Frequency Spectrum Analysis Research Articles

PIV based POD analysis of coherent structures in flow patterns generated by triple interacting buoyant plumes

The paper performs an investigation on multi-scale coherent structures that exist in different flow patterns of triple interacting plumes. Time-averaged and turbulent flow characteristics are first obtained by the two-dimensional (2-D) particle image velocimetry (PIV) technique. Proper orthogonal decomposition (POD) method is then applied to extract the dominant coherent structures. Energy contributions, POD modes, and POD coefficients are systematically explored to understand the spatial-temporal characteristics of the coherent structures.The first three POD modes are most important in the turbulent kinetic energy (TKE). Mode 1, as the most dominant mode, can contain about 10% TKE in an average sense. In addition, the first 12–14 POD modes can totally contribute 50% TKE. Hierarchical four-scale flow structures, independent of the flow patterns, are clearly identified when mode number increases, which are successively characterized by main flows (the 1st scale), larger-scale outer-side vortex rings (the 2nd scale), shear-layer vortex shedding (the 3rd scale), and smaller-scale homogeneous turbulent vortices (the 4th scale).Frequency spectra analysis confirms the co-existence of lower-frequency and higher-frequency periodic cycles in one certain POD mode. Dominant frequencies of the first three POD coefficient series (a1–a3) fall into the range of 0.025–0.187 Hz. Probability density analysis has identified negative/positive peak probability densities of the series a1. Cumulative probabilities of negative and positive coefficients are approximately equivalent during the sampling period.

Research on Fault Extraction Method of Variational Mode Decomposition Based on Immunized Fruit Fly Optimization Algorithm.

In recent years, a new method of fault diagnosis, named variational mode decomposition (VMD), has been widely used in industrial production, but the decomposition accuracy of VMD is determined by two parameters, which are respectively the decomposition layer number k and the penalty factor α, if the parameters are not properly selected, there will be over-decomposition or under-decomposition. In order to find an approach to determine the parameters adaptively, a method to optimize VMD by using the immune fruit fly optimization algorithm (IFOA) is proposed in this paper. In this method, permutation entropy is used as the fitness function, firstly, the immune fruit fly optimization algorithm is used to search the combined parameters of k and α in VMD, searching for the best combination parameters of k and α by iteration, and then uses the combined parameters to perform VMD, finally, the center frequency is determined through frequency spectrum analysis. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a wind turbine gearbox, and the fault frequency is successfully extracted. Using ensemble empirical mode decomposition (EEMD) and singular spectrum decomposition (SSD) to compare with the proposed method, which validated feasibility of the proposed method.

Mechanical properties and charge signal characteristics in coal material failure under different loading paths

Rock burst is a catastrophic dynamic disaster caused by sudden failure and instability of coal, loading paths play an important role in the failure of coal, the coal failure process is associated with charge exception information. Hence, violent coal failure mechanics and time–frequency domain distribution of charge signal such as rock burst under different loading paths should be studied in-depth. In this paper, grade and cyclic loading test were carried out for coal with impact tendency samples produced by blocks cored from 800 depth in Xiaoqing coal mine of the Tiefa coal group in northeast China. Theory discussion was carried out for the result of stress and strain, frequency-spectra analysis was conducted for the wavelet charge data, figures showing the evolution mechanism of mechanical properties and the relationship of time–frequency domain amplitude of charge signals in coal with different loading paths and stage were obtained. The failure process and characteristics of coal under different loading paths were summarized. It found that the loading path changed the manner of energy accelerate–release, there were more plastic strain generation in coal under cyclic loading than that under grade loading, the former was more likely to cause greater damage and failure, then the strength of coal under cyclic loading is generally lower than that under grade loading, an energy conversion mechanical model of stress, damage and deformation was developed and explained the effect of the loading path. Charge signal was primarily distributed in the strengthening and peak stages, where there was a high amplitude pulse at each stress drop. The charge pulse was a type of low frequency signal with a primary frequency distribution range of 1 –100 Hz. Discussion on the charge generating mechanism from the perspective of friction slip, it demonstrated that the charge obtained during the coal failure process directly to stress loaded on and damage, the result verified it better. We propose that the research results in this study could be efficiently applied to daily mining activities, to provide an early warning and effectively avoid rock burst disaster.

Multi-temporal assessment of power system flexibility requirement

In power systems, flexibility can be defined as the ability to adapt to variability and uncertainty in demand and generation. Various ongoing changes in the power system are impacting the need for flexibility. We propose a novel methodology to (i) evaluate annual, weekly and daily flexibility requirements through a set of frequency spectrum analysis based metrics, (ii) examine the sensitivity of these flexibility requirements to five variables: the degree of network interconnection and the penetration of wind power, solar power, electric heating and cooling. The proposed methodology is validated on a case study focusing on the French power system, while accounting for its electrically connected neighbours. We provide an estimation of how flexibility requirements are likely to evolve in years to come; the use of global sensitivity analysis allows the identification of the variables responsible for these evolutions. The presented methodology and results can be used to identify future challenges, to evaluate the market potential of flexibility solutions and to assess the implications of policy decisions.

