Output Power Spectral Density Research Articles

A mixer architecture using GaN-based split-gate nanowire transistor

Frequency mixer is an essential block in radio-frequency signal processing for frequency translation and phase comparison. The most common mixers are fabricated using passive elements which suffer from significant conversion loss and low isolation. Mixers using active devices are used less frequently and rather less matured on GaN technology. Here, we demonstrate a mixer based on GaN split-gate nanowire transistor, allowing low conversion loss and high isolation. A constriction is formed by electrostatic modulation of the effective gate width. The threshold voltage of the transistor is modified by one of the gate voltages through the width variation, while the other gate voltage biases the transistor in the saturation region. The nonlinear dependency of the transistor characteristics on the two gate voltages facilitates frequency translation. The mixing characteristics of this architecture are verified both experimentally and theoretically. The output power spectral density peaks at the difference frequency with a minimal conversion loss. Extremely high isolation is measured using three-port S-parameter measurements. The proposed architecture shows multiple benefits, additionally facilitating monolithic mixers on the GaN platform.

A comparison study on the derivation of in-structure FRS during seismic events for application of ITER upper port 18

The design of in-structure components in Port Plug (PP) requires the accurate reaction of the seismic events on the particular points of interest to properly define the vibration behavior of PPs. The most common way to represent the seismic event used is by Floor Response Spectral (FRS). To define the seismic FRS at the particular locations of the ITER diagnostics components, IO has been developed a suitable methodology by a “direct spectra-to-spectra method”. The developed methodology in the frequency domain, has four main steps: first, conversion of the response spectral into artificial equivalent Power Spectral Density (PSD); second, performing random vibration analysis using the artificial equivalent PSD; third, extraction of the output PSD at specific points; fourth, inverse conversion of the generated PSD into response spectra. This methodology to find seismic FRS at the particular points of in-structure in Upper Port 18 (UP18) is presented in this work. A comparison result for different Upper Port Plug (UPP) models is also discussed.

Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing

A new method for the determination of oil and water flow rates in vertical upward oil-water two-phase pipe flows has been proposed. This method consists of an application of machine learning techniques on the probability density function (PDF) and the power spectral density (PSD) of the power spectrum output of an ultrasonic Doppler sensor in the pipe. The power spectrum characteristic parameters of the two-phase flow are first determined by the probability density function (PDF) method. Then, the transducer signal is preprocessed by distance correlation analysis (DCA), and independent features are extracted by principal component analysis (PCA). The extracted features are used as input to a least-squares fit, which gave the oil flow rates as output. In the same way, the transducer signal is also preprocessed by partial correlation analysis (PCA), and independent features were extracted using independent component analysis (ICA). The extracted features were used as inputs to multilayer back-propagation neural networks, which water cuts as output. The present method was used to calibrate an ultrasonic Doppler sensor to estimate the flow rates of both phases in oil–water flow in a vertical pipe of diameter 159 mm. Predictions of the present method were in good agreement with direct flow rate measurements. Compared to previously used methods of feature extraction from the ultrasonic Doppler power spectrum signals, the present method provides a theoretical basis for the interpretation of ultrasonic multiphase flow logging data. Ultrasonic multiphase flow logging has potential application value in the production profile logging and interpretation evaluation of production wells with low fluid production and high water cut.

Influence of the offshore electrical platform on the dynamic responses of converter valve under sea waves and earthquakes

ABSTRACT Converter valves are installed on the offshore electrical platform, whose structural characteristics have a significant effect on the dynamic responses of the supported converter valves. In this paper, the simplified computational models of platform and converter valve were proposed to evaluate the effect of platform mass and stiffness on the dynamic responses of converter valve under sea waves and earthquakes. In order to determine the frequency corresponding to the peak responses accurately, the input and output power spectral density functions that could overcome the effect of the randomness of external loadings were derived. The key response parameters including peak acceleration and peak displacement were considered. The structural responses showed a significant difference under different external loadings. Results of this paper can be utilised to make a reliable decision for designing suitable structural parameters of the offshore electrical platform and selecting the most reasonable vibration control measures to reduce the structural peak responses.

