A new method for estimating the correlation of seismic waveforms based on the NTFT

2021 ◽  
Author(s):  
Wei Cheng ◽  
Lintao Liu ◽  
Guocheng Wang
Keyword(s):  
Signal To Noise Ratio ◽  
Frequency Component ◽  
Love Waves ◽  
Seismic Signals ◽  
High Background ◽  
Time Frequency ◽  
Seismic Waveforms ◽  
Delay Times ◽  
High Background Noise ◽  
Mariana Island Arc

Summary We propose a new correlation function called the similarity coefficient (SC) based on the normal time-frequency transform (NTFT) to evaluate the similarity between two nonstationary seismic signals as a function of the delay time. The SC is defined in the time-frequency spectrum of the NTFT, and the instantaneous phase and amplitude of each frequency component in a signal are employed to calculate the SC. Our simulation experiments demonstrate that the SC method can effectively recognize similar signals compared to the conventional normalized cross-correlation coefficient (NCC) under high background noise conditions. The SC presents good robustness in identifying similar signals and performs well in the case of an extremely low signal-to-noise ratio (SNR), which makes it suitable for detecting weak seismic signals concealed by noise. As a real application case, we use the SC method to detect quasi-Love (QL) surface waves. QL waves are scattered Love waves and are important indicators for lateral anisotropic gradients in the upper mantle. We detect the QL waves at 21 stations deployed across Japan after the December 23 2004 Mw 8.1 Macquarie earthquake by using the SC method. Obvious QL waves are observed at 19 stations, and we locate the Love-to-Rayleigh scatterers by applying the delay times between the QL and main Love waves. Our results show that the QL wave scatterers were mostly generated in two areas: Mariana subduction and Papua New Guinea. The observations of QL waves suggest the presence of lateral gradients in anisotropy beneath those two areas. The spatial distribution of the 13 scatterers in the Mariana subduction zone agrees well with the Mariana Island Arc, and we infer that the Mariana slab may have melted and coupled with the surrounding mantle at depth.

A Novel Approach for Detection of Bearing Defects from Noisy Vibration Signal

2014 ◽  
Vol 592-594 ◽  
pp. 2001-2005
Author(s):  
Deepak Paliwal ◽  
Achintya Choudhury ◽  
T. Govardhan ◽  
Saurabh Singh Chandrawat
Keyword(s):  
Signal To Noise Ratio ◽  
Vibration Signal ◽  
High Background ◽  
Related Information ◽  
Bearing Defects ◽  
Novel Approach ◽  
Deep Groove ◽  
Deep Groove Ball Bearing ◽  
High Background Noise ◽  
Inner Race

Vibration signal of a defective bearing carries fault related information. The aim of this paper is to develop a signal processing methodology that identifies the presence of defect from bearing vibration signal subjected high background noise. A simulated vibration signal considering inner race defect in a deep groove ball bearing with low signal to noise ratio has been generated and investigated. A technique involving CWT of vibration signal and post-processing though FFT has been adopted to analyze the signal. Results show that proposed methodology can yield the presence of inner race defect prominently from a noisy vibration signal.

Robust estimation of instantaneous phase using a time-frequency adaptive filter

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. O1-O7 ◽  
Author(s):  
Wen-kai Lu ◽  
Chang-Kai Zhang
Keyword(s):  
Adaptive Filter ◽  
Signal To Noise Ratio ◽  
Amplitude Spectrum ◽  
Estimation Method ◽  
Frequency Component ◽  
Data Sets ◽  
Time Frequency ◽  
Instantaneous Phase ◽  
The Hilbert Transform ◽  
Short Time

The instantaneous phase estimated by the Hilbert transform (HT) is susceptible to noise; we propose a robust approach for the estimation of instantaneous phase in noisy situations. The main procedure of the proposed method is applying an adaptive filter in time-frequency domain and calculating the analytic signal. By supposing that one frequency component with higher amplitude has higher signal-to-noise ratio, a zero-phase adaptive filter, which is constructed by using the time-frequency amplitude spectrum, enhances the frequency components with higher amplitudes and suppresses those with lower amplitudes. The estimation of instantaneous frequency, which is defined as the derivative of instantaneous phase, is also improved by the proposed robust instantaneous phase estimation method. Synthetic and field data sets are used to demonstrate the performance of the proposed method for the estimation of instantaneous phase and frequency, compared by the HT and short-time-Fourier-transform methods.

