scholarly journals SPEAKER LOCALIZATION AND SPEECH SEPARATIONIN TWO ECHOIC MIXTURES / KALBĖTOJO APTIKIMAS IR ŠNEKOS IŠSKYRIMAS DVIEJŲ SIGNALŲ MIŠINIUOSE SU AIDU

2011 ◽  
Vol 3 (1) ◽  
pp. 43-49
Author(s):  
Włodzimierz Kasprzak ◽  
Ning Ding ◽  
Nozomu Hamada
Keyword(s):  
Energy Distribution ◽  
Estimation Error ◽  
Real Life ◽  
Low Frequency ◽  
Delay Estimation ◽  
Distribution Analysis ◽  
Time Frequency ◽  
Time Points ◽  
Fundamental Frequencies ◽  
Orientation Histogram

We are developing two crucial improvements on the time-frequency masking approach to the blind speech separation of underdetermined mixtures when processing anechoic and echoic mixtures. First, the proposed method copes with the usually large amount of delay estimation error that appears in a low frequency band. This step generates a restrictive mask for phase delays on the basis of local and global energy distribution analysis. This mask allows the selected cells to contribute to the orientation histogram. Second, the strong WDO assumption (disjoint orthogonal frequency domain) is relaxed by allowing some frequency bins to be shared by both sources. By detecting fundamental frequencies of speakers at instantaneous time points, mask creation is supported by exploring their harmonic frequencies. The proposed method is proved to be effective and reliable in conducting experiments with both simulated and real-life mixtures.

Copula-Based Time-Frequency Distribution Analysis for Planetary Gearbox Fault Detection

2017 ◽  
Author(s):  
Libin Liu ◽  
Ming J. Zuo
Keyword(s):  
Fault Detection ◽  
Energy Distribution ◽  
Simulated Data ◽  
Frequency Resolution ◽  
Data Sets ◽  
Distribution Analysis ◽  
Frequency Distributions ◽  
Copula Theory ◽  
Planetary Gearbox ◽  
Time Frequency

Linear and bilinear time-frequency distributions (TFDs) have been employed in planetary gearbox fault diagnosis. For linear TFDs, there is a trade-off between the time localization and frequency resolution and the spectrogram may not have correct energy marginals. For bilinear TFDs, they cannot be interpreted as an energy distribution because of the existence of possible negative values even though they are designed for energy density representation. To overcome these shortcomings, TFDs based on copula theory have been reported in the literature. In this paper, we analyze two simulated data sets using linear TFD and copula-based TFD. The results show that the constructed copula-based TFD has desirable properties of being positive, free from cross-term interference, having high time-frequency resolution and matching well with true marginals. The copula-based TFD is also able to locate fault-induced impulses by vertical lines over a certain frequency range in the time-frequency domain. Consequently, this study confirms the advantages of the copula-based TFD as an energy distribution and its capability in fault detection for planetary gearboxes.

Accelerating the fatigue analysis based on strain signal using Hilbert–Huang transform

2019 ◽  
Vol 10 (1) ◽  
pp. 118-132
Author(s):  
Nadia Nurnajihah M. Nasir ◽  
Salvinder Singh ◽  
Shahrum Abdullah ◽  
Sallehuddin Mohamed Haris
Keyword(s):  
Fatigue Life ◽  
Fatigue Damage ◽  
Low Frequency ◽  
Life Assessment ◽  
Distribution Analysis ◽  
Original Signal ◽  
Damage Potential ◽  
Content Type ◽  
Hilbert Huang Transform ◽  
Time Frequency

Purpose The purpose of this paper is to present the application of Hilbert–Huang transform (HHT) for fatigue damage feature characterisation in the time–frequency domain based on strain signals obtained from the automotive coil springs. Design/methodology/approach HHT was employed to detect the temporary changes in frequency characteristics of the vibration response of the signals. The extraction successfully reduced the length of the original signal to 40 per cent, whereas the fatigue damage was retained. The analysis process for this work is divided into three stages: signal characterisation with the application of fatigue data editing (FDE) for fatigue life assessment, empirical mode decomposition with Hilbert transform, an energy–time–frequency distribution analysis of each intrinsic mode function (IMF). Findings The edited signal had a time length of 72.5 s, which was 40 per cent lower than the original signal. Both signals were retained statistically with close mean, root-mean-square and kurtosis value. FDE improved the fatigue life, and the extraction did not affect the content and behaviour of the original signal because the editing technique only removed the minimal fatigue damage potential. HHT helped to remove unnecessary noise in the recorded signals. EMD produced sets of IMFs that indicated the differences between the original signal and mean of the signal to produce new components. The low-frequency energy was expected to cause large damage, whereas the high-frequency energy will cause small damage. Originality/value HHT and EMD can be used in the strain data signal analysis of the automotive component of a suspension system. This is to improve the fatigue life, where the extraction did not affect the content and behaviour of the original signal because the editing technique only removed the minimal fatigue damage potential.