Power spectral density analysis for nonlinear systems based on Volterra series

A consequence of nonlinearities is a multi-harmonic response via a mono-harmonic excitation. A similar phenomenon also exists in random vibration. The power spectral density (PSD) analysis of random vibration for nonlinear systems is studied in this paper. The analytical formulation of output PSD subject to the zero-mean Gaussian random load is deduced by using the Volterra series expansion and the conception of generalized frequency response function (GFRF). For a class of nonlinear systems, the growing exponential method is used to determine the first 3rd-order GFRFs. The proposed approach is used to achieve the nonlinear system’s output PSD under a narrow-band stationary random input. The relationship between the peak of PSD and the parameters of the nonlinear system is discussed. By using the proposed method, the nonlinear characteristics of multi-band output via single-band input can be well predicted. The results reveal that changing nonlinear system parameters gives a one-of-a-kind change of the system’s output PSD. This paper provides a method for the research of random vibration prediction and control in real-world nonlinear systems.

Analysis of spectral efficiency for OFDM cooperative cognitive networks with non‐linear relay

This paper analyzes the downlink achievable spectral efficiency of an orthogonal frequency-division multiplexing (OFDM) cooperative cognitive network with a non-linear relay. The analysis is carried out subject to the power amplifier's (PA) non-linear effect on the relay node which operates in the amplify-and-forward (AF) mode. Specifically, an analytical expression for the power spectral density (PSD) of relay output in terms of its source power is derived. By using the obtained PSD, the power of relay's PA output is derived for each subcarrier and the 1 dB compression point is determined. Then, the adjacent channel power (ACP) of each subcarrier is analytically derived in terms of secondary user (SU) source input power. Next, the signal to interference and noise ratio (SINR) of each subcarrier at destination (SU receiver) is calculated by considering the non-linear effect of PA at the relay. Having the SINRs of all subcarriers, a constrained optimization problem on the source's input power is formulated in which the achievable spectral efficiency is the objective function and all ACPs being less than the interference temperature limit are its constraints. Finally, we perform some simulations and show that the numerical results are consistent with the analytical findings.

Seismic response analysis of fixed jacket-type offshore structures based on power spectrum density Driven input

ABSTRACT Offshore platforms in seismically active areas should be properly designed to survive within the face of intense earthquakes without a global structural collapse. This paper scrutinizes the seismic performance of a newly designed and established jacket type offshore platform based on the API-RP2A normalized response spectra during seismic events. A finite element model is developed from a typical jacket type offshore platform taking into the effect of the interaction among structure, pile, and soil components. The seismic responses of jacket type offshore platforms subjected to random earthquake excitations are evaluated by means of the power spectral density (PSD) analysis. Dynamic characteristics, the response function, output PSD and transfer functions for various elements of the platform are discussed. The spectrum compatible PSD is directly used to estimate the peak structural responses and determine the dynamic response of offshore jacket platforms that meet the required level of engineering practice for preliminary design.

All normal dispersion nonlinear fibre supercontinuum source characterization and application in hyperspectral stimulated Raman scattering microscopy

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful label-free, chemical-specific technique for biomedical and mineralogical imaging. Usually, broad and rapid spectral scanning across Raman bands is required for species identification. In many implementations, however, the Raman spectral scan speed is limited by the need to tune source laser wavelengths. Alternatively, a broadband supercontinuum source can be considered. In SRS microscopy, however, source noise is critically important, precluding many spectral broadening schemes. Here we show that a supercontinuum light source based on all normal dispersion (ANDi) fibres provides a stable broadband output with very low incremental source noise. We characterized the noise power spectral density of the ANDi fibre output and demonstrated its use in hyperspectral SRS microscopy applications. This confirms the viability and ease of implementation of ANDi fibre sources for broadband SRS imaging.

Fully integrated fractional‐N phase‐locked loop for GNSS standards

This study presents the design of a fully integrated fractional-N phase-locked loop (FNPLL) for the Global Navigation Satellite System (GNSS) applications. A new linearisation technique is presented for a charge pump (CP) circuit to improve the mismatch between the charging and discharging currents. The linearised currents help to reduce the static phase offset and the reference spurs of the FNPLL and the constant current helps to control the PLL dynamics precisely. The presented FNPLL is designed in a 0.18 µm CMOS technology. The simulation result reveals that the linearity of the CP is enhanced greatly when the technique is enabled and the current mismatch is <0.2 µA over the output voltage ranging from 0.2 to 1.65 V. The phase noise of the FNPLL at 10 and 100 KHz offset frequencies without the linearised CP are −85 and −90 dBc/Hz, respectively, and with the high linear CP are −90 and −97 dBc/Hz, respectively. The output power spectral density of the FNPLL shows that the power of the highest fractional spur is about −57 dBc. The lock time and the power consumption of the designed FNPLL are 50 µs and 11 mW from a 1.8 V power supply, respectively.