scholarly journals Stable Q analysis on vertical seismic profiling data

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. D217-D225 ◽  
Author(s):  
Yanghua Wang
Keyword(s):  
Frequency Domain ◽  
Text Analysis ◽  
Signal To Noise Ratio ◽  
Attenuation Measurement ◽  
Time Frequency ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Seismic Waveforms ◽  
Vsp Data ◽  
Fitting In

Vertical seismic profiling (VSP) provides a direct observation of seismic waveforms propagating to various depths within the earth’s subsurface. The [Formula: see text] analysis or attenuation ([Formula: see text]) analysis based on direct comparison between individual waveforms at different depths, however, suffers from the problem of instability commonly due to fluctuations inherent in the frequency spectrum of each waveform. To improve the stability, we considered frequency and time variations and conducted [Formula: see text] analysis on an integrated observation. First, we transformed the time- (or depth-) frequency-domain spectrum to a 1D attenuation measurement with respect to a single variable, the product of time and frequency. Although this 1D measurement has a higher signal-to-noise ratio than the 2D spectrum in the time-frequency domain, it can also be used to further generate a stabilized compensation function. Then, we implemented two [Formula: see text]-analysis methods by data fitting (in a least-squares sense) to either the attenuation measurement or the data-driven gain function. These two methods are theoretically consistent and practically robust for conducting [Formula: see text] analysis on field VSP data.

scholarly journals Ceilometer lidar comparison: backscatter coefficient retrieval and signal-to-noise ratio determination

2010 ◽  
Vol 3 (6) ◽  
pp. 1763-1770 ◽  
Author(s):  
B. Heese ◽  
H. Flentje ◽  
D. Althausen ◽  
A. Ansmann ◽  
S. Frey
Keyword(s):  
Signal To Noise Ratio ◽  
Backscatter Coefficient ◽  
Signal To Noise ◽  
Night Time ◽  
High Background ◽  
Comparison Results ◽  
High Background Noise ◽  
Ratio Determination ◽  
Noise Ratio ◽  
New Generation

Abstract. The potential of a new generation of ceilometer instruments for aerosol monitoring has been studied in the Ceilometer Lidar Comparison (CLIC) study. The used ceilometer was developed by Jenoptik, Germany, and is designed to find both thin cirrus clouds at tropopause level and aerosol layers at close ranges during day and night-time. The comparison study was performed to determine up to which altitude the ceilometers are capable to deliver particle backscatter coefficient profiles. For this, the derived ceilometer profiles are compared to simultaneously measured lidar profiles at the same wavelength. The lidar used for the comparison was the multi-wavelengths Raman lidar PollyXT. To demonstrate the capabilities and limits of ceilometers for the derivation of particle backscatter coefficient profiles from their measurements two examples of the comparison results are shown. Two cases, a daytime case with high background noise and a less noisy night-time case, are chosen. In both cases the ceilometer profiles compare well with the lidar profiles in atmospheric structures like aerosol layers or the boundary layer top height. However, the determination of the correct magnitude of the particle backscatter coefficient needs a calibration of the ceilometer data with an independent measurement of the aerosol optical depth by a sun photometer. To characterizes the ceilometers signal performance with increasing altitude a comprehensive signal-to-noise ratio study was performed. During daytime the signal-to-noise ratio is higher than 1 up to 4–5 km depending on the aerosol content. In our night-time case the SNR is higher than 1 even up to 8.5 km, so that also aerosol layers in the upper troposphere had been detected by the ceilometer.

