Conventional Time-domain Analysis Research Articles

Investigation of Track Gauge and Alignment Parameters of Ballasted Railway Tracks Based on Real Measurements Using Signal Processing Techniques

This paper deals with the time-frequency characteristic analysis for track geometry irregularities using field data recorded by a comprehensive track inspection train. The parameters of the track gauge and the left and right rail alignment are considered to identify their characteristic wavelengths and the locations of their waveforms. In addition to the conventional time and frequency domain analysis, auto-adaptive signal decomposition techniques are used on four pre-selected track sections. During the time series analysis of the track gauge, the cumulative difference from the mean value is calculated, which makes it possible to distinguish the track section constructed with non-standard initial track gauges. The sensitive wavelengths of the track irregularities are obtained from the proper allocation of wavelength ranges in the Fourier Amplitude Spectrum of the original signal and the Fourier transform of the components detected by the Variational Mode Decomposition. This analysis can elucidate the wavelengths and positions of track irregularities that affect vehicle responses.

Single-trial-based temporal principal component analysis on extracting event-related potentials of interest for an individual subject

Background:Temporal principal component analysis (tPCA) has been widely used to extract event-related potentials (ERPs) at group level of multiple subjects ERP data and it assumes that the underlying factor loading is fixed across participants. However, such assumption may fail to work if latency and phase for one ERP vary considerably across participants. Furthermore, effect of number of trials on tPCA decomposition has not been systematically examined as well, especially for within-subject PCA. New method:We reanalyzed a real ERP data of an emotional experiment using tPCA to extract N2 and P2 from single-trial EEG of an individual. We also explored influence of the number of trials (consecutively increased from 10 to 42 trials) on PCA decomposition by comparing temporal correlation, the statistical result, Cronbach’s alpha, spatial correlation of both N2 and P2 for the proposed method with the conventional time-domain analysis, trial-averaged group PCA, and single-trial-based group PCA. Results:The results of the proposed method can enhance spatial and temporal consistency. We could obtain stable N2 with few trials (about 20) for the proposed method, but, for P2, approximately 30 trials were needed for all methods. Comparison with Existing Method(s):About 30 trials for N2 were required and the reconstructed P2 and N2 were poor correlated across participants for the other three methods. Conclusion:The proposed approach may efficiently capture variability of one ERP from an individual that cannot be extracted by group PCA analysis.

Overcoming the Lead Fiber-Induced Limitation on Pulse Repetition Rate in Distributed Fiber Sensors

Distributed fiber sensor (DFS)-based dynamic sensing has attracted increasing attention thanks to the growing demand in areas such as structural health monitoring and geophysical science. The maximum detectable frequency of DFSs depends on the maximum pulse repetition rate (MPRR), which is limited by the total length of the fiber under test (FUT). In some real-world applications, there is some distance between the interrogator and the monitoring site. Therefore, only a small part of the FUT acts as a sensing fiber (SF), while the other major part just acts as a lead fiber (LF), and the MPRR is limited by the LF and SF. Overcoming the LF-induced extra limitation on the MPRR is a practical problem for many DFS applications. In this paper, to the best of our knowledge, we propose a simple approach for overcoming the LF-induced extra limitation on the MPRR by dividing the DFS interrogator into two parts, for the first time. The proposed approach can be easily implemented for the real-world applicationsof DFSs whose LF is much longer than SF. It has been experimentally validated by using conventional phase-sensitive optical time domain reflectometry and Brillouin optical time domain analysis.

Music and Visual Art Training Increase Auditory-Evoked Theta Oscillations in Older Adults.

Music training was shown to induce changes in auditory processing in older adults. However, most findings stem from correlational studies and fewer examine long-term sustainable benefits. Moreover, research shows small and variable changes in auditory event-related potential (ERP) amplitudes and/or latencies in older adults. Conventional time domain analysis methods, however, are susceptible to latency jitter in evoked responses and may miss important information of brain processing. Here, we used time-frequency analyses to examine training-related changes in auditory-evoked oscillatory activity in healthy older adults (N = 50) assigned to a music training (n = 16), visual art training (n = 17), or a no-treatment control (n = 17) group. All three groups were presented with oddball auditory paradigms with synthesized piano tones or vowels during the acquisition of high-density EEG. Neurophysiological measures were collected at three-time points: pre-training, post-training, and at a three-month follow-up. Training programs were administered for 12-weeks. Increased theta power was found pre and post- training for the music (p = 0.010) and visual art group (p = 0.010) as compared to controls (p = 0.776) and maintained at the three-month follow-up. Results showed training-related plasticity on auditory processing in aging adults. Neuroplastic changes were maintained three months post-training, suggesting music and visual art programs yield lasting benefits that might facilitate encoding, retention, and memory retrieval.

