226 results about "Analytic signal" patented technology

The invention relates to a fault diagnosis method of a rolling bearing under variable working conditions. The method comprises the steps of: extracting a characteristic vector of a signal by means of Hilbert-Huang conversion, carrying out EMD (Empirical Mode Decomposition) to a signal to obtain a plurality of IMFs (Intrinsic Mode Function), and selecting useful IMFs to carry out Hilbert conversion respectively to obtain analytic signals Hi(t) and taking envelopes respectively to form a characteristic vector w; then, carrying out singular value decomposition for w by a singular value decomposition method, and using a singular value matrix as the final fault characteristic vector; using the singular value matrixes in four modes of the rolling bearing as input and four matrixes corresponding to the four modes as output to train an Elman neural network. When the rolling bearing fails, whether the rolling bearing is faulted or not can be judged and direction of faults can be accurately positioned through analysis and judgment of a signal at t moment by the trained Elman neural network. According to the invention, classification of fault modes of the rolling bearing under variable working conditions can be effectively finished, and higher precision is maintained.

The invention discloses a modulation mode identification system and method based on a convolutional neural network, which solve the problems of complex feature extraction steps and low identificationrate under a low signal-to-noise ratio in the prior art. The simple feature in the identification system is constructed as a simple feature using a co-directional component and a quadrature componentof a baseband signal as signals, and the simple feature is sent to a convolutional neural network module for identification. The identification method comprises the steps of: modulating a transmittedsignal and performing pulse shaping; performing up-conversion on the transmitted signal and then transmitting the transmitted signal through an additive white Gaussian noise channel; performing pre-processing first by a receiving end to obtain the co-directional component r(t) of the analyzed signal; constructing the simple feature, i.e., constructing the co-directional component r(t) and the quadrature component of the analyzed signal into a two-dimensional matrix; performing feature learning and classification by the convolutional neural network; and sending a modulation method to a demodulation end to obtain a demodulated signal. The method is low in feature design complexity, avoids explicit feature extraction, has high classification correctness, and can be applied to communication systems having high recognition performance requirements.

What is disclosed is a system and method for determining arterial pulse transit time (PTT) for a subject. In one embodiment, time-series signals are received for each of a proximal and distal arterial site of a subject's body which represent blood volume changes in the microvascular tissue at each site. A proximal and distal analytic signal is obtained which has a first component being a waveform of the respective time-series signal and a second component being a transform of the respective waveform. A phase function is determined for the first and second components of each analytic signal. The phase function obtained for the proximal waveform is then subtracted from the phase function obtained for the distal waveform to get a phase difference. The phase difference is analyzed with the subject's heart rate to determine an arterial pulse wave transit time between the two proximal and distal sites.

Embodiments use seismic processing methods that account for the spatial variability of surface wave velocities. Embodiments analyze surface wave properties by rapidly characterizing spatial variability of the surface waves in the seismic survey data (302). Filtering criteria are formed using the spatial variability of the surface waves (204). The filtering criteria can then be used to remove at least a portion of the surface waves from the seismic data (206, 319). The rapid characterization involves estimating a local group velocity of the surface waves by cross-correlation of the analytic signals (302).

A signal under measurement x(t) is transformed into a complex analytic signal zc(t), and an instantaneous phase of the xc(t) is estimated using the zc(t). A linear phase is removed from the instantaneous phase to obtain a phase noise waveform Δφ(t) of the x(t), and the Δφ(t) is sampled at a timing close to a zero-crossing timing of the x(t) to obtain a timing jitter sequence. Then a difference sequence of the timing jitter sequence is calculated to obtain a period jitter sequence. The period jitter sequence is multiplied by a ratio T0 / Tk,k+1 of the fundamental period T0 of the x(t) and the sampling time interval Tk,k+1 to make a correction of the period jitter sequence. A period jitter value of the x(t) is obtained from the corrected period jitter sequence.

