Calculation Of Power Spectral Density Research Articles

The evaluation for plasma noise in arbitrary time-delay interferometry combinations

The laser interferometer space antenna (LISA) uses laser interferometry to measure gravitational wave-induced distance changes between freely falling test masses on separate spacecraft. In practice, the space-borne gravitational wave detector operates in a plasma medium, and subsequently, the variations in electron density affect the refractive index and add displacement noise to measurements. Geometric time-delay interferometry (TDI) is the TDI combinations searched by geometric method, which is employed to mitigate overwhelming laser phase noise. This study explores all forty-five second-generation geometric TDI combinations up to sixteen links, analyzing plasma noise effects via power spectral density and cross-spectral density calculations for different optical links. Our findings reveal that plasma noise can exceed the noise floor, which comprises optical metrology system and test mass acceleration noise, in certain low-frequency regions due to different noise transfer behaviors. Further, we establish electron density requirements for various TDI combinations, showing that densities below 100cm−3/Hz @ 10mHz satisfy LISA’s criteria across all forty-five combinations. This allows for optimized TDI selection based on specific plasma densities.

An Assessment of Persistent Acoustic Monitoring of a Nuclear Reactor during Full Power Generation

Persistent low-frequency (<180 Hz) acoustic detection took place within the boundaries of Oak Ridge National Laboratory to monitor full power operations of the High Flux Isotope Reactor. Three acoustic sensors were installed at distances of 69, 101, and 914 m from the northeast corner of the cooling towers to monitor and assess four reactor power generation cycles. Features were extracted from power spectral density calculations where data were collected during reactor on and off operations. Diverse spectral features were present during full reactor power, including a 21.4 Hz fundamental frequency and ascending harmonics. Using bandpass filters, these related frequencies were isolated and summed, and the root mean square energy was calculated. The method of isolating and summing characteristic features provided a significant improvement in identifying acoustic behavior related to reactor power when the raw signals were obscured by noise.

Using electroencephalography to analyse drivers' different cognitive workload characteristics based on on-road experiment.

Driver's cognitive workload has an important impact on driving safety. This paper carries out an on-road experiment to analyse the impact from three innovative aspects: significance analysis of electroencephalogram (EEG) under different cognitive workloads, distribution of EEG maps with different frequency signals and influence of different cognitive workloads on driving safety based on EEG. First, the EEG signals are processed and four frequencies of delta, theta, alpha and beta are obtained. Then, the time-frequency transform and power spectral density calculation are carried out by short-time Fourier to study the correlation of each frequency signal of different workload states, as well as the distribution pattern of the EEG topographic map. Finally, the time and space energy and phase changes in each cognitive task event are studied through event-related spectral perturbation and inter-trial coherence. Results show the difference between left and right brains, as well as the resource occupancy trends of the monitor, perception, visual and auditory channels in different driving conditions. Results also demonstrate that the increase in cognitive workloads will directly affect driving safety. Changes in cognitive workload have different effects on brain signals, and this paper can provide a theoretical basis for improving driving safety under different cognitive workloads. Mastering the EEG characteristics of signals can provide more targeted supervision and safety warnings for the driver.

Extended harmonic input method for response spectrum determination of vehicle–bridge systems

The calculation of response power spectral densities (PSDs) from the excitation PSDs of vehicle–bridge (VB) systems is crucial for the safety evaluation of operating vehicles, bridge fatigue analysis, and vibration control optimization. However, calculations using the available methods result in considerable computational errors when applied to evaluate the response PSDs of VB systems. Hence, an extended harmonic input method (HIM) is proposed to compute the time-varying response spectrum in VB systems. First, the unique characteristics of VB systems that may cause the inapplicability of conventional methods are systematically analyzed. Subsequently, an extended version of the HIM is mathematically established to calculate the time-varying response spectrum of VB systems via the representation of inputs and decomposition of responses. Finally, a numerical example of an actual high-speed railway bridge subjected to track irregularities or seismic excitations is presented to illustrate the efficacy of the novel method.

Influence of PSD Estimation Parameters on Fatigue Life Prediction in Spectral Method.