Time-based damage detection of underground ferromagnetic pipelines using complexity pursuit based blind signal separation

The measured sensor data of underground ferromagnetic pipelines consist of hidden damage information that can be explored by developing output data identification models due to the availability of only output signal responses. The current research findings elaborate output-only modal identification method Complexity Pursuit based on blind signal separation. An attempt is made to apply the complexity pursuit algorithms, for time-based damage detection of underground ferromagnetic pipelines which blindly estimates the modal parameters from the measured magnetic field signals for targeting the pipeline defect locations. Numerical simulations for multi-degree of freedom systems show that the proposed tested method could precisely identify the structural parameters. Experiments are conducted primarily under well-equipped controlled laboratory conditions followed by confirmation in the real field on pipeline magnetic field data, recorded through high precision magnetic field sensors. The measured recorded structural responses are given as input to the blind source separation model where the complexity pursuit algorithms blindly extracted the least complex signals from the observed mixtures guaranteed to be source signals. The output power spectral densities calculated from the estimated modal responses unveiled elegant physical interpretation of the underground ferromagnetic pipeline structures.

Time-Domain Output Data Identification Model for Pipeline Flaw Detection Using Blind Source Separation Technique Complexity Pursuit

Vital defect information present in the magnetic field data of oil and gas pipelines can be perceived by developing such non-parametric algorithms that can extract modal features and performs structural assessment directly from the recorded signal data. This paper discusses such output-only modal identification method Complexity Pursuit (CP) based on blind signal separation. An application to the pipeline flaw detection is presented and it is shown that the complexity pursuit algorithm blindly estimates the modal parameters from the measured magnetic field signals. Numerical simulations for multi-degree of freedom systems show that the method can precisely identify the structural parameters. Experiments are performed first in a controlled laboratory environment secondly in real world, on pipeline magnetic field data, recorded using high precision magnetic field sensors. The measured structural responses are given as input to the blind source separation model where the complexity pursuit algorithm blindly extracted the least complex signals from the observed mixtures that were guaranteed to be source signals. The output power spectral densities calculated from the estimated modal responses exhibit rich physical interpretation of the pipeline structures.

Clamp looseness detection using modal strain estimated from FBG based operational modal analysis

Clamps are widely used to fix and support the pipe in engineering community. Clamps looseness may further lead to the fatigue damage of the pipe, therefore the early detection of clamps looseness is very crucial. The robustness and the accuracy of damages detection have already been the greatest challenges in traditional methods in Structural Health Monitoring (SHM). Due to the higher sensitivity of Strain Mode Shape (SMS) to local damages and more effective performance of fiber Bragg grating (FBG) sensing technology for industrial and mechanical devices, present works focus on a new method to detect clamp looseness based on Strain Mode Shape Differences (SMSD) and FBG sensing technology. In order to estimate the SMSs online, a novel diagram of Operational Strain Modal Analysis (OSMA) with FBG sensing technology is also presented, in which a rational fraction composed by Forsythe Complex Orthogonal Polynomials (FCOP) is employed to fit the ‘Positive’ Strain Power Spectral Density (PSPSD) of a single output. Traditionally, the fitting of the all the outputs need to be conducted to obtain the SMSs, which increases the calculation cost. To further address this issue, an improved OSMA integrated with strain response transmissibility (SRT) is also proposed to calculate the SMSs by just fitting a single output. Firstly, the identified modal parameters based on the presented method is validated with simulation results. And then, the ability of the SMSD index is further investigated analytically and experimentally for clamp looseness detection under different locations and degrees, the results indicate that the clamp looseness can be detected by the SMSD index.

Dynamic response of tank trains to random track irregularities

This paper presents a dynamic analytical model for tank train vibrations. The train is considered as a system of 27 degrees of freedom consisting of lateral, roll, yaw, vertical, and pitch motions for the vehicle body and its two bogies and lateral, roll and vertical motions for the four wheel-sets. Liquid sloshing in the tank is modeled using an equivalent mechanical mass-spring model. Coupling between the vehicle system and the railway track is realized through the interaction forces between the train and the rail, where the vertical and lateral irregularity profiles of the track are regarded as stationary ergodic Gaussian random processes and simulated by polynomial functions. Random vibration theory is used to obtain the response power spectral densities. Finally, numerical results for a typical test case including natural frequencies of a coupled system, frequency response functions, and output power spectral densities are presented.