A method for measuring the temperature rise in anatomical tissue as a result of ultrasound treatment. A first ultrasound signal is obtained prior to treating the anatomical tissue, then a second ultrasound signal is obtained after the tissue is treated. Complex analytic signals are computed from the first and second ultrasound signals, then the depth-dependent delay is computed from the complex analytic signals. An echo strain map is generated from the slope of the depth-dependent delay. The echo strain map is used to estimate the amount of temperature rise from the first ultrasound signal to the second ultrasound signal. An image may then be created showing where temperature rise is occurring in the anatomical tissue.

The invention discloses a data processing method of a WiFi integrated tester based on the IEEE802.11n standard, and aims at processing data accurately in real time and reflecting performance of pieces to be reflected when the data received by the WiFi integrated tester satisfies the IEEE802.11n standard. The method comprises that accurate synchronization can be realized by combined timing synchronization based on cross correlation of energy packet detection and local training sequence; a frequency offset value can be accurately estimated by maximum likelihood estimation of carrier-wave frequency offset assisted by time-domain data; and channel characteristic can be accurately estimated via LS channel estimation and fitting. One frame of effective data is cut from received data, frequency compensation is carried out on the data after timing synchronization and frequency offset estimation, data is demodulated after removing the cyclic prefix, channel estimation is carried out, the signal domain is parsed, phase compensation is carried out on the data to obtain the EVM, and thus, the performance of the piece to be tested is accurately reflected.

The invention relates to a full-wave magnetic resonance signal random noise abatement method combining EMD and TFPF algorithms. The method is a 'blind' filtering method in which filtering range designis not needed. The method comprises the steps of firstly utilizing decomposition characteristics of the EMD algorithm to decompose full-wave magnetic resonance signals into different intrinsic mode functions, then using the TFPF algorithm to code signal dominant mode functions into instantaneous frequencies of unit amplitude analytic signals, and utilizing the characteristic that time-frequency distribution of the analytic signals is concentrated along instantaneous frequency to inhibit random noise. The full-wave magnetic resonance signal random noise abatement method combining the EMD and TFPF algorithms has the advantages that few filtering constraint conditions are needed, the operation is simple, there is no need to design a filtering range in a time-frequency domain, and the methodhas high adaptability to full-wave magnetic resonance signals with a low signal-noise rate; the detection efficiency is remarkably improved, a good denoising effect can be obtained only through once measuring, random noise is effectively reduced, signal components are not lost at the same time, the signal-to-noise ratio can be remarkably increased, and the accuracy of later inversion is improved.

The invention provides a sonar moving target imaging method based on target echo Doppler characteristics, which comprises the following steps of: performing band-pass filtering on echo data of each basic element in a receiving basic array; performing band-pass filtering on each frequency point signal to acquire band-pass data of each frequency point; performing quadrature demodulation on the datasubjected to band-pass filtering of each frequency point to acquire an analytic signal form of a real signal; performing Chebyshev weighting and focusing operation on the echo data subjected to quadrature demodulation of each frequency point; acquiring image data of each frequency point in a polar coordinate system by fast Fourier transform (FFT) beam forming; and performing interpolation mergingon the image data subjected to FFT beam forming of each frequency point, and converting an image in the polar coordinate system into an image which accords with the visual habit of people in a rectangular coordinate system by sector conversion. By the FFT beam forming, the method can be implemented by an FFT algorithm in digital signal processing, and the requirement of system real-time imaging is met.

The invention relates to a method for diagnosing power transformer winding working condition. The method includes the following steps: (1) inputting a signal Vi to a vibration generator to conduct vibration excitation to a power transformer winding, and collecting and recording a vibration signal Voi of each measuring point according to N vibration acceleration sensors on the surface of the power transformer winding; (2), respectively conducting Fourier transform to the input signal Vi and the vibration signal Voi of each measuring point, and then obtaining a vibration frequency response curve H(omega) of the power transformer winding; (3) conducting the Fourier transform to the vibration frequency response curve H(omega) and then obtaining a free vibration signal H(t) of the power transformer winding; (4) decomposing the free vibration signal H(t) into a plurality of natural mode functions; (5) conducting Hilbert transform to all natural mode functions which are obtained by decomposing; (6) constructing an analytic signal; (7) obtaining a kth natural frequency of the power transformer winding; (8) conducting discrimination to the power transformer winding working condition according to the changing of the natural frequency. Compared with the prior art, the method has the advantages of being precise in diagnosis, convenient to operate, safe and the like.