The paper analyzes in detail the influence of the Welch method on the estimation of fatigue life in the frequency domain. The aim is to examine how the setting of parameters, such as window size, weighting and overlap, affects the calculation of power spectral density (PSD) and thus lifetime. The paper uses knowledge from the theory of signal processing, statistics and fatigue life estimation in the frequency domain. In order to demonstrate the general validity of the conclusions, four different reference PSD spectra are generated and examined. The spectra are converted to time histories using an inverse fast Fourier transform and then used as input (measured) data for the Welch method. The PSD thus obtained are subsequently subjected to lifetime estimation using the Dirlik and Tovo-Benasciutti models. Based on the obtained results, it was found that the best configuration of the parameters of the Welch method for fatigue calculations is the selection of the smallest possible time window (maximum 60% of the observation length) and the largest possible overlap (minimum 70% of the window size).

Effects of geometric track irregularities on vehicle dynamic behaviour when running through a turnout

Railway vehicle dynamics is strongly affected by track irregularities, which can influence the safety and the running behaviour of the vehicle. The EN 13848-5:2017 standard provides the limits of track irregularities for standard track but does not states specific restrictions for switches and crossings. Furthermore, since turnouts have a limited length, their track geometric irregularities cannot be accurately described by stochastic functions usually adopted for railway vehicle dynamics simulations. Nevertheless, irregularities in railway turnouts, related to the non-uniform stiffness of the track support and to the variation of the rail profiles along the longitudinal direction should be considered in dynamic simulations, as they can generate large dynamic loads, strongly affecting the vehicle dynamics and running stability. The aim of the paper is to expand the Switches and Crossing benchmark exercise analysing the effect of several kinds of irregularity with different wavelengths and amplitudes on a complete turnout on the main quantities related to the vehicle dynamics. The influence of each defect on each quantity is estimated through a post-processing sensitivity analysis based on power spectral density calculation. This sensitivity analysis is hence used to combine different types of defects in order to detect irregularity combinations that could compromise running safety.

Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

Performance vs. Spectral Properties for Single-Sideband Continuous Phase Modulation

This study revokes the performance of continuous phase modulation (CPM) able to generate a single-sideband (SSB) spectrum directly. This signal is analyzed in terms of modulation indices, pulse lengths, and pulse widths, all of which affect error probability, bandwidth, SSB property, and receiver complexity. The error probability performance is based on an approximation of the minimum Euclidean distance. A numerical power spectral density calculation for this particular SSB modulation in terms of the modulation index is presented. Reasonable tradeoffs in designing modulation schemes have been proposed using multi-objective optimization to ensure sizable improvements in bit error rate (BER), spectral efficiencies, and complexity without losing the property of being a SSB signal. Performance comparisons are made with known CPM schemes, e.g., Gaussian Minimum Shift Keying (GMSK) and Raised Cosine based CPM (RC).

Experimental investigation of supercritical carbon dioxide non-equilibrium condensation in a highly unsteady environment

The current work presents a study of qualitative relationships between the flow unsteadiness, induced by nozzle geometry variation, and non-equilibrium condensation behavior at high temporal scales for supercritical carbon dioxide (sCO2) flow. A closed sCO2 loop facility is used to drive a supercritical carbon dioxide flow through a rectangular converging–diverging channel. As the flow traverses through the channel, it experiences a local pressure reduction in a stalled region, eventually leading to non-equilibrium condensation of the working fluid. The flow is visualized using high-speed shadowgraphy and schlieren techniques to characterize the unsteady flow dynamics at the diverging section of the nozzle. Spectral information of the condensation behavior is retrieved from the optical diagnostics using power spectral density calculations, revealing multiple dominant frequencies in the diverging section of the nozzle. Three different nozzles are studied to understand how these dominant frequencies of condensation phenomenon change with respect to the nozzle geometry. Each nozzle design is distinguished with a unique dominant frequency, which is significantly impacted by the effect of flow throat velocity and the degree of adverse pressure gradient. Nozzles with divergence of 15° shows a dominant frequency in the range of 5 – 6.25 kHz in condensing behavior while nozzles with 6° divergence exhibited half the frequency of the phase change. These effects resulted from the extent of adverse pressure gradient imposed by the divergence angle of the nozzle. Additionally, these dominant frequencies are also compared to the wall-pressure signals acquired from high-frequency pressure transducers. Spectral analysis of wall-pressure signals, which are directly linked to nozzle designs, reveals a strong coupling between the condensation behavior and the wall-pressures.