NOISE AND TARGET SIGNALS SIMULATION IN PASSIVE SEISMIC LOCATION SYSTEMS

2018 ◽  
pp. 73-78
Author(s):  
Yu. V. Morozov ◽  
M. A. Rajfeld ◽  
A. A. Spektor
Keyword(s):  
Pulse Sequence ◽  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Seismic Signals ◽  
Simulation Procedure ◽  
Proposed Model ◽  
Seismic Location ◽  
Passive Seismic ◽  
System Characteristics ◽  
Primary Pulse

The paper proposes the model of a person seismic signal with noise for the investigation of passive seismic location system characteristics. The known models based on Gabor and Berlage pulses have been analyzed. These models are not able wholly to consider statistical properties of seismic signals. The proposed model is based on almost cyclic character of seismic signals, Gauss character of fluctuations inside a pulse, random amplitude change from pulse to pulse and relatively small fluctuation of separate pulses positions. The simulation procedure consists of passing the white noise through a linear generating filter with characteristics formed by real steps of a person, and the primary pulse sequence modulation by Gauss functions. The model permits to control the signal-to-noise ratio after its reduction to unity and to vary pulse shifts with respect to person steps irregularity. It has been shown that the model of a person seismic signal with noise agrees with experimental data.

scholarly journals A Local Search Maximum Likelihood Parameter Estimator of Chirp Signal

2021 ◽  
Vol 11 (2) ◽  
pp. 673
Author(s):  
Guangli Ben ◽  
Xifeng Zheng ◽  
Yongcheng Wang ◽  
Ning Zhang ◽  
Xin Zhang
Keyword(s):  
Maximum Likelihood ◽  
Local Search ◽  
Signal To Noise Ratio ◽  
Estimation Accuracy ◽  
Chirp Signal ◽  
Estimation Of Parameters ◽  
Parameter Estimator ◽  
Denoising Method ◽  
Time Frequency ◽  
Approximate Estimation

A local search Maximum Likelihood (ML) parameter estimator for mono-component chirp signal in low Signal-to-Noise Ratio (SNR) conditions is proposed in this paper. The approach combines a deep learning denoising method with a two-step parameter estimator. The denoiser utilizes residual learning assisted Denoising Convolutional Neural Network (DnCNN) to recover the structured signal component, which is used to denoise the original observations. Following the denoising step, we employ a coarse parameter estimator, which is based on the Time-Frequency (TF) distribution, to the denoised signal for approximate estimation of parameters. Then around the coarse results, we do a local search by using the ML technique to achieve fine estimation. Numerical results show that the proposed approach outperforms several methods in terms of parameter estimation accuracy and efficiency.

scholarly journals The Reporter System for GPCR Assay with the Fission YeastSchizosaccharomyces pombe

Scientifica ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Shintaro Sasuga ◽  
Toshiya Osada
Keyword(s):  
Fluorescent Protein ◽  
Signal To Noise Ratio ◽  
Biological Activities ◽  
Inducible Promoter ◽  
Upstream Region ◽  
Reporter Plasmid ◽  
Reporter System ◽  
High Background ◽  
Downstream Region ◽  
Green Fluorescent

G protein-coupled receptors (GPCRs) are associated with a great variety of biological activities. Yeasts are often utilized as a host for heterologous GPCR assay. We engineered the intense reporter plasmids for fission yeast to produce green fluorescent protein (GFP) through its endogenous GPCR pathway. As a control region of GFP expression on the reporter plasmid, we focused on seven endogenous genes specifically activated through the pathway. When upstream regions of these genes were used as an inducible promoter in combination with LPI terminator, themam2upstream region produced GFP most rapidly and intensely despite the high background. Subsequently, LPI terminator was replaced with the corresponding downstream regions. The SPBC4.01 downstream region enhanced the response with the low background. Furthermore, combining SPBC4.01 downstream region with the sxa2 upstream region, the signal to noise ratio was obviously better than those of other regions. We also evaluated the time- and dose-dependent GFP productions of the strains transformed with the reporter plasmids. Finally, we exhibited a model of simplified GPCR assay with the reporter plasmid by expressing endogenous GPCR under the control of the foreign promoter.

