89results about How to "High time-frequency resolution" patented technology

The invention discloses an intelligent road sweeper and a road pollutant identification method and a control method thereof. The road sweeper comprises a road sweeper body, a laser radar, a camera, anencoder, a dust concentration detector, an inertial sensor, a GPS system and a processing controller. A method for identify road pollutants include acquiring RGB images of clean road surface and roadfacilities to be cleaned, convert that acquired RGB images into HSV space, and obtaining a BP neural network model capable of identifying the clean road surface and road facilities; The real-time image information of the road to be cleaned is input to the BP neural network model to identify the pollutants. The method for identifying pollutants such as garbage in the present invention utilizes theHSV feature of a road image, which has a larger information amount of the gray value of the image than that of a single image, and has a better effect for identifying pollutants such as garbage.

The invention relates to a power transmission line short circuit fault diagnosis method based on empirical wavelet transformation and local energy. The method is characterized by comprising the following steps of: collecting short-circuit fault voltage signals; using an empirical wavelet transformation method to process the short-circuit fault voltage signals to obtain an empirical mode; performing short-circuit fault detection on the basis of empirical wavelet transformation; and performing short-circuit fault classification feature extraction on the basis of block local energy. The method has the advantages of scientificity, rationality, high time-frequency resolution, high noise resistance, high adaptability, good application effect and the like.

The invention discloses a microseismic signal noise reduction filtering method based on a VMD and a wavelet packet and belongs to the signal processing technology field. In the invention, a mode of combining the VMD and the wavelet packet is adopted; adaptivity of a VMD decomposition method and characteristics of a high mathematical theory basis, high frequency noise suppression and the like in the algorithm are used; and the wavelet packet has the characteristics of carrying out multilevel division on a frequency band, further decomposing a high frequency portion which is not subdivided in multiresolution analysis, and adaptively selecting a frequency band according to a characteristic of an analyzed signal so that a time frequency resolution is increased. In the invention, based on a condition of maintaining randomness, non-stationary performance and a burst transient characteristic of a microseismic signal, the microseismic signal is filtered. The algorithm is simple and easy and an effect is ideal. Effective noise reduction filtering can be performed on a mine noisy microseismic signal. And a good technical value and an application prospect are possessed.

The invention discloses a method for diagnosing a fault of an automatic ammunition supply and transportation device, and aims to realize low maintenance cost and short period. The method comprises the following steps of: arranging measurement points on the large-aperture artillery automatic ammunition supply and transportation device, and selecting driving current of an ammunition supply motor and a hydraulic oil source motor as the measurement points according to a driving mode supplied by an automatic ammunition supply and transportation motion cyclic graph; simultaneously acquiring and recording angular displacement signals and angular speed signals of a rotary ammunition cabin, a coordination arm, a turning mechanism and an ammunition transportation mechanism as well as load current change signals of driving motors by a portable signal acquirer; performing signal data correction work of baseline drift correction and wild point removal on the acquired and recorded angular motion signals and current change signals; performing time domain analysis on an acquired acceleration impact signal and an acquired current impact signal, and making an amplitude probability density and probability distribution curve; and performing short-time-frequency characteristic extraction and small sample signal analysis on an impact response signal, analyzing a wavelet energy spectrum, and supplying peak values and frequencies in a frequency domain, and energy and entropy of each frequency band.

The invention relates to a seismic wave attenuation compensation method in a curvelet domain. The method comprises the following steps of (1) collecting a seismic signal and carrying out preprocessing to obtain a time domain signal x(t) of an earthquake, (2) carrying out curvelet transform on the time domain signal x(t) to obtain a curvelet domain signal psi j, l (omega j, Tk), (3) carrying out smoothing process on the curvelet domain signal psi j, l (omega j, Tk) to obtain a curvelet coefficient Phi j, l (omega j, Tk), (4) carrying out threshold iterative processing on the curvelet coefficient Phi j, l (omega j, Tk) to obtain a denoised signal Psi j, l (omega j, Tk), (5) carrying out pointwise recursion to obtain the deep and shallow layer energy ratio delta j, ll (omega j, Tk) of the denoised signal Psi j, l (omega j, Tk) in each frequency band compensation angle, (6) calculating all frequency band compensation factor coefficient matrices Dj, ll (omega j, Tk) in a compensation angle, (7) weighing the reciprocal values of the compensation factor coefficient matrices Dj, ll (omega j, Tk) in all frequency band compensation angles to obtain a signal Cj, l (omega j, Tk) after curvelet wave weighing, (8) carrying out inverse curvelet transform on the signal Cj, l (omega j, Tk) after the curvelet wave weighing to obtain a time domain signal xx(t) after frequency division directional compensation. The method can be widely applied to the seismic data processing.