Frequency domain modeling of long-span sea-crossing bridge under stochastic wind and waves

In this study, a frequency domain modeling framework that assembles aero- and hydro-dynamic approaches to characterize the structural motions of a long-span sea-crossing bridge under stochastic wind and waves is proposed as an efficient alternative for the conventional time-consuming time domain analysis. The improved quasi-steady buffeting model is employed to investigate the fluctuating wind actions on structural components and the aero-elastic effect of bridge decks. Potential flow theory associated with constant boundary element method is applied to calculate the linear as well as quadratic hydrodynamic transfer functions and both first- and second-order wave loads are considered and coupled in the modeling framework. The proposed methodology is well validated using a benchwork experiment of a flexible cylinder subjected to wind and waves. The dynamic performance of a long-span sea-crossing bridge under extreme wind and wave conditions is modeled using the proposed framework. The effects of wind and waves, different mode combinations, directionality and nonlinear wave loads on global responses are discussed. In the proposed approach, a combination of only a few main modes is necessary to yield plausible displacement responses of bridge deck, while more modes are required to obtain converged internal force responses.

Comparison study of three-component polarization analysis methods for seismic advanced detection in the roadway

Multicomponent seismic exploration makes up for the shortcomings of multiple solutions in conventional single-component seismic exploration for lithological identification and geological structure interpretation. Polarization analysis methods play a key role in the processing of multicomponent seismic data. However, when multiple types of waves are very close to each other, it is very difficult to characterize the polarization distribution of different waveforms using conventional time domain or time-frequency domain polarization analysis. In this paper, a time-frequency domain instantaneous polarization analysis method based on a time-frequency method of generalized S-transform is introduced. The instantaneous polarization parameters (polarization axis, polarizability, and planarization vector) can be calculated based on a time-frequency spectrum and instantaneous phase of multicomponent signal. The numerical simulation of three-component seismic advanced detection in the three-dimensional space shows the following results: the diffracted P-wave from a fault breakpoint has the characteristics of narrow wave train and fast speed, which make it easy to be identified. Besides, it is an effective wave for polarization analysis due to its distinct polarization characteristics. Combining the advantages of the time-frequency domain analysis method, this method is more accurate in waveform identification and more reliable in fault identification. Besides, this method provides better results than the conventional time-domain polarization analysis method.

The use of variational mode decomposition in assisting sedimentary cyclicity analysis: A case study from an Albian carbonate reservoir, Campos Basin, southeast Brazil

The sedimentary cyclicity analysis investigates the cyclic patterns and the different hierarchical orders of cyclicity in the stratigraphic record. The detection of cyclic depositional patterns is a key element of quantitative stratigraphy. It is often based on well-log data, which can be challenging due to the presence of superimposed cycles and nongeologic artifacts. We have developed an approach to assist the detection of sedimentary cyclicity in well-log signals based on a multiscale spectral analysis method. First, we apply variational mode decomposition to decompose the gamma-ray logs into band-limited subsignals, the intrinsic mode functions (IMFs), to investigate different orders of smoothness, signal-to-noise ratio, and the cyclicity embedded in the geologic record. Conventional time-domain analysis is carried out to understand the general trends in the IMFs, which enables us to better identify long-term cycles associated with transgressive-regressive (T-R) sequences. Then, by appropriately selecting a given IMF and extracting the instantaneous frequency (IF) and its mirrored version, we build a cyclicity log that can map expressive behavior change in the time-frequency domain. Because the IF is more sensitive to the signal variations, we could highlight the short-term cycles throughout the formation in detail. The detected short-term cycles are in agreement with the T-R sequence. We apply our method to the Albian carbonate succession of Macaé Group, Campos Basin, Brazil. We understand that our method can be a valuable tool for semiautomated detection of sedimentary cycles, assisting in the characterization of different hierarchical orders of cyclicity.