Noise activated bistable sensor based on chaotic system with output defined by temporal coding and firing rate.

Traditional bistable sensors use external bias signal to drive its response between states and their detection strategy is based on the output power spectral density or the residence time difference (RTD) in two sensor states. Recently, the noise activated nonlinear dynamic sensors driven only by noise based on RTD technique have been proposed. Here, we present experimental results of dc voltage measurements by noise-driven bistable sensor based on electronic Chua's circuit operating in a chaotic regime where two single scroll attractors coexist. The output of the sensor is quantified by the proportion of the time the sensor stays in one state to the total observation time and by the spike-count rate with spikes defined by crossings between attractors. The relationship between the stimuli and particular observable for different noise intensities is obtained, the usefulness of each coding scheme is discussed, and the optimal noise intensity for detection is indicated. It is shown that the obtained relationship is the same for any observation time when population coding is used. The optimal time window for both detection and the number of units in population coding is found. Our results may be useful for analyses and understanding of the neural activity and in designing bistable storage elements at length scales where thermal fluctuations drastically increase and the effect of noise must be taken into consideration.

Modeling and assessment of partially debonded piezoelectric sensor in smart composite laminates

As substantive components of intelligent structures, piezoelectric sensors need to perform their intended function without any spuriousness. In this work, a mathematical model has been developed to characterize the performance degradation of a piezoelectric sensor due to its debonding from a smart composite laminate. The electromechanically coupled governing equation of motion is developed by incorporating improved layerwise theory and higher electric potential field along with the finite element method and Extended Hamilton's principle. The problem governing equation is solved by Newmark time-integration algorithm to assess the performance of a piezoelectric sensor in the presence of partial debonding at the edge and inner side of the sensor. The partially debonded piezoelectric sensor is investigated in frequency domain via power spectral density of the sensor output. The degradative performance of the partially debonded sensor is generalized for random loadings via basic signal statistics. The numerical results show that the developed model recover the presence and extent of partial debonding between the piezoelectric sensor and the host laminate.

Localization of breathing cracks in stepped rotors using super‐harmonic characteristic deflection shapes based on singular value decomposition in frequency domain

AbstractAn output‐only multiple‐crack localization method is proposed in this paper to detect and localize breathing cracks in a stepped rotor, which utilizes the crack‐induced local shape distortions in super‐harmonic characteristic deflection shapes (SCDSs). To minimize the noise effects on SCDSs and improve the accuracy of SCDS‐based crack localization, singular value decomposition is adopted to estimate the SCDS as the dominant singular vector of output power spectral density matrix at a super‐harmonic frequency. Then, in order to better reveal shape distortions in the SCDSs, an after‐treatment technique called gapped smoothing method is applied to derive a damage index. Numerical experiments are carried out to investigate the performance of the proposed method based on a two‐disc stepped rotor‐bearing system with breathing cracks established by the finite element method. Results show that the method is effective for single and multiple crack localization in stepped rotors and interference of steps can be excluded. Furthermore, the method is robust to noise. Influences of crack depths and rotating speeds are also investigated, and how to choose the rotating speed for better crack localization is discussed.

An Efficient Method of Power Spectral Density Estimation for On-Chip IR-UWB Transmitter Self-Calibration

In ultra-wideband impulse radio communications, process, voltage, and temperature variations may impact the operation of emitters by modifying the emitted power spectral density. In order to compensate the impact of such variations and to respect the spectral emission masks, self-calibration systems able to estimate the output power spectral density have to be integrated in ultra-wideband impulse radio transmitters. In this paper, a new power spectral density estimation method for ultra-wideband impulse radio signals is presented. Unlike the discrete Fourier transform classically used to estimate the power spectral density, the proposed method, which is based on the measurement of the time varying envelope and instantaneous frequency of the emitted pulse, preserves a link between the time and the frequency domain thanks to a piece-wise approximation of these waveforms. This time-to-frequency link enables a straightforward pulse shape control by using simple control methods and allows to comply with spectral masks required by ultra-wideband communication regulations and standards such as the IEEE 802.15.4a. Thus, both envelope and instantaneous frequency extraction techniques are introduced for acquisition of these time domain waveforms in ultra-wideband impulse radio domain. The proposed techniques are validated and allow to consider future hardware implementation in order to build on-chip calibration systems for ultra-wideband transmitters.

Power Spectral Density Analysis of Purkinje Cell Tonic and Burst Firing Patterns From a Rat Model of Ataxia and Riluzole Treated.