Automated electronic approaches for detecting disease vectors mosquitoes through the wing-beat frequency

The knowledge of flying insects wing-beat acoustical properties supported the progress of sensing disease vectors mosquitoes in free flight. The classification of individual flying insects species' through wing-beat frequencies and respective harmonics is the principle of frequency spectrum analysis method both in acoustical and optical sensors approaches for disease vectors mosquitoes. Investigations based on acoustic devices, microphones, amplifiers, and recorders have produced extensive scientific contributions to behavioral and biological insects’ knowledge. Moreover, the researches based on acoustical approach are accountable for the massive available database on flying insects species and gender classification. However, it was the advent of the optical sensing approach for flying insects detection that allowed sensor devices to become smaller, cheaper, faster, self-triggered, and further reliable and energy efficient. These benefits enabled the state of the art on mosquitoes monitoring to move towards smarter devices that automatically process data and have greater autonomy in inaccessible locations. Consequently, it becomes plausible to break geographic, economic and social boundaries for the flying insects sensing, allowing the ubiquitous monitoring of disease-vector mosquito populations. This paper reviews the related literature on automated electronic approaches for disease vectors mosquitoes monitoring and identifies open issues and opportunities for further researches in expanding scenarios considering new data processing and emerging transmission technologies.

X-ray non-destructive testing – an essential tool during modern aeronautics material technology design and development

The X-ray non-destructive testing process is carried out by the system, which includes: the object of control (OC); source of radiation; detector; operator. The X-ray radiation and the object of control interaction formed the radiation image as X-ray doze distribution in accordance with the properties of the OC. At this stage, useful information about the OK is formed, which one is partially lost, partially distorted, and veiled with noise when the radiation image is converted into an optical one. The optical image is analyzed by operator, and the result of the control depends from his physical and emotional state.This article presents a phased analysis of the entire radiation monitoring system. The first stage is the radiation image formation. Theoretical estimate of X-ray inspection system minimum detected defect size was made using space frequency spectrum analysis. The second stage is the transformation of the radiation image into an optical one. We represented the simulation of this process and obtained a modulation of how the operator sees the X-ray optical image and makes a decision about the OC state. Analyzed the X-ray digital image formation and determined the energy choice criteria when applied digital radiography.

Wind turbine gearbox fault diagnosis based on the vibration spectrum analysis

Gear box has the high failure rate among the components in wind turbines and the vibration signal analysis is the most common technology in its fault diagnosis. Gearbox vibration signals of wind turbines have complicated compositions, strong background noise and obvious non-stationary characteristi cs. The new method research suited to non-stationary and non-gaussian characteristics of vibration signals is the key to improve the level of fault diagnosis technology. In order to diagnosis the operation status of wind turbines, based on the spectral analysis and the combination of vibration wave spectrum analysis of wind turbine gearbox fault diagnosis method is proposed. Through the gearbox oil spectral analysis, tests the main metal content in the oil, the preliminary judgment out of the wind turbine operation working condition. Using the vibration waveform frequency spectrum analysis method can get the fault severity, and analyzes the cause of the problem. This method can realize the wind turbine gearbox fault diagnosis, to ensure reliability. It is can effectively conduct the wind turbine development, design and optimization, and reduces maintenance costs.

Estimation of Remaining Useful Lifetime of Lithium-Ion Battery Based on Acoustic Emission Measurements

Lithium-ion battery (LIB) utilization as energy storage device in electric and hybrid-electric vehicles, wind turbine systems, a number of portable electrical devices, and in many other application fields is encouraged due to LIB small size alongside high energy density. Monitoring of LIB health state parameters, calculation of additional LIB operating parameters, and the fulfillment of safety requirements are provided through battery management systems. Prediction of remaining useful lifetime (RUL) of LIB and state-of-health (SoH) estimation are identified as still challenging and not completely solved tasks. In this contribution, previous works on RUL/SoH estimation, mainly relied on modeling of underlying electrochemical processes inside LIB, are compared with newly developed approach. The proposed approach utilizes acoustic emission measurements for LIB aging indicators estimation. Developed model for RUL estimation is closely related to frequency spectrum analysis of captured acoustic emission (AE) signal. Features selected from AE measurements are considered as model inputs. The novelty of this approach is the opportunity to estimate RUL/SoH of LIB without necessity to capture some intermediate variables, only indirectly related to RUL/SoH (charging/discharging currents, temperature, and similar). The proposed approach provides the possibility to obtain reliable information about current RUL/SoH without the knowledge about underlying physical processes occurred in LIB. Experimental data sets gathered from LIB aging tests are used for model establishment, training, and validation. The experimental results demonstrate the applicability of the novel approach.

