a time-frequency distribution matrix; uniformly dividing the signal along the frequency axis to obtain initial sub-bands; calculating the effectiveness index of each sub-band and adaptively aggregating them to obtain candidate feature intervals; and performing a collaborative contribution analysis on the candidate feature intervals to obtain the preferred feature intervals. This invention solves the technical problem in existing GIS partial discharge broadband electromagnetic signal feature extraction processes where frequency band division relies on experience and lacks an adaptive optimization mechanism, leading to inaccurate feature interval selection and weak anti-interference capabilities. It achieves the technical effect of improving the accuracy and anti-interference capability of partial discharge feature extraction through adaptive sub-band division and collaborative analysis of feature intervals for broadband electromagnetic signals.

The present disclosure relates to an information processing device, a method, and a program that enable accurate generating of audio of an unlearned length without additional learning. An information processing device according to the present invention includes a prompt information input unit that receives a constraint condition for audio to be generated as prompt information, a noise generation unit that generates noise for a duration of the audio to be generated, a position embedding unit that embeds position information in the generated noise by using RoPE for a position in a temporal axis direction of the audio and embeds position information by using an absolute position for a position in a frequency axis direction thereof, and a diffusion transformer module that performs denoising processing of an embedded vector in which the position information is embedded. The technology according to the present disclosure can be applied to, for example, a generation task for generating natural and accurate audio from text prompt input.

A communication device (10, 47) according to an embodiment comprises a signal reception unit (1001), a time waveform operation unit (1002), a symbol timing generation unit (1007), an FFT unit (1004), a frequency waveform operation unit (1005), and a switching timing estimation unit (1006). The signal reception unit (1001) receives an OFDM signal and converts the OFDM signal to a baseband time axis waveform signal. The time waveform operation unit (1002) extracts part of the time axis waveform signal, which is output from the signal reception unit, and calculates a correlation value between the extracted signal and a known signal. The symbol timing generation unit (1007) outputs the timing at which the reception state is the best in a timing detection period that has been predetermined on the basis of the correlation value. The FFT unit (1004) performs FFT on a time axis waveform signal, which is output from the signal reception unit, on the basis of the timing. The frequency waveform operation unit (1005) extracts part of a frequency axis waveform signal after the FFT and calculates the degree of similarity between the extracted signal and a known signal. The switching timing estimation unit (1006) estimates, on the basis of the calculation result of the frequency waveform operation unit, the timing for switching between uplink communication and downlink communication in said device.

The invention discloses a method for dynamically judging a perimeter alarm threshold value of a detection cable based on double-cable coupling, which relates to the technical field of perimeter alarm of the detection cable, and comprises the following steps of: on the basis of a frequency spectrum jump criterion set, calculating a consistency curvature of a main frequency scatter point track of a double-cable coupling signal, analyzing a ratio of periodic repetition term density to energy return, and calculating a threshold value of the perimeter alarm threshold value of the detection cable; judging whether the detection cable passes through the electromagnetic reflection structure or not; and under the condition that the detection cable passes through the electromagnetic reflection structure, relative slippage distribution of signal channels corresponding to the first cable and the second cable in the double-cable coupling signal on a frequency axis is extracted, and a feature vector set for describing spectrum dislocation features of the double-cable coupling signal is generated. According to the invention, the problem of alarm determination misalignment caused by frequency spectrum dislocation when a double-cable coupling detection cable passes through an electromagnetic reflection structure is solved, and accurate determination and adaptive dynamic regulation and control of a perimeter alarm threshold in a complex structure environment are realized.

The application discloses a dynamic power quality disturbance signal detection method, device and medium, and the method steps comprise the following steps: S01, acquiring a dynamic power quality disturbance signal to be detected; S02, dividing a signal frequency band, and performing time-frequency analysis on the dynamic power quality disturbance signal by using an improved variable resolution S transform method; the improved variable resolution S transform method is an S transform based on a Gaussian window, and a Gaussian window scale factor is used to optimize the Gaussian window function; S03, performing a synchronous squeezing rearrangement operation on the improved variable resolution S transform result, so that energy components scattered in adjacent frequency intervals are aggregated to real frequency axis positions, and a time-frequency matrix after synchronous squeezing rearrangement is obtained; and S04, detecting signal components of the time-frequency matrix after synchronous squeezing rearrangement. The application can reduce energy diffusion and realize high-precision detection of non-stationary multi-scale complex dynamic power quality disturbance signals.