The invention provides a spectrum analysis method of a seismic signal and an apparatus thereof. The method comprises the following steps: acquiring the seismic signal; carrying out Hilbert transformation operation on the seismic signal to obtain an analytic signal of the seismic signal; carrying out WVD processing on the analytic signal; according to a result of the WVD processing, determining a Gauss window function and an attenuation coefficient; according to the determined Gauss window function and the attenuation coefficient, carrying out smooth pseudo-WVD distribution time frequency analysis processing on the result of the WVD processing. Through the method and the apparatus in the invention, a high time frequency resolution of seismic signal spectrum analysis can be obtained.

The invention provides a communication signal modulating and identifying method based on generalized S transformation. The communication signal modulating and identifying method comprises the following steps of: (1) carrying out analytic signal configuration on an input modulating signal according to the characteristic of an input signal to noise ratio modulating signal to obtain an analytic signal to be used as a signal for carrying out generalized S transformation; (2) configuring a Gaussian window function needed by the generalized S transformation; (3) determining a Gaussian window width factor sigma according to an expression formula of the generalized S transformation; carrying out the generalized S transformation on an input modulation signal by combining short-time Fourier transformation and the Gaussian window function to obtain time-frequency energy distribution images of the modulation signal; and (4) comparing energy images of all modulation signals according to the time-frequency energy distribution images obtained by the step (3) to find out a difference between the time-frequency energy distribution images of all modulation signals which are subjected to the generalized S transformation; selecting a frequency strip quantity with concentrated energy, a maximum value ratio of high-frequency component energy to low-frequency component energy, energy time domain distribution, high-frequency and low-frequency component extreme value time domain distribution and high-frequency component extreme value distribution so as to identify all modulation signals. According to the invention, a high identification rate is achieved under the condition of a low signal to noise ratio, and the method is suitable for modulating and identifying communication signals under a heavy clutter environment.

The invention provides a self-adaption surface wave attenuation method and belongs to the field of oil geophysical prospecting. The self-adaption surface wave attenuation method firstly conducts lowpass filtering on seismic record to obtain dominated records of the surface wave, and then uses Hilbert conversion to convert the records into analytic signals and uses an envelope amplitude difference theory to seek an optimized apparent velocity of each sampling point, and then chooses a space-time window in the sampling point along the optimized apparent velocity and uses the singular value decomposition to choose the preceding one or two maximum singular value to reconstruct space-time signals, and only the current amplitude value of the sampling point can be saved, and a surface wave model can be formed after procedures are completed one by one. Then, matched filtering between the surface wave model and original records is conducted to further revise a wave shape difference of the surface wave model. Lastly, the surface wave model is substracted from the original records and final results are obtained. The self-adaption surface wave attenuation method achieves the accurate positioning of each surface wave direction, so that vertical and horizontal amplitude changes of the surface wave in the seismic records can be overcome to a certain extent, so the self-adaption surface wave attenuation method has a adaptivity.

The invention discloses a glass surface authentic and false defect identification method and system based on an OCT (Optical Coherence Tomograhy)complex signal. The method comprises the following steps: performing the illumination and parallel detection by utilizing linear focused light in an OCT system, analyzing difference between a complex analytic signal along the depth direction at a glass interface and a complex analytic signal generated at a standard single reflection interface to classify a boundary of a defect core on the glass surface by utilizing a complex analytic signal obtained in an OCT imaging way, reconfiguring a high-precision glass surface shape appearance figure by utilizing a complex analytic reflection signal of the glass surface obtained in an OCT imaging way, comparing the glass surface defect core boundary figure with the glass surface shape appearance figure, and identifying an authentic defect and a false defect. By adopting the method and system, the high-resolution and high-accuracy authentic and false defect identification can be realized, the glass defect can be detected in real time in a dust production environment, and the error in judgment caused by the interference of dust can be avoided.