Introduction:Purkinje Cell (PC) output displays a complex firing pattern consisting of high frequency sodium spikes and low frequency calcium spikes, and disruption in this firing behavior may contribute to cerebellar ataxia. Riluzole, neuroprotective agent, has been demonstrated to have neuroprotective effects in cerebellar ataxia. Here, the spectral analysis of PCs firing in control, 3-acetylpyridine (3-AP), neurotoxin agent, treated alone and riluzole plus 3-AP treated were investigated to determine changes in the firing properties. Difference in the power spectra of tonic and burst firing was assessed. Furthermore, the role of calcium-activated potassium channels in the power spectra was evaluated.Methods:Analysis was performed using Matlab. Power spectral density (PSD) of PCs output were obtained. Peak frequencies were extracted from the spectrum and statistical comparisons were done. In addition, a multi-compartment computational model of a Purkinje cell was used. This computational stimulation allowed us to study the changes in the power spectral density of the PC output as a result of alteration in ion channels.Results:Spectral analysis showed that in the spectrum of tonic and burst firing pattern only high sodium frequency and low calcium frequency was seen, respectively. In addition, there was a significant difference between the frequency components of PCs firing obtained from normal, ataxia and riluzole treated rats. Results indicated that sodium firing frequency of normal, ataxic and treated PCs occurred in approximate frequency of 22.53±5.49, 6.46±0.23, and 31.34±4.07 Hz, respectively; and calcium frequency occurred in frequency of 4.22±2.02, 1.52±1.19, and 3.88±1.37 Hz, respectively. The simulation results demonstrated that blockade of calcium-activated potassium channels in the PC model changed the PSD of the PC model firing activity. This change was similar to PSD changes in ataxia condition.Conclusion:These alterations in the spectrum of PC output may be a basis for developing possible new treatment strategies to improve cerebellar ataxia.

Design, fabrication and performances of MEMS piezoelectric energy harvester

MEMS piezoelectric energy harvester is optimally designed and fabricated, and its vibration characteristics, output voltage, power, power spectral density (SD) and frequency response function under harmonic and random excitation is studied by theory analysis, simulation and experimental test. For the designed MEMS piezoelectric energy harvester, the accurate solutions and expressions of amplitude, voltage, power and power spectral density are derived. Then, vibration characteristic, voltage, power and power SD with different load resistance, sinusoidal acceleration and random acceleration SD are simulated and tested; moreover, frequency response function of MEMS piezoelectric energy harvester is obtained by experimental test, and the results are consistent with theoretical model. When sinusoidal acceleration is 0.6 g, the maximal amplitude of mass is 116 µm and the power density is 0.1 mW/cm 3 . By testing results, output voltage of piezoelectric energy harvester is proportional to the amplitude, and the amplitude at optimal load is smaller than of at open circuit because of the feedback effect of load resistance. In addition, output power SD linearly increases with acceleration SD increasing. When acceleration SD is 5 × 10 −4 (m/s 2 ) 2 /Hz, power SD is 1.24 µW 2 /Hz.

Frequency-Selective Digital Predistortion for Unwanted Emission Reduction

In this paper, we present a novel digital predistortion (DPD) solution based on a direct learning approach, which is capable of reducing the unwanted emissions resulting from the power amplifier (PA) at any prespecified frequency located in the transmitter's out-of-band or spurious domain. The proposed scheme is based on evaluating the power spectral density (PSD) of the PA output signal and optimizing the DPD coefficients iteratively in order to minimize the output PSD around the prespecified frequency. To highlight the feasibility of the proposed implementation, the predistortion processing is kept as simple as possible, deploying quasi-memoryless polynomial models. Efficient mitigation of unwanted emissions around the target frequency is demonstrated via simulations and actual RF measurements, in both single- and dual-carrier waveform scenarios, using memoryless and memory-based PAs. The proposed DPD solution could be potentially employed in applications such as mobile devices utilizing noncontiguous multicarrier transmission, where the intermodulation spurs may overlap with the device's own receiver band, or could be potentially violating the spurious emission limits. Another target application is cognitive radio, where the PA may produce unwanted emissions that are interfering with primary-user transmissions. To the best of the authors' knowledge, there does not exist a similar technique in the open literature, and thus, the purpose of this paper is to encourage scientific discussions and technological innovations toward the creation of relatively low-complexity frequency-optimized predistortion techniques employed against selected unwanted emissions produced by the transmitter.