The invention discloses a frequency division rule-based spectrogram intelligent linkage display and interaction method and system, and relates to the technical field of radio monitoring. The method comprises the following steps: determining an effective frequency range in combination with user setting and equipment hardware limitation; establishing double display areas of a frequency spectrum view and a frequency business view, and realizing accurate alignment of frequency axes through equal-proportion linear mapping; collecting real-time FFT spectrum data to generate a spectrogram; loading a multi-source structured frequency division rule file, screening frequency bands and generating a graphical division table containing service information (the frequency bands are plotted into square blocks, overlapped frequency bands are displayed in parallel, and sub-channels are nested and presented); and operations such as double-view response parameter modification, zooming and dragging are synchronously updated, and intelligent alarm and diversified interaction are supported. According to the method, deep fusion of rules and spectrum signals is realized, the operation cost is reduced, the spectrum analysis efficiency and compliance judgment accuracy are improved, and multi-scene monitoring requirements are met.

The application discloses a bearing fault acoustic detection method and system based on fractional harmonic phase-locked amplification, acoustics signals of a target motor are acquired, the shaft rotation frequency of the motor shaft is measured in real time, and is synchronized to a fractional phase-locked loop; according to the geometric parameters of the bearing, the bearing fault characteristic frequency is calculated, the bearing fault characteristic frequency is a non-integer multiple of the shaft rotation frequency, a reference signal synchronized to the bearing fault characteristic frequency is generated through the fractional phase-locked loop, and the acquired acoustics signals and the generated reference signal are detected in a phase-sensitive manner through a phase-locked amplifier; specifically, the acoustics signals and the reference signal are quadrature demodulated to generate in-phase components and quadrature components, direct current components are extracted through low-pass filtering, and then the vibration amplitude and phase information corresponding to the bearing fault characteristic frequency are calculated; according to the comparison between the vibration amplitude and a preset baseline, harmonic consistency and phase stability, the bearing fault type and severity are determined.

The invention relates to the technical field of community medical treatment, and provides a community hearing screening method and system based on adaptive correction of environmental noise, and the method comprises the steps: obtaining a sound signal in a test environment, and carrying out the short-time Fourier transform, and obtaining a frequency domain spectrogram; for each key frequency, finding an index closest to the key frequency on a frequency axis in the frequency domain spectrogram, taking intensity values of the index in all time frames, calculating an average value, obtaining an original noise amplitude average value corresponding to the key frequency, carrying out smooth processing, calculating the average value, obtaining average noise, and if the intensity values are lower than a set value, outputting the average noise; if yes, determining that the testing environment is suitable for testing; and for each key frequency, playing pure tone, recording the minimum volume which can be heard by the subject as an initial baseline threshold value, performing noise correction to obtain a baseline threshold value after noise compensation, and if the baseline threshold value exceeds a clinical boundary value, determining that potential hearing loss is detected. And personal errors and environmental interference are obviously reduced.

The embodiment of the application discloses a kind of full electronic flexible line voltage regulator voltage control method, system, equipment and storage medium, method includes: the voltage and current signal of full electronic flexible line voltage regulator access point is collected, obtains the dynamic response characteristic of line under different frequency;Based on dynamic response characteristic, for each voltage regulator, frequency action potential function is constructed on frequency axis;According to frequency action potential function, the action interval on frequency axis is adaptively evolved to form stable action interval;Stable action interval is determined as the frequency domain responsibility interval of each voltage regulator, and the voltage regulation loop of corresponding frequency band in voltage regulator is activated or inhibited;When line operating state changes, trigger the re-evolution of action interval, and synchronously update the control parameter of voltage regulator to corresponding frequency band voltage regulation loop.The application realizes the natural division of labor and responsibility attribution uniqueness of multiple voltage regulators in frequency domain, and improves the regulation efficiency.

All data symbols used in data transmission of a modulated signal are precoded by switching between precoding matrices so that the precoding matrix used to precode each data symbol and the precoding matrices used to precode data symbols that are adjacent to the data symbol along the frequency axis and the time axis all differ. A modulated signal with such data symbols arranged therein is transmitted.

The present application belongs to the technical field of pile detection technology, and relates to a stress wave waveform period normalization method and a high-strain pile detection method. The method comprises the following steps: obtaining stress wave data of continuous multiple hammering, performing Fourier transform to obtain amplitude spectrum and phase spectrum, calculating actual period according to the amplitude spectrum; calculating theoretical period according to the pile length and wave velocity, constructing a correction factor according to the actual period and the theoretical period; scaling the frequency axis according to the correction factor and performing frequency domain interpolation, combining the phase spectrum to perform inverse Fourier transform to obtain a period normalized waveform; calculating the matching degree and the signal-to-noise ratio of the period normalized waveform, determining a weight coefficient according to the matching degree and the signal-to-noise ratio, performing weighted superposition according to the weight coefficient to obtain an enhanced waveform. The present application eliminates the waveform period drift caused by the cumulative deformation of the hammer pad through frequency domain phase spectrum correction, effectively enhances the coherence of the multiple hammering waveforms, and improves the signal-to-noise ratio of the superimposed waveform and the pile bottom reflection recognition rate.