Analysis of Vibration Signals in Monitoring Titanium End Milling Process Using Triaxial Accelerometer

2021 ◽  
Author(s):  
John Henry Navarro-Devia ◽  
Dzung Viet Dao ◽  
Yun Chen ◽  
Huaizhong Li
Keyword(s):  
Titanium Alloys ◽  
Frequency Domain ◽  
Single Channel ◽  
End Milling ◽  
Cutting Parameters ◽  
Frequency Component ◽  
Spindle Speed ◽  
Triaxial Accelerometer ◽  
Vibration Signals ◽  
Time Frequency

Abstract Vibrations during milling of hard-to-cut materials can cause low productivity, inferior quality and short tool life. It is one of the common issues in the machining of hard-to-cut materials employed in aerospace applications, such as titanium alloys. This paper presents an analysis of the vibration signals in the 3 axes of movement during titanium end milling, under diverse cutting parameters, manipulating spindle speed and feed rate. Signals were obtained using a triaxial accelerometer and processed in MATLAB. The analysis was conducted in the frequency-domain and the time-frequency domain. The results show that high-frequency vibration could occur in any direction with different amplitudes. Response on each axis depends on spindle speed, feed, and type of milling. A frequency component continually appeared in each axis regardless of cutting conditions and is located near the natural frequencies. Finally, the triaxial accelerations were compared for the milling cases with a new and a worn tool. Results highlight the importance and need for continuous monitoring of vibration in the 3 axes, instead of only using a single-channel signal, providing experimental data which could expand knowledge relating to the milling of titanium alloys.

Novel Method for Detecting Weak AE Signals Based on the Similarity of Time-Frequency Spectra

Geophysics ◽  
2021 ◽  
pp. 1-62
Author(s):  
Wencheng Yang ◽  
Xiao Li ◽  
Yibo Wang ◽  
Yue Zheng ◽  
Peng Guo
Keyword(s):  
Mathematical Morphology ◽  
Signal To Noise Ratio ◽  
Critical Role ◽  
Real Data ◽  
Monitoring Method ◽  
Frequency Spectra ◽  
Arrival Times ◽  
Time Frequency ◽  
Fracturing Process ◽  
Ae Signals

As a key monitoring method, the acoustic emission (AE) technique has played a critical role in characterizing the fracturing process of laboratory rock mechanics experiments. However, this method is limited by low signal-to-noise ratio (SNR) because of a large amount of noise in the measurement and environment and inaccurate AE location. Furthermore, it is difficult to distinguish two or more hits because their arrival times are very close when AE signals are mixed with the strong background noise. Thus, we propose a new method for detecting weak AE signals using the mathematical morphology character correlation of the time-frequency spectrum. The character in all hits of an AE event can be extracted from time-frequency spectra based on the theory of mathematical morphology. Through synthetic and real data experiments, we determined that this method accurately identifies weak AE signals. Compared with conventional methods, the proposed approach can detect AE signals with a lower SNR.

scholarly journals Noise masking method based on an effective ratio mask estimation in Gammatone channels

2018 ◽  
Vol 7 ◽  
Author(s):  
Feng Bao ◽  
Waleed H. Abdulla
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Wiener Filter ◽  
Power Spectra ◽  
Auditory Scene Analysis ◽  
Accurate Estimation ◽  
Noise Power ◽  
Noise Masking ◽  
Time Frequency ◽  
Mask Estimation

In computational auditory scene analysis, the accurate estimation of binary mask or ratio mask plays a key role in noise masking. An inaccurate estimation often leads to some artifacts and temporal discontinuity in the synthesized speech. To overcome this problem, we propose a new ratio mask estimation method in terms of Wiener filtering in each Gammatone channel. In the reconstruction of Wiener filter, we utilize the relationship of the speech and noise power spectra in each Gammatone channel to build the objective function for the convex optimization of speech power. To improve the accuracy of estimation, the estimated ratio mask is further modified based on its adjacent time–frequency units, and then smoothed by interpolating with the estimated binary masks. The objective tests including the signal-to-noise ratio improvement, spectral distortion and intelligibility, and subjective listening test demonstrate the superiority of the proposed method compared with the reference methods.

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