Sampling Rate Effects on Resting State fMRI Metrics.

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning.

Subdivision of Brillouin gain spectrum to improve the spatial resolution of a BOTDA system.

A pulse subdivision analysis method was developed to improve the spatial resolution of a conventional long pump pulse Brillouin optical time domain analysis (BOTDA) system. An exclusive photodetector was used to obtain the accurate energy distribution along the long pulse, based on which the long pulse was subdivided into several sub-pulses with certain energy weights. With these energy weights, the Brillouin spectrum generated by the long pulse was subdivided into equal numbers of sub-spectra. Each sub-spectrum could provide detailed sensing information about a fiber sub-segment related to a sub-pulse. Thus, the actual spatial resolution of the BOTDA system was determined by the sub-pulse instead of the long pulse. As a result, spatial resolution was increased by several times, depending on the subdivision multiples. The method was theoretically simulated and experimentally demonstrated. For experimental demonstration, the recognization capability of the melting point of two different fiber sections and the discrete strain distribution on a sensing fiber were respectively tested. For melting point recognization, thanks to five-multiple subdivision, a 1m spatial resolution over 31km sensing fiber was realized using a 50ns pump pulse. For the strain sensing test, ten-multiple subdivision was performed to distinguish two 0.5m stretched fiber sections with a 0.2m interval using a 20ns pump pulse. The spatial resolution is 0.2m, which is a ten times' improvement compared with that before subdivision analysis. Due to its simplicity and cost-effectiveness, the method is believed to have extensive application prospects in distributed fiber sensing fields.

Determination of average times for Brillouin optical time domain analysis sensor denoising by non-local means filtering

Integration of signal average and image restoration can improve the performance of distributed optical fiber sensors. Here we illustrate the denoising behavior of non-local means filtering (NLM) affected by number of average. On the one hand, the signal average can effectively remove the high-frequency noise but be time-consuming; on the other hand, the NLM can accelerate decent in noise but is dependent on level of noise contained in raw sensing image. To best of our knowledge, this is the first time to apply NLM to conventional Brillouin optical time domain analysis sensor (BOTDA) with theoretically spatial resolution of 10 ns. Moreover, we propose an optimal averaging number determination method for further denoising by NLM to achieve trade-off between accuracy and average times. The results indicated that the optimal-times for BOTDA configured 10 ns and 10km fiber-loop is 13 with Brillouin frequency shift uncertainty of 0.85MHz. The proposed method has potential to apply in engineering applications and commercialized software for BOTDA denoising by image restoration.

Steady-state anti-plane shear wave scattering by a crack with friction.

The present article describes the steady-state numerical modeling of anti-plane shear wave scattering by a crack with frictional boundary conditions. The system is composed of an unbounded elastic solid that includes a closed crack under static compressive stress. A time-harmonic anti-plane shear wave is incident, and dynamic friction between the crack faces is induced as a nonlinear phenomenon. The anti-plane wave scattering can be described in a retarded potential integral equation by taking the nonlinearity into account. The present article introduces the steady-state expression as an asymptotic vibration of crack faces after a sufficient elapsed time. In order to solve the equations describing nonlinear steady-state vibration, a harmonic balance method is integrated into a boundary element method. Fourier coefficients of crack opening displacement distributed on the crack face are treated as unknown variables. The system of nonlinear equations is solved by means of a numerical continuation method. The present numerical results show almost complete agreement with those obtained by the conventional time-domain analysis after a sufficient elapsed time. Furthermore, the robustness and effectiveness of the proposed method are demonstrated numerically.

Compensation Strategy of the Numerical Analysis in Frequency Domain on Induction Motor Considering Magnetic Flux Saturation

Numerical analysis in frequency-domain guarantees convincing accuracy by reflecting non-linearity of material without massive computation time, combining advantages of the equivalent circuit method and numerical analysis method. However, at highly magnetic saturated regions where non-linearity of the material is severe, error in torque calculation is evident, as parameters in frequency domain are presumed to be in a sinusoidal condition. Many researchers have been suggested a compensating method by creating fictious material with logically modified B-H curve. Nevertheless, the error between the results of the numerical analysis in frequency-domain and time-domain analysis is not small enough to estimate motor characteristic. Therefore, the compensation method for improving accuracy on the estimation of induction motor characteristics is proposed in this paper. The numerical analysis based on finite-element method in frequency domain has been conducted using the proposed fictious material and the result is compared to those of the conventional methods and time-domain analysis to validate its improvement on accuracy.