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 discloses a method for positioning an underwater sound pulse signal by double array elements on the basis of cross-correlation, which comprises the following steps of: a step 10 of carrying out estimation of time-frequency distribution with a self-adaption radial gaussian kernel function on a frequency of the underwater sound pulse signal; and a step 20 of implementing positioning on the underwater sound pulse signal received by the double array elements, wherein the step 10 comprises a step 101 of determining a fuzzy function on a two-dimensional frequency-deviation-time-lag region, a step 102 of setting a total dot number of a discretized frequency deviation and a total dot number of a discretized time lag, a step 103 of converting the fuzzy function in a rectangular coordinate system into a fuzzy function in a polar coordinate system and a step 104 of a central frequency and corresponding instantaneous time of the received signal; and the step 20 comprises a step 201 of determining a searching range of a sound source, a step 202 of determining corresponding copy channel pulse response and a step 203 of implementing matching field positioning on a target. The method utilizes two vertical receiving hydrophones to implement accurate positioning on the unknown underwater sound pulse signal of a transmitted signal.

The invention discloses a seismic fluid prediction method based on VMD and TK energy operators. The method comprises the following steps: S1, performing variational mode decomposition on a seismic signal to obtain a set of modal components that reflect a natural mode of vibration inside the seismic signal and have an instantaneous frequency with real physical meaning; S2, getting TK energy spectrums of each modal component by using the TK energy operators to obtain more accurate energy distribution on a signal time frequency; and S3, performing effective and accurate seismic fluid prediction by searching fluid characteristics of ''enhanced low frequency energy and attenuated high frequency energy'' of oil and gas contained in the reservoir. The seismic fluid prediction method based on VMDand TK energy operators combines the variational mode decomposition with the TK energy operators, which has stronger identification for the fluid-containing characteristics of the reservoir, and can effectively improve the accuracy of seismic fluid prediction.

The invention discloses a traveling wave time-frequency analysis method based on variational mode decomposition and Wigner-ville distribution. The method includes the following steps that: fault traveling wave signals are detected, and Karebauer phase-mode transformation is performed on three-phase voltage traveling wave signals, so that a traveling wave aerial mode component is obtained; variational mode decomposition is performed on the traveling wave aerial mode component, so that K intrinsic mode components are generated; Wigner-Ville analysis is performed on each intrinsic mode component;and the Wigner-Ville distribution of each intrinsic mode component is linearly superimposed, so that the time-frequency domain distribution of original traveling wave aerial mode signals is obtained.With the method of the invention adopted, the interference of cross terms in Wigner-Ville distribution can be effectively suppressed; a good noise suppression effect enabling good VMD (Variational Mode Decomposition) is preserved; time-frequency resolution enabling high Wigner-Ville distribution and good time-frequency aggregation are preserved; traveling wave time-frequency domain information characteristics are truly and accurately represented; and fault traveling waves can be completely observed. The method is of important theoretical and practical significance for the practical application of fault traveling wave protection and positioning.

The present invention discloses a CEEMD-SPWVD time-frequency spectrum analysis-based post-stack seismic fluid prediction method which solves the defect in the prior art that due to a wavelet basis reason of the wavelet transform, the focusing capability of the extracted frequency domain data is insufficient, so that the accurate frequency component data can not be extracted correctly. The post-stack seismic fluid prediction method of the present invention comprises the steps of utilizing a complete ensemble empirical mode decomposition (CEEMD) method to decompose the seismic trace set data to obtain a plurality of IMF frequency components, carrying out the cross-correlation calculation on an original seismic trace set signal and the IMF components, removing the IMF Redundant components having low cross-correlation coefficients, and then carrying out the SPWVD calculation on the effective IMF components and superposing to obtain a CEEMD-SPWVD time frequency spectrum, and finally calculating the frequency attenuation gradient of the obtained CEEMD-SPWVD time frequency spectrum, thereby guaranteeing the situation that the effective frequency of the post-stack seismic data can be extracted most accurately.

