scholarly journals Evolutionary Spectra Estimation of Field Measurement Typhoon Processes Using Wavelets

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-Dong Zhou ◽  
You-Liang Ding ◽  
Ai-Qun Li
Keyword(s):  
Estimation Method ◽  
Engineering Application ◽  
Frequency Component ◽  
Time Frequency ◽  
Whole Process ◽  
Power Spectral ◽  
Frequency Domains ◽  
Definition Of ◽  
Evolutionary Spectra ◽  
Oscillatory Processes

This paper presents a wavelet-based method for estimating evolutionary power spectral density (EPSD) of nonstationary stochastic oscillatory processes and its application to field measured typhoon processes. The EPSD, which is deduced in a closed form based on the definition of the EPSD and the algorithm of the continuous wavelet transform, can be formulated as a sum of squared moduli of the wavelet functions in time domain modulated by frequency-dependent coefficients that relate to the squared values of wavelet coefficients and two wavelet functions with different time shifts. A parametric study is conducted to examine the efficacy of the wavelet-based estimation method and the accuracy of different wavelets. The results indicate that all of the estimated EPSDs have acceptable accuracy in engineering application and the Morlet transform can provide desirable estimations in both time and frequency domains. Finally, the proposed method is adopted to investigate the time-frequency characteristics of the Typhoon Matsa measured in bridge site. The nonstationary energy distribution and stationary frequency component during the whole process are found. The work in this paper may promote an improved understanding of the nonstationary features of typhoon winds.

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 On a new Wigner-Ville distribution associated with linear canonical transform

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Hong-Cai Xin ◽  
Bing-Zhao Li
Keyword(s):  
Modulation Frequency ◽  
Computational Cost ◽  
Estimation Method ◽  
Superior Performance ◽  
Linear Canonical Transform ◽  
Two Phase ◽  
Cross Term ◽  
Time Frequency ◽  
Definition Of ◽  
Non Stationary Signal

AbstractLinear canonical transform as a general integration transform has been considered into Wigner-Ville distribution (WVD) to show more powerful ability for non-stationary signal processing. In this paper, a new WVD associated with linear canonical transform (WVDL) and integration form of WVDL (IWVDL) are presented. First, the definition of WVDL is derived based on new autocorrelation function and some properties are investigated in details. It removes the coupling between time and time delay and lays the foundation for signal analysis and processing. Then, based on the characteristics of WVDL over time-frequency plane, a new parameter estimation method, IWVDL, is proposed for linear modulation frequency (LFM) signal. Two phase parameters of LFM signal are estimated simultaneously and the cross term can be suppressed well by integration operator. Finally, compared with classical WVD, the simulation experiments are carried out to verify its better estimation and suppression of cross term ability. Error analysis and computational cost are discussed to show superior performance compared with other WVD in linear canonical transform domain. The further application in radar imaging field will be studied in the future work.

scholarly journals Transient Modeling and Recovery of Non-Stationary Fault Signature for Condition Monitoring of Induction Motors

2021 ◽  
Vol 11 (6) ◽  
pp. 2806
Author(s):  
Bilal Asad ◽  
Toomas Vaimann ◽  
Anouar Belahcen ◽  
Ants Kallaste ◽  
Anton Rassõlkin ◽  
...  
Keyword(s):  
Function Analysis ◽  
Diagnostic Algorithm ◽  
Efficient Utilization ◽  
Transient Time ◽  
Time Frequency ◽  
Motor Current ◽  
Laboratory Setup ◽  
Rotor Faults ◽  
Power Spectral ◽  
Definition Of

This paper presents the modeling and the broken rotor bar fault diagnostics by time–frequency analysis of the motor current under an extended startup transient time. The transient current-based nonstationary signal is retrieved and investigated for its time–frequency response to segregate the rotor faults and spatial harmonics. For studying the effect of reduced voltage on various parameters and the theoretical definition of the fault patterns, the winding function analysis (WFA)-based model is presented first. Moreover, an algorithm to improve the spectrum legibility is proposed. It is shown that by efficient utilization of the attenuation filter and consideration of the area containing the maximum power spectral density, the diagnostic algorithm gives promising results. The results are based on the machine’s analytical model and the measurements taken from the laboratory setup.