A case study on Discrete Wavelet Transform based Hurst exponent for epilepsy detection

Epileptic seizures are manifestations of epilepsy. Careful analysis of EEG records can provide valuable insight and improved understanding of the mechanism causing epileptic disorders. The detection of epileptic form discharges in EEG is an important component in the diagnosis of epilepsy. As EEG signals are non-stationary, the conventional frequency and time domain analysis does not provide better accuracy. So, in this work an attempt has been made to provide an overview of the determination of epilepsy by implementation of Hurst exponent (HE)-based discrete wavelet transform techniques for feature extraction from EEG data sets obtained during ictal and pre ictal stages of affected person and finally classifying EEG signals using SVM and KNN Classifiers. The The highest accuracy of 99% is obtained using SVM.

Full scale strain monitoring of a suspension bridge using high performance distributed fiber optic sensors

This paper investigated field monitoring of a 1108 m suspension bridge during an assessment load test, using integrated distributed fibre-optic sensors (DFOSs). In addition to the conventional Brillouin time domain analysis system, a high spatial resolution Brillouin system using the differential pulse-width pair (DPP) technique was adopted. Temperature compensation was achieved using a Raman distributed temperature sensing system. This is the first full scale field application of DFOSs using the Brillouin time domain analysis technique in a thousand-meter-scale suspension bridge. Measured strain distributions along the whole length of the bridge were presented. The interaction between the main cables and the steel-box-girder was highlighted. The Brillouin fibre-optic monitoring systems exhibited great facility for the purposes of long distance distributed strain monitoring, with up to 0.05 m spatial resolution, and 0.01 m/point sampling interval. The performance of the Brillouin system using DPP technique was discussed. The measured data was also employed for assessing bridge design and for the assessment of structural condition. The results show that the symmetrical design assumptions were consistent with the actual bridge, and that the strain values along the whole bridge were within the safety range. This trial field study serves as an example, demonstrating the feasibility of highly dense strain and temperature measurement for large scale civil infrastructures using integrated DFOSs.

Robust extraction of the N1-effect in dichotic listening using hardy space mappings of auditory late single trials.

It is known that signs of (early) auditory selective attention are reflected in the N1-wave of auditory late potentials. In recent years, we have analyzed this N1-effect using multiscale neurofunctional modeling and (instantaneous) phase synchronization measures of Hardy space mapped data. To acquire the electroencephalographic data in dichotic listening, we repeated the seminal experiment of Hillyard et al. which first described the N1-effect. Here we apply for the first time phase synchronization measures to these dichotic data and compare the results to the conventional time-domain analysis. Our results suggest that a single trial synchronization analysis of the instantaneous phase at the α/θ-border shows the N1-attention effect even more clear than the original averaged time-domain representation. It is concluded that the presented method is a robust tool to analyse (early) signs of selective attention in dichotic listening tasks.

Comparative assessment of the harmonic balance Navier–Stokes technology for horizontal and vertical axis wind turbine aerodynamics

Several important wind turbine unsteady flow regimes, such as those associated with the yawed wind condition of horizontal axis machines, and most operating conditions of all vertical axis machines, are predominantly periodic. The harmonic balance Reynolds-averaged Navier–Stokes technology for the rapid calculation of nonlinear periodic flow fields has been successfully used to greatly reduce runtimes of turbomachinery periodic flow analyses in the past fifteen years. This paper presents an objective comparative study of the performance and solution accuracy of this technology for aerodynamic analysis and design applications of horizontal and vertical axis wind turbines. The considered use cases are the periodic flow past the blade section of a utility-scale horizontal axis wind turbine rotor in yawed wind, and the periodic flow of a H-Darrieus rotor section working at a tip-speed ratio close to that of maximum power. The aforementioned comparative assessment is based on thorough parametric time-domain and harmonic balance analyses of both use cases. The paper also reports the main mathematical and numerical features of a new turbulent harmonic balance Navier–Stokes solver using Menter’s shear stress transport model for the turbulence closure. Presented results indicate that (a) typical multimegawatt horizontal axis wind turbine periodic flows can be computed by the harmonic balance solver about ten times more rapidly than by the conventional time-domain analysis, achieving the same temporal accuracy of the latter method, and (b) the harmonic balance acceleration for Darrieus rotor unsteady flow analysis is lower than for horizontal axis machines, and the harmonic balance solutions feature undesired oscillations caused by the wide harmonic content and the high-level of stall predisposition of this flow field type.