There is provided a method of and an apparatus for detecting delay faults in phase-locked loop circuits. A frequency impulse is applied to a phase-locked loop circuit under test as the reference clock, and a waveform of a signal outputted from the phase-locked loop circuit under test is transformed to an analytic signal to estimate an instantaneous phase of the analytic signal. A linear phase is estimated from the estimated instantaneous phase, and the estimated linear phase is removed from the estimated instantaneous phase to obtain a fluctuation term of the instantaneous phase. A delay time is measured from this fluctuation term of the instantaneous phase, and further, a delay fault is detected by comparing a time duration during which the phase-locked loop circuit remains in a state of oscillating a certain frequency with a time duration during which a fault-free phase-locked loop circuit remains in a state of oscillating that certain frequency.

The invention relates to an auto-focus processing method of a synthetic aperture sonar image, which mainly comprises the following steps: (1) obtaining width band analytic signal rp(t) by using complex baseband to demodulate each wave-return signal and matching wave-filtering process; (2) doing relevant process between adjacent wave-returning analytic signals; (3) obtaining the phase error estimation of the adjacent wave-returning analytic signals by computing the complex phase angle; (4) obtaining accumulation phase error caused by movement error by doing space location accumulation process; (5) using the phase error sequence {ªŠp} to do compensation to achieve wave-returning data adjustment; (6) Obtaining focus synthetic aperture sonar image by using the corresponding image reconstructing algorithm to the compensated data.

The invention belongs to the field of underground pipeline detection, and particularly relates to a buried iron pipeline detection and accurate positioning method and device based on magnetic anomaly vertical component analytic signal detection. The method particularly comprises the steps that multiple parallel detection paths are delimited on the ground of a detected region, magnetic anomaly analytic signal detectors are used for forming a linear array, magnetic anomaly vertical component analytic signals caused by buried iron pipelines are detected along the delimited tracks, four single-axis magnetic field sensors measure magnetic anomaly vertical components simultaneously, an analytic signal at the center of the cross is obtained through calculation and uploaded to a computer, detection surface analytic signal strength distribution is drawn on the computer, and existence and horizontal positions and orientations of the underground iron pipelines are indicated in a graph visualization mode. According to the buried iron pipeline detection and accurate positioning method and device, pipeline detection positioning is accurate, the use cost is low, instruments are easy to manufacture, and the economic benefit is significant.

The invention discloses a TDM (Time Division Multiplexing)-based high-order adaptive wave trap of a parallel structure and an adaptive wave trap method, and belongs to communication technology. The method comprises the following steps of: dividing a high-speed sampling point sequence into N (N is greater than or equal to 2 and is less than or equal to 9) low-speed sampling point sequence branchesbased on a narrow band analytic signal sampling theorem by using a sampling point interleaving TDM technology; performing cascaded high-order adaptive wave trap respectively; and combining by using the TDM technology to reduce the low-speed sampling point sequence branches into a high-speed sequence, wherein the entire wave trap falls to be zero close to a specific frequency omega i; and omega i is amended in a unified way by using a linkage method to realize adaptive iteration. Through the wave trap serving as preprocessing before de-spreading, a plurality of narrow band strong interferencescan be suppressed, and the interference tolerance of the system can be greatly improved. High-order adaptive wave trap can be realized at the sampling rate of over hundreds of megabits, the realization complexity is low, the wave trap effect and the stability are high, a plurality of zero fall combination phenomena can be reduced or avoided, and the number of zero fall frequency points is approximately the same as the number of the actual narrow band strong interferences. The wave trap and the wave trap method are mainly used in wideband or ultra wideband digital communication systems.