Signal Processing and Engineering Application of Ground Penetrating Radar (GPR) Based on Multi-Wavelet Transformation

2015 ◽  
Vol 729 ◽  
pp. 199-207
Author(s):  
Zhi Le Shu ◽  
Shan Huang ◽  
Bao Xian Liu ◽  
Ke Xu
Keyword(s):  
Fourier Transformation ◽  
Wavelet Transformation ◽  
Engineering Application ◽  
Image Resolution ◽  
Main Concern ◽  
Time Frequency ◽  
Definition Of ◽  
The Time Domain ◽  
Filtering Effect ◽  
Target Characteristics

In tunnel lining quality testing and advanced geological forecasting, the main concern is the local signals, such as the position and form of defects or the unusual mutations; while all kinds of filtering methods based on Fourier transformation reflect the overall characteristics of the signals, but can not describe the time-frequency local properties of the signals; however, the characteristics of the multi-resolution based on the wavelet transformation have the ability to show the local characteristics of the signals in terms of the time domain and frequency domain; based on the analysis of multi-wavelet theory, the paper infers the decomposition and reconstruction of CL4 multi-wavelet, discusses the necessity of multi-wavelet preprocessing and conducts the equalization treatment of CL4 multi-wavelet, realizes CL4 balanced multi-wavelet threshold filtering algorithm based on the application of MATLAB language programming, and compares with the traditional filtering effect based on Fourier transformation; the results show that the both conventional filter and CL4 balanced multi-wavelet filter can clearly distinguish the unusual targets; but the target characteristics through multi-wavelet transformation are enhanced; the lineups are clearer, the noises are removed more thoroughly, the signals are reserved more completely and the images become “clearer”. The multi-wavelet transformation provides good assistance for improvement in GPR image resolution and the definition of the target detection image, and achieves better filtering effect.

scholarly journals A Survey of Candidate Waveforms for beyond 5G Systems

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Filipe Conceição ◽  
Marco Gomes ◽  
Vitor Silva ◽  
Rui Dinis ◽  
Adão Silva ◽  
...  
Keyword(s):  
Average Power ◽  
Downlink Transmission ◽  
Advantages And Disadvantages ◽  
Air Interface ◽  
Power Spectral ◽  
Frequency Domains ◽  
Flexible Resource ◽  
Increasing Demand ◽  
Definition Of ◽  
Key Aspects

The 5G and beyond future wireless networks aim to support a large variety of services with increasing demand in terms of data rate and throughput while providing a higher degree of reliability, keeping the overall system complexity affordable. One of the key aspects regarding the physical layer architecture of such systems is the definition of the waveform to be used in the air interface. Such waveforms must be studied and compared in order to choose the most suitable and capable of providing the 5G and beyond services requirements, with flexible resource allocation in time and frequency domains, while providing high spectral and power efficiencies. In this paper, several beyond 5G waveforms candidates are presented, along with their transceiver architectures. Additionally, the associated advantages and disadvantages regarding the use of these transmission techniques are discussed. They are compared in a similar downlink transmission scenario where three main key performance indicators (KPIs) are evaluated. They are the peak-to-average power ratio, the overall system spectral efficiency (wherein the out of band emissions are measured, along with the spectral confinement of the power spectral density of the transmitted signals) and the bit error rate performance. Additionally, other KPIs are discussed.

scholarly journals Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Guang-Dong Zhou ◽  
You-Liang Ding ◽  
Ai-Qun Li
Keyword(s):  
Wavelet Transform ◽  
Closed Form ◽  
Time Domain ◽  
Estimation Method ◽  
Time Instant ◽  
Oscillatory Process ◽  
Wavelet Coefficients ◽  
The Fourier Transform ◽  
Definition Of ◽  
Evolutionary Spectra

Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD) of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.