Extraction of response waveforms of heartbeat and blood pressure to swallowing. Using mixed signal processing of time domain and respiratory phase domain.

Evaluating the accurate responses of the cardiovascular system to external stimuli is important for a deeper understanding of cardiovascular homeostasis. However, the responses should be distorted by the conventional time domain analysis when a frequency of the effect of external stimuli matches that of intrinsic fluctuations. The purpose of this study is to propose a mixed signal processing of time domain and respiratory phase domain to extract the response waveforms of heartbeat and blood pressure (BP) to external stimuli and to clarify the physiological mechanisms of swallowing effects on the cardiovascular system. Measurements were conducted on 12 healthy humans in the sitting and standing positions, with each subject requested to swallow every 30 s between expiration and inspiration. Waveforms of respiratory sinus arrhythmia (RSA) and respiratory-related BP variations were extracted as functions of the respiratory phase. Then, respiratory effects were subtracted from response waveforms with reference to the respiratory phase in the time domain. As a result, swallowing induced tachycardia, which peaked within 3 s and recovered within 8 s. Tachycardia was greater in the sitting position than during standing. Furthermore, systolic BP and pulse pressure immediately decreased and diastolic BP increased coincident with the occurrence of tachycardia. Subsequently, systolic BP and pulse pressure recovered faster than the R-R interval. We conclude that swallowing-induced tachycardia arises largely from the decrease of vagal activity and the baroreflex would yield fast oscillatory responses in recovery.

Clinical usefulness and feasibility of time-frequency analysis of chemosensory event-related potentials

The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.

An investigation into diesel engine air-borne acoustics using continuous wavelet transform

The emitted acoustic signals from diesel engines carry useful indicators about their operating conditions and health status. Unfortunately, those signals are very complex, contain numerous numbers of sources and corrupted by subnational amount of noise. This makes it difficult to extract those condition indicators via the use of conventional time and frequency domain analysis techniques. This paper studies the characteristics of diesel engine air-borne acoustic signals using time-frequency domain techniques. One analysis technique is investigated; continuous wavelet transform (CWT). First, some of the mathematical background of the CWT is reviewed. Second, the detection capabilities of this technique are evaluated using air-borne acoustic signals collected from diesel engine in acoustically untreated laboratory. Consequently, some engine operating conditions and faults are investigated using the CWT techniques. The achieved results prove the technique’s sensitivity to engine speed and load variations. More important the CWT shows excellent capabilities in detecting engine’s injection process and lubrication related faults at early stages.

Time-lapse wave-equation migration velocity analysis

Time-lapse (4D) analysis of seismic data acquired at different stages of hydrocarbon production or gas/fluid injection has been very successful at imaging detailed reservoir changes. Conventional time-domain analysis of 4D data sets usually assumes a linear perturbation about a reference baseline earth model. However, this assumption is violated when production/injection significantly alters the subsurface generating large 4D velocity changes, time shifts, and complicated 4D wavefield coda, necessitating a more robust 4D analysis involving prestack wave-equation depth migration and velocity analysis. We address these situations by extending conventional 3D wave-equation migration velocity analysis (WEMVA) based on one-way wave-equations and single-scattering theory to 4D velocity estimation using a “parallel” inversion approach involving parallel solution of two separate inversion problems. Recognizing that the 4D WEMVA strategy requires precomputed baseline/monitor image-difference volumes, we develop an approximate 4D WEMVA technique that replaces these differences with a single weight function derived from the smooth background time-lapse image difference. We demonstrate the usefulness of the parallel and an approximate 4D WEMVA approach using a synthetic time-lapse [Formula: see text] geosequestration experiment that requires inverting for a thin-layer velocity change derived from [Formula: see text] injection in an analogue North Sea reservoir. The parallel 4D WEMVA solutions generate an excellent high-resolution velocity estimates, whereas the approximate methods recover lower-resolution estimates with magnitudes that must be rescaled through a post-inversion gradient line-search.