The method relates to an acoustic array imaging system and a method thereof. The system comprises a data acquisition module 101, a first imaging module 102, a second imaging module 103 and an image composite module 104. The method comprises the following steps of successively emitting array elements in an acoustic array and collecting echo signals so as to acquire an analysis signal; according to a sound propagation relation between the emitted array elements and receiving array elements in an array, acquiring a time-delay value, and according to the analysis signal and the time-delay value, calculating images of the receiving array elements; using a cascaded parallel composite processing unit to recombine the image of all the receiving array elements; and superposing all the composite images and carrying out envelope processing so as to acquire a full-matrix data acquisition imaging result. The system and the method have advantages that when each array element data is collected, processing is performed so that an occupied storage space is small; a parallel mode is used to increase an operation speed; during an actual application, calculating time consuming is less, and high frame rate imaging can be realized; and the method and the system are suitable for real-time data processing and high resolution imaging. In addition, the system and the method are suitable for acoustic array imaging under different frequency and application scenes.

The invention provides a method for determining the position of a reflection interface of seismic data, and belongs to the field of petroleum geophysical exploration. The method includes: (1) supposing seismic waves as f (t), performing Hilbert transform of the f (t), calculating analytic signals of real seismic signals, and obtaining the instantaneous amplitude, the instantaneous phase section Theta (t), and the instantaneous frequency of the seismic waves f (t); (2) performing first-order differential operation based on the instantaneous phase section Theta (t) of the seismic waves, and obtaining the instantaneous phase first-order difference G (t); and (3) obtaining F (t)=-f (t) via the polarity reverse processing of the seismic data f (t), performing Hilbert transform of the F (t), obtaining the instantaneous phase section Theta1 (t), performing first-order differential operation of the instantaneous phase section Theta1 (t), obtaining the instantaneous phase first-order difference j (t) of the seismic waves after polarity reverse, and calculating J (t)=-j (t) via the calculation of the opposite number of the j (t).

The invention is a multi-field direction multi-scale edge detection method, which is technique that can carry out quickly inversion for three-dimensional structure of shallow crust based on field data. The invention realizes the calculation of the modulus and angle of wavelet transform after the rotation of coordinate system through directional wavelet transform, thus realizes serving the connection of modulus maximum points of wavelet transform along the vertical direction of gradient vector as the multi-scale edge of the field. The invention overcomes the weak point that the it is insensitive to directional information in the method such as signal analysis method, Euler deconvolution method, level derivative method, field multi-scale edge detection method, etc., can quickly obtains complete and accurate abnormal location of the border of geophysical field in various depths, thus generates a more accurate three-dimensional structure for shallow crust.

The invention discloses a method and a device for realizing clear channel assessment (CCA) when an 802.11n device works under the band width of 40MHz. The device is composed of two groups of independent detectors; in order to obtain CCA of the band width of 20MHz of an upper side band, the device inputs signals to a Hilbert transformer, and the output of the Hilbert transformer is combined with original signals to form analytic signals; analytic signals are performed with energy detection, or with carrier detection after down-conversion so as to obtain CCA of the band width of 20MHz of the upper side band; and for obtaining CCA of the band width of 20MHz of a lower side band, sampled signals are input into another group of identical detectors after taking conjugation.

The invention relates to a tissue displacement estimation method and system based on ultrasonic echo radio frequency signals. The method includes a converting step, namely converting the entire-frame ultrasonic echo radio frequency signals into analytic signals; a segmenting step, namely segmenting the entire-frame analytic signals according to the preset window length and acquiring segmented window data segments; a product summary step, namely performing once no-offset product summary on the segmented window data segments corresponding to two adjacent frames and acquiring a target plurality; a phase calculating step, namely calculating the phase of the target plurality; and a corresponding displacement estimating step, namely utilizing the phase to calculate and acquire corresponding displacement between two frame signals. According to the tissue displacement estimation method based on the ultrasonic echo radio frequency signals, the entire-frame ultrasonic echo radio frequency signals are converted into the analytic signals once, calculating speed is increased greatly, the corresponding displacement between two frame signals can be acquired through once product summary, calculating amount is reduced, calculating efficiency is improved, and complexity is low.