Study on Time-Frequency Spectrum Characteristic of Dynamic Cutting Load Based on Wavelet Regularization

2014 ◽  
Vol 577 ◽  
pp. 196-200 ◽  
Author(s):  
Chun Sheng Liu ◽  
Chun Ping Ren ◽  
Fei Han
Keyword(s):  
Energy Distribution ◽  
Frequency Spectrum ◽  
Low Frequency ◽  
Cutting Process ◽  
Load Spectrum ◽  
Cycle Number ◽  
Conical Pick ◽  
Time Frequency ◽  
Wavelet Regularization ◽  
Spectrum Characteristic

Aimed at investigating time-frequency spectrum characteristic laws of conical pick rotary crushing coal and rock, this paper determines the mapping relationship of load spectrum between energy distribution and cutting process, and achieves quantitative reconstruction of the cutting coal and rock load spectrum. The experimental load spectrum is used as the object of research, utilizing wavelet regularization method to establish load spectrum reconstruction model of the pick cutting coal and rock, which will achieve its reconstruction load spectrum, so that it will discuss the variation of reconstruction load spectrum. Finally, it determines energy distribution of the load spectrum in different frequency band. The results show that the experimental load spectrum energy increases with the increasing of the cutting cycle number, and then decreases, so the characteristics of energy can characterize the cutting process. Energy of reconstruction load spectrum is mainly distributed in the low frequency range, which focuses on 1Hz and 3Hz, the amplitude of the high frequency energy is smaller than others.

scholarly journals Tunable characteristics of low-frequency bandgaps in two-dimensional multivibrator phononic crystal plates under prestrain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hai-Fei Zhu ◽  
Xiao-Wei Sun ◽  
Ting Song ◽  
Xiao-Dong Wen ◽  
Xi-Xuan Liu ◽  
...  
Keyword(s):  
Phononic Crystal ◽  
Real Life ◽  
Low Frequency ◽  
Acoustic Vibration ◽  
Crystal Plate ◽  
Frequency Noise ◽  
Two Dimensional ◽  
The Matrix ◽  
Noise Frequency ◽  
Realtime Control

AbstractIn view of the influence of variability of low-frequency noise frequency on noise prevention in real life, we present a novel two-dimensional tunable phononic crystal plate which is consisted of lead columns deposited in a silicone rubber plate with periodic holes and calculate its bandgap characteristics by finite element method. The low-frequency bandgap mechanism of the designed model is discussed simultaneously. Accordingly, the influence of geometric parameters of the phononic crystal plate on the bandgap characteristics is analyzed and the bandgap adjustability under prestretch strain is further studied. Results show that the new designed phononic crystal plate has lower bandgap starting frequency and wider bandwidth than the traditional single-sided structure, which is due to the coupling between the resonance mode of the scatterer and the long traveling wave in the matrix with the introduction of periodic holes. Applying prestretch strain to the matrix can realize active realtime control of low-frequency bandgap under slight deformation and broaden the low-frequency bandgap, which can be explained as the multiple bands tend to be flattened due to the localization degree of unit cell vibration increases with the rise of prestrain. The presented structure improves the realtime adjustability of sound isolation and vibration reduction frequency for phononic crystal in complex acoustic vibration environments.

scholarly journals Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance

2021 ◽  
Vol 13 (3) ◽  
pp. 480
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Principal Component Analysis ◽  
Ice Sheet ◽  
Low Frequency ◽  
Principal Component ◽  
Equatorial Pacific ◽  
Mass Change ◽  
Frequency Variation ◽  
Periodic Signal ◽  
Time Frequency ◽  
The Antarctic

Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly reflects atmospheric factors such as precipitation accumulation.

Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

Adsorption of levofloxacin onto mechanochemistry treated zeolite: Modeling and site energy distribution analysis

2019 ◽  
Vol 222 ◽  
pp. 30-34 ◽  
Author(s):  
Zhen Chen ◽  
Wei Ma ◽  
Guang Lu ◽  
Fanqing Meng ◽  
Shibo Duan ◽  
...  
Keyword(s):  
Energy Distribution ◽  
Distribution Analysis ◽  
Site Energy

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

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