The invention discloses a method for measuring a distance of a low-frequency underwater sound pulse signal on the basis of frequency dispersion features, which comprises the following steps of: a step 10 of receiving the low-frequency underwater sound pulse signal by a single hydrophone and then carrying out representation of time-frequency distribution with a self-adaption radial gaussian kernel function on the frequency dispersion features of the low-frequency underwater sound pulse signal; a step 20 of extracting a frequency dispersion curve of spread modes in the time-frequency distribution to obtain a time difference of arrival between the modes; and a step 30 of measuring the distance of a sound source according to the time difference between the extracted modes under each frequency point, i.e. firstly, measuring theoretical group velocity values corresponding to the extracted modes under each frequency point by using a normal mode model, then estimating the distance of the sound source under each frequency point in a frequency range in which a mode mc is the same with a mode nc, and finally, measuring an arithmetic mean of the estimated distances under all the frequency points so as to obtain the distance of the sound source. According to the measuring method, accurate measurement on the distance of the low-frequency underwater sound pulse signal of shallow sea can be implemented by utilizing the single hydrophone.

The embodiment of the invention discloses a rotational speed estimation method and device based on gear meshing vibration, which are used for enhancing the anti-noise capability and improving the precision of the estimated rotational speed curve. The rotational speed estimation method comprises the following steps: acquiring a gear meshing vibration signal; calculating the Wigner-Ville distribution and the wavelet scale spectrum of the gear meshing vibration signal; achieving time-frequency fusion of the Wigner-Ville distribution and the wavelet scale spectrum to obtain the time-frequency fusion distribution; according to the time-frequency fusion distribution, determining the gear meshing frequency curve; according to the gear meshing frequency curve and the number of gears of a driving wheel, determining the rotational speed curve of the driving wheel.

The invention relates to a propeller shaft frequency searching method based on improved noise envelope signal recognition. The method includes: enveloping an original hydrophone signal, and performingHilbert-Yellow transform on each wavelet packet signal to obtain a wavelet envelope signal; performing wavelet reconstruction to obtain an improved noise envelope signal; calculating a time correlation spectrum, take a line spectrum protruding at the peak of the low frequency band as the suspected shaft frequency; setting a step size smaller than the frequency resolution according to the demand;forming a suspected shaft frequency set with the suspected shaft frequency as the center; performing cyclic correlation calculation on a time correlation spectral signal on each suspected shaft frequency to obtain the frequency statistical amount of a cyclic modulation spectrum; and finally searching the shaft frequency of a target according to the frequency statistical amount. The method of the invention corrects axial frequency offset errors generated by the conventional cyclic modulation spectrum methods in the spectrum calculation process, improves the accuracy of the shaft frequency detection, greatly reduces the calculation amount of the loop iteration, and is convenient to implement in engineering application.

The invention discloses a fault diagnosis method for an AC/DC charging equipment power device based on wavelet packet analysis, and the method comprises the steps: analyzing a charging equipment powermodule, and determining a fault class; obtaining output signals of the charging equipment power module under the normal condition and various fault conditions; carrying out the high-low frequency decomposition of the output signals, carrying out the multilayer wavelet packet decomposition of the high-low frequency signals obtained through decomposition, and carrying out the reconstruction of a wavelet packet decomposition coefficient; calculating the extracted signal energy at all frequency bands, carrying out the normalized calculation of the signal energy, and finally determining a centralized frequency band range of the signal energy; carrying out the power spectrum analysis of the reconstructed wavelet packet decomposition coefficient, determining the feature frequency and power spectrum value of a frequency band signal, comparing the comparison with the fault analysis, and determining the type of a fault; and carrying out the fault type coding of the type of the fault. The methodimproves the time-frequency resolution of a signal, achieves the precise fault positioning through the spectrum features, and improves the precision of the fault diagnosis of the AC/DC charging equipment power device.

The invention discloses a series-type seismic signal optimization time frequency transformation method, which relates to an oil exploration data processing and interpretation technology. Complete set empirical mode decomposition is used for decomposing an original seismic trace x(t) to a plurality of different bands of intrinsic mode function (IMF) signal components, each signal component serves as a new input signal imf(t), an energy optimization criterion objective function is then used for solving the optimal frequency domain window parameter, an optimization time frequency distribution calculation formula is used for sequentially solving the time frequency distribution TFR(t, f) for each newly-inputted signal, and finally, the obtained time frequency distribution is overlapped to obtain a seismic signal time frequency spectrum TFR(t, f) with the time frequency resolution improved obviously. The technology makes full use of effective information of seismic exploration data, the time frequency resolution is high, the calculation speed can be improved exponentially, the information utilization rate in the seismic exploration data is improved, and the seismic data interpretation reliability is also improved.