Power Spectral Density Computation and Dominant Frequencies Identification from the Vibration Sensor Output under Random Vibration Environment

The objective of the modal and spectral analysis is to determine the vibration characteristics of structures such as natural frequencies, dominant frequencies and mode shapes. Such modal and spectral analyses have major relevance to the study of the dynamic properties of the structures undergoing dynamic vibration. Methods for the estimation of the power spectral density and identification of the dominant frequencies from the sensor responses under random vibrating environment are presented in this paper. Periodogram using FFT, Welch Method and MUSIC algorithm are used to analyse the known frequency sinusoids with additive white noise and output of the vibration sensor mounted on the test object. The resultant spectra obtained using the methods and their corresponding errors with the reference spectrum are analysed. The Welch method is further studied with three different windows, namely, Hann, Hamming and Blackman-Harris and with three different overlapping criteria viz. 0%, 25% and 50%. The same algorithm and methodology were adopted and compared in two different platforms: Mathematical Model Simulation and Hardware-In-Loop-Simulation. It is observed from the results that Welch Method with 25% overlap used in combination either with Hann or Blackman-Harris window yields more accurate results, compared to other combinations. Also, 25% overlap provides better execution time trade-off compared to 50% overlap.

Source levels and propagation modelling of whistles from a free-ranging rough-toothed dolphin

A lone adult individual of rough-toothed-dolphin had its acoustic behavior recorded with a calibrated system (Fostex FR22: 192 kHz sampling rate; C54 hydrophone: -165.0 dBV, 0.009 Hz–100 kHz). Moments when the animal approached and faced the hydrophone were noted. Whistles were counted in Raven 1.6 (Hann window, 512, 50% overlap). Duration (ms), minimum, maximum and peak frequencies (kHz), number of steps and step frequency (kHz) were extracted of whistles emitted when the animal was in a 1-m radius of the hydrophone. Source levels (SL) were estimated through power spectral density calculation in Matlab. SL at frequency parameters and at each whistle step were extracted and used in bellhop propagation models of a coastal scenario. 63 whistles were emitted within 1m. Frequencies ranged from 1.2 to 9.7 kHz and duration from 115.3 to 825.6 ms. Frequency and SL increased with step number, with 4.5 steps per whistle. Minimum frequencies (1.9 ± 0.6 kHz) had smaller SL (125.2 ± 4.2 dB re 1 μPa) and decreased to 100 dB before 500 m. Peak frequencies (6.7 ± 1.0 kHz) had mean SL of 149.5 ± 8.5 dB re 1 μPa and reached 2500 m with 100 dB. Higher frequencies reached longer distances and depths.

PSD based high impedance fault detection and classification in distribution system

The recent progress in the area of signal processing has led to the development of intelligent schemes for fault classification and faulty phase selection in distribution system. The conventional algorithms find limitations to detect high impedance fault (HIF) and HIF remains a great concern for utilities as it can cause serious danger and accident if not detected properly. This study presents an algorithm for the detection and classification of HIF in a multi-feeder radial distribution system based on the calculation of power spectral density of faulty current signals. Discrete wavelet transform has been used to decouple the time information from the frequency information to detect and classify HIF effectively. The proposed technique has been extensively assessed under various dynamic situations including the presence of distributed generation and nonlinear load. This technique does not involve any training or learning process nor it involves any concern about data synchronization. The fault detection time is improved as it requires only half cycle of post fault current signal to detect and classify faults successfully. It is noteworthy to mention that the proposed technique considers only one end terminal current data. The comparative assessment reveals that this method can overcome the limitations of other existing techniques.

Method of vibration power spectral density calculation for spacecraft attached large-size and small-mass equipment units

During the lift-off and the ascent phase, spacecraft (SC) large-size attached equipment is impacted by intensive vibrations, largely due to acoustic pressures. To ensure a reliable in-orbit operation of all SC systems the modes of vibration loads shall be assessed as much as reliable (using experimentally-confirmed mathematical models). Determination of the vibroacoustic response parameters of the equipment structure is a very important issue for such equipment units (elements) which have a large surface square with a relatively small mass. Among such structures are folded solar arrays (SA) and reflector type antennae dishes (ART). The purpose of this study is to validate the calculation methodology of vibration power spectral density (PSD) for low and medium frequency band (25-400 Hz), and apply it for the aforesaid structures in the lift-off and flight phases as part of the integrated launch vehicle in the area of maximum ram effects, when the acoustic pressure levels, and therefore their impact on the vibroacoustic response of these structures are maximum. The target goal has been implemented using the example of the solar array and reflector type antenna being used in the spacecraft power supply system and onboard radio system of one of RSC Energia-developed spacecraft. Key words: environment air, spacecraft, solar array, reflector type antennae dish, dynamic model, sound pressure level, acoustic pressure, structure vibroacoustic response.