Evolutionary Spectra Estimation of a Nonstationary Process Based on a Single Sample

2019 ◽  
Vol 19 (12) ◽  
pp. 1950151 ◽  
Author(s):  
Zifeng Huang ◽  
Ming Gu
Keyword(s):  
Numerical Study ◽  
Estimation Method ◽  
Nonstationary Process ◽  
Single Sample ◽  
Spectrum Estimation ◽  
Time Varying ◽  
Power Spectral ◽  
Novel Method ◽  
Evolutionary Spectra ◽  
Short Time

This paper proposes a novel method for estimating the evolutionary power spectral density (EPSD) of a nonstationary process based on a single sample. In the proposed method, a sample of a nonstationary process is decomposed into several components with a new binomial fitting decomposition (BFD). The EPSD of each component can be estimated using a newly proposed time-varying standard deviation estimation method and short-time Thomson multiple-window spectrum estimation method. The EPSD of the analyzed nonstationary sample is obtained by combining the EPSDs of all components. Via a comprehensive numerical study, the applicability of the proposed EPSD estimation method (for estimating the EPSD of a nonstationary process) is analyzed and compared with those by the Priestley method and wavelet-based method. The numerical results indicate that the estimated EPSD by the proposed method is more consistent with the corresponding theoretical one than those by the other two methods. Finally, the EPSDs of Storm Ampil, measured atop the Shanghai World Financial Center, are analyzed by the proposed method.

Estimation of Failure Probability for Bearing and its Applications in the Case of Zero-Failure Data

2014 ◽  
Vol 915-916 ◽  
pp. 318-322 ◽  
Author(s):  
Ming Han
Keyword(s):  
Bayesian Estimation ◽  
Failure Probability ◽  
Estimation Method ◽  
Engineering Application ◽  
New Method ◽  
Hierarchical Bayesian ◽  
Failure Data ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

This paper introduces a new method, named E-Bayesian estimation method, to estimate failure probability. In the case of zero-failure data, the definition of E-Bayesian estimation of failure probability is provided; moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation and the property of E-Bayesian estimation of the failure probability are also provided. For the estimate failure probability, in the following sections we will see simple the E-Bayesian estimation method is method than hierarchical Bayesian estimation method. Finally, the calculated results of bearing show that the proposed method is feasible and convenient in engineering application.

scholarly journals Electrophysiological Correlates of Virtual-Reality Applications in the Rehabilitation Setting: New Perspectives for Stroke Patients

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 836
Author(s):  
Francesco Arcuri ◽  
Camillo Porcaro ◽  
Irene Ciancarelli ◽  
Paolo Tonin ◽  
Antonio Cerasa
Keyword(s):  
Virtual Reality ◽  
Brain Plasticity ◽  
Eeg Signal ◽  
Stroke Patients ◽  
Time Frequency ◽  
Non Invasive ◽  
Power Spectral ◽  
Frequency Domains ◽  
Multisensory Training ◽  
Vr Training

Here we reviewed the last evidence on the application of electroencephalography (EEG) as a non-invasive and portable neuroimaging method useful to extract hallmarks of neuroplasticity induced by virtual reality (VR) rehabilitation approaches in stroke patients. In the neurorehabilitation context, VR training has been used extensively to hamper the effects of motor treatments on the stroke’s brain. The concept underlying VR therapy is to improve brain plasticity by engaging users in multisensory training. In this narrative review, we present the key concepts of VR protocols applied to the rehabilitation of stroke patients and critically discuss challenges of EEG signal when applied as endophenotype to extract neurophysiological markers. When VR technology was applied to magnify the effects of treatments on motor recovery, significant EEG-related neural improvements were detected in the primary motor circuit either in terms of power spectral density or as time-frequency domains.

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

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