The invention provides a multi-target medium frequency digital phased-array antenna, and provides a phased-array antenna, which has small resource consumption, less required direct digital control (DDC) modules, and needs one DDC module for each target. The multi-target medium frequency digital phased-array antenna is realized through the following technical scheme: in an antenna array side which is formed by individual array elements, the radio frequency front end of each individual array element corresponds to an analog to digital converter (ADC) unit (3) which is correspondingly connected with the individual array element, each ADC unit (3) converts an output analog medium frequency signal into a digital medium frequency signal, the digital medium frequency signal output by each ADC unit (3) is converted into an analytic signal by an individual digital beam forming (DBF) unit (4) which corresponds to an individual target, then the analytic signal is multiplied with an individual complex number weight vector which is produced by a weight production unit (5) which is correspondingly connected with each ADC unit (3), so wave beam synthesis is completed, an individual wave beam synthesis output signal is filtered by a channelizing band-pass filter unit (6) which is correspondingly connected, so the digital medium frequency signal of the individual target is obtained and is transferred to respective DDC units (7), and the baseband signal of the individual target is output.

The invention discloses an automobile and a reminding system and method for sounds outside the automobile. The system comprises a sound recognition device, a sound conversion device and a vehicle-mounted reminding device. The sound recognition device is used for receiving and recognizing the sounds outside the automobile, converting the sounds outside the automobile into corresponding sound signals and screening out sound signals meeting preset conditions. The sound conversion device is used for receiving the sound signals meeting the preset conditions and converting the received sound signals into corresponding analytic signals. The vehicle-mounted reminding device is used for receiving the analytic signals and converting the analytic signals into corresponding reminding signals. The automobile, especially, an automobile with good NVH performance can recognize, transmit and convert sounds outside a cab and remind a driver to pay attention to the driving environment, then the driver can make corresponding response according to actual conditions, and accordingly driving safety of the driver is guaranteed.

The invention provides a method for extracting a fluid factor. The method comprises the following steps of: detecting at least one channel seismic data in a work area; setting an initial value of a fractional order number used for fractional order Fourier transform; calculating the fractional order Fourier transform of one channel seismic data in the at least one channel seismic data according tothe fractional order number; calculating an analytic signal of the fractional order Fourier transform, and Wigner-Ville distribution with suppressed cross terms of the analytic signal; calculating Radon transform of a band window of the Wigner-Ville distribution with the suppressed cross terms; reconstructing a time frequency distribution map according to the Radon transform of the band window; and extracting the fluid factor from the time frequency distribution map. According to the method for extracting the fluid factor, the fluid factor can be accurately extracted from seismic waves even though the seismic waves have a dispersion effect.

The invention provides a field source depth obtaining method based on downward continuation of potential field data. The field source depth obtaining method comprises the steps of S1, obtaining actually measured potential field data; s2, calculating analytic signal data according to the actually measured potential field data; s3, analyzing the signal data according to the actually measured potential field data; calling a preset depth calculation model; obtaining the depth position of the target body; the depth calculation model carries out downward continuation calculation on the analysis signal data according to an improved Chebyshev-Pad approximation downward continuation calculation method, simple normalization calculation is carried out on a calculation result, the position of a localmaximum value is found based on the calculation result, and the position of the local maximum value is the depth position of the field source; and S4, performing three-dimensional visualization on thecalculation result obtained in the S3, and visually displaying the depth position of the field source. Compared with a conventional regularization downward continuation method, the method is higher in resolution and more accurate in depth calculation effect, can achieve the high-precision depth calculation of the field source, and facilitates the popularization and promotion.

The invention relates to a classifying method for the echo signals in ultrasonic non-destructive inspection that is based on fuzzy plane, which comprises the following procedures: first the Hibert transformation of ultrasonic signal is worked out to get the analytic signal; then the fuzzy function of the analytic ultrasonic signal is worked out; finally in respect to the sample of training set, the fuzzy function of the ultrasonic signal is mapped on a characteristic space of low dimensions by K-L transformation. The invention uses a classification method of echo signal based on the non variability of the time shift and frequency shift of mode of fuzzy function, can solve any problem in the pre treating method at characteristic extracting, overcome the influence on characteristic extracting from the arrival times of echo signals of different defects and from the central frequency of probe at inspection. The invention is of good noise proofness, good classification effect, and is of a wide application prospect.