Automated wireless monitoring system for cable tension forces using deep learning

As demand for long-span bridges is increasing worldwide, effective maintenance has become a critical issue to maintain their structural integrity and prolong their lifetime. Given that a stay-cable is the principal load-carrying component in cable-stayed bridges, monitoring tension forces in stay-cables provides critical data regarding the structural condition of bridges. Indeed, various methodologies have been proposed to measure cable tension forces, including the magneto-elastic effect-based sensor technique, direct measurement using load cells, and indirect tension estimation based on cable vibration. In particular, vibration-based tension estimation has been widely applied to systems for tension monitoring and is known as a cost-effective approach. However, full automation under different cable tension forces has not been reported in the literature thus far. This study proposes an automated cable tension monitoring system using deep learning and wireless smart sensors that enables tension forces to be estimated. A fully automated peak-picking algorithm tailored to cable vibration is developed using a region-based convolution neural network to apply the vibration-based tension estimation method to automated cable tension monitoring. The developed system features embedded processing on wireless smart sensors, which includes data acquisition, power spectral density calculation, peak-picking, post-processing for peak-selection, and tension estimation. A series of laboratory and field tests are conducted on a cable to validate the performance of the proposed automated monitoring system.

Characterization of Individual Alpha Frequency of EEG Signals as an Indicator of Cognitive Fatigue

Cognitive fatigue is a condition caused by monotonous work which involving cognitive function in a long period that influences performance impairment. One of the methods to detect cognitive fatigue is using Individual Alpha Frequency (IAF) of brain waves which was obtained from an electroencephalography (EEG) measurement. This study aimed to calculate IAF values using power spectral density (PSD) as an indicator of cognitive fatigue in the frontal, parietal, and occipital lobes which used a cognitive task as the stimulus. The EEG was measured by using Cadwell Easy^ III with a sampling frequency of 250 Hz and the electrode impedance maintained below 20 k?. Electrodes on F3, F4, F7, F8, Fz, P3, P4, O1, and O2 were investigated in this study. The data acquisition was conducted in 46 minutes: 3 minutes before, 40 minutes during, and 3 minutes after carrying out the arithmetic test as a cognitive task. The arithmetic test was displayed through the visual display terminal (VDT). In the next stage, the preprocessing was conducted to remove noise and artifacts, followed by PSD calculation using the Welch periodogram. Finally, the values of IAF were calculated by using the Center of Gravity (CoG). The results showed that PSD in all session sorted by the largest values are delta, theta, and alpha wave. As for the IAF pre-task values shifted towards larger alpha frequency in the post-task in frontal and parietal region, showed in vigilance with increasing time spent on task, and shifted towards smaller values in occipital region which fatigue begins to occur in this region and has not occured in other region.

Comparison of Wet and Dry EEG Electrodes Based On Brain Signals Characterization In Temporal and Anterior Frontal Areas Using Audio Stimulation

Electroencephalography (EEG) electrodes are divided into two types: dry and wet. In wet electrodes, a gel or saline liquid is used to increase the conductivity value, however, it tends to dry over time. On the contrary, gel or saline liquid is not required on the dry electrode. The use of certain types of electrode in EEG influences Power Spectral Density (PSD) of brain signals. Therefore, this study compared the EEG signal produced by Emotiv using the two different types of electrodes and a specific stimulus. This study was conducted using Emotiv EPOC (wet) and Insight (dry). The Temporal (T7 and T8) and Anterior Frontal (AF3 and AF4) electrodes from both devices were used to be compared. An audio stimulus that contains a story was chosen followed by a small task related to the story. The data acquisition was performed in 36 minutes to maintain the stability of the two types of electrodes. Three minutes of recordings in resting condition were conducted on both before and after given audio stimulus. Audio stimulation followed by a small task was performed for thirty minutes. The data analysis has consisted of EEG data pre-processing using centering and filtering the data, followed by PSD calculation using the Welch periodogram with Hanning window. The result showed that the decrement percentage of PSD after stimulation from wet was higher than dry electrodes.

Исследование переходных процессов сердечного ритма на плоскости комплексных частот у детей школьного возраста при выполнении корректурной пробы

Introduction. The method of processing experimental data obtained in the form of a timevarying non-stationary signal is described. In the experimental study of transients associated with changes in the heart rate of schoolchildren during a proof-reading test, it became necessary to develop a new effective method for processing the results of dynamic measurements. Purpose of the study. Consider the main points of this methodology, which is based on the Prony method, and the possibility of its use in the field of studies of changes in heart rate variability (HRV) in response to various functional test influences. Materials and methods. Traditional approaches related to the calculation of power spectral density (PSD) and based on classical spectral methods are currently very widespread. The model of constant rhythm is not applicable for non-stationary dependencies of HRV. For spectral analysis of time dependences of HRV reflecting transient processes (nonstationary processes) it is proposed to apply spectral analysis on the plane of complex frequencies (PCF). PCF is a generalization of the usual spectrum. The calculation of the PCF is based on the Prony procedure, based on parametric modeling. Results. PCF reflects the frequency structure of oscillations of unsteady physiological signals, therefore, can be used to classify them. It is shown that the use of spectral analysis on the plane of complex frequencies for transient processes of the heart rhythm makes it possible (according to the parameters of the PCF) to calculate, for diagnostic purposes, the numerical values of the parameters characterizing the reactions of various regulatory mechanisms of the heart rhythm in response to various functional test influences. Conclusion. The best results, as compared with the methods of classical spectral analysis, for the analysis of transients in the form of a HRV signal were given by approaches based on the use of spectral analysis on the plane of complex frequencies.

Vehicle model response in frequency domain

The offered article deals with one of the possibilities of numerical analysis of the vehicle response in frequency domain. It works with quarter model of vehicle. For the selected computational model of vehicle it quantifies the Frequency Response Functions (FRF) of both force and kinematic quantities. It considers the stochastic road profile. The Power Spectral Density (PSD) of the road profile is used as input value for the calculation of Power Spectral Density of the response. Al calculations are carried out numerically in the environment of program system MATLAB. When we know the modules of FRF or the Power Response Factors (PRF) of vehicle model the calculation of vehicle response in frequency domain is fast and efficient.

Wide frequency band electrochemical noise measurement and analysis of a Li/SOCl2 primary battery

Electrochemical noise of a primary LiSOCl2 battery was measured in a wide frequency band during discharge at a constant value resistor. Power spectral density calculation method was used as the first stage of data analysis. Measurements with two analog to digital converter speed rates made it possible to carry out precision analysis in more than five order wide frequency bands starting from 2.5 kHz down to 17 mHz. It was shown that each power spectral density spectrum consists of two regions. Each of them possesses linear frequency dependence with its own slope. They intercept in the frequency band from 10 Hz down to 0.1 Hz depending on the state of charge value. Dispersion and high-order moments such as kurtosis and skewness calculation methods were applied to analyze electrochemical noise data as alternate analysis techniques. It was found that dispersion calculation can give useful information about electrochemical noise evolution during discharge process for the investigated battery type.

Calculation of Evolutionary Power Spectral Density of Bridge Response to Earthquakes by Convolution Summation

This paper presents a method for calculating the evolutionary power spectral density (EPSD) of the seismic response of bridges using the convolution summation. With zero initial values, a formula for the dynamic component of the response of bridges to spatially varying seismic ground motions is derived as the convolution summation, by assuming the seismic acceleration to vary linearly between two adjacent time stations. The convolution summation is used for calculating the convolution integral of the dynamic component response factor in the EPSD, in which the constant coefficients are independent of the harmonically modulated excitation. The constant coefficients are obtained by the time-history analysis using triangular unit impulse acceleration excitations. The computational cost of the EPSD depends mainly on the amount of degrees-of-freedom (DOFs) numbers of bridge supports in contact. The corresponding computational scheme is proposed, and its validity is indirectly verified with a single DOF system, by comparing the results obtained with those of the existing methods. Finally, a three-span continuous rigid-frame bridge is taken as a case study to illustrate the applicability and effectiveness of the proposed scheme.