Wind power fluctuation compensation by variable speed pumped storage plant in a grid integrated system: Frequency spectrum analysis

An electrical power generation from the wind technology is the most rapidly growing technology due to its ample characteristics. Nevertheless, because of its stochastic feature, it has unnecessary impacts on the operation s and stability of the power grid system. The fluctuation of the grid frequency problem, for example, is more pronounced. The fluctuation of the frequency in turn impacts even the collapse of the power system. To minimize such problem, a droop-vector control strategy applied on a doubly-fed induction machine based (DFIM) variable speed pumped storage (VSPS) system is proposed in this paper. This method is supposed to be used as a wind power fluctuation compensation solution in the wind farm-grid integration system. The system model is made on the basis of the technique called a phasor model. The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation. The software platform MATLAB/Simulink is used for verifying the performance of the proposed system. The results show that the method of frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirement in the large power network. The control strategy proposed on this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves well-controlled power flow and stable grid frequency with the deviations in acceptable ranges.

Earthquake testing of the 1:60 scaled immersed tunnel of the Hong Kong-Zhuhai-Macao-Bridge: analysis of frequency spectra from 44 experiments

The Hong Kong-Zhuhai-Macao-Bridge (HZMB) is a traffic link consisting of two parts connected by an immersed tunnel. The structure may be subjected to moderate earthquakes. During such an exceptional load case, the joints between the 33 tunnel elements must remain water-tight. This was the motivation to perform 44 earthquake tests of 13 scaled elements of the tunnel. Different earthquake scenarios were simulated, with the prime focus resting on the opening widths of the joints. In addition, accelerometers documented the dynamic behavior of the tunnel elements, the soil at selected positions underneath the tunnel, and the shaking tables. In the present paper, the related frequency spectra are analyzed based on the Discrete Fourier Transform. This way, the first eigenfrequency of the tunnel is quantified. Furthermore, frequency intervals are identified, inside of which Fourier amplitudes are either amplified or attenuated, after comparison of readings of accelerometers mounted to the shaking tables and to the tunnel elements, respectively. Arguments by analogy to the real-scale tunnel can be drawn from the obtained results.

Real-time signal processing of photoplethysmographic signals to estimate the on-demand and continuous heart rate by spectral analysis

In healthcare applications, heart rate is one of the vital signs which give the health informatics of a person. Nowadays, the evolution of PPG sensors help to develop low cost heart rate monitoring devices with minimal hardware resources compared to ECG. In this paper, an efficient algorithm is proposed to find the heart rate using frequency spectrum analysis on PPG signals. Using the proposed algorithm, the heart rate is calculated with a pass percentage of 99.2, mean absolute percentage error (MAPE) of 1.59%, mean absolute error (MAE) of 1.20 BPM and reference closeness factor (RCF) of 0.989. The first reliable heart rate output comes in 6.5th second, which is the minimum possible time. The algorithm operates with a speed of 2 MIPS and with a memory of 18 KB. So the proposed method can be integrated to any low cost real-time embedded platforms to accurately measure the heart rate.

Latest results on the analysis of the radio frequency spectrum emitted by high energy air showers with LOFAR

The LOw Frequency ARay (LOFAR) is a multi-purpose radio antenna array aimed to detect radio signals in the frequency range 10 - 240 MHz, covering a largesurface in Northern Europe with a higher density in the Netherlands. Analytical calculations and simulation studies performed in the 2000s indicate a dependence of the radio frequency spectrum on cosmic-ray characteristics. The high number density of radio antennas at the LOFAR core allows to characterise the observed cascade in a detailed way. The radio signal emitted by air showers in the atmosphere has been studied accurately in the 30 - 80 MHz frequency range. The analysis has been conducted on simulated eventsand on real data detected by LOFAR since 2011. The final aim of this study is to find an independent method to infer information of primary cosmic rays for improving the reconstruction of primary particle parameters. Results show a strong dependence of the frequency spectrum on the distance to the shower axis for both real data and simulations. Furthermore, results show that this method is very sensitive to the precision in reconstructing the position of the shower axis at ground, and to different antenna calibration procedures. A correlation between the frequency spectrum and geometrical distance to the shower maximum development Xmax has also been investigated.

Feature extraction using frequency spectrum and time domain analysis of vibration signals to monitoring advanced ceramic in grinding process

New alternatives for monitoring the ceramic grinding process have been studied. Monitoring vibration signals is one of the most successful methods because some characteristics that describe the behaviour and influence of the process on ground parts are only noticeable by studying such signals. This study aims to monitor the finishing of advanced ceramics during the surface grinding process via digital processing of the vibration signals. Experimental tests were performed using a surface tangential grinding machine with a diamond grinding wheel and alumina (Al 2 O 3 ) test specimens. The vibration signal was measured by an accelerometer and recorded by an oscilloscope at a 2 MHz sampling rate. The tests were conducted at different depths of cut for two workpiece speeds ( v w ) under mild and severe machining conditions. Confocal microscopy and surface roughness R a measurements were performed after grinding each workpiece to classify the samples. Digital signal processing was performed to achieve feature extraction. A frequency range of 800 Hz-2 kHz was most strongly related to the post-grinding ceramic condition. A correlation was found between vibration and integrity of the ceramic workpiece because the vibration signal was proportional to the surface roughness for each cutting depth used. To support the conclusion presented, a statistical analysis through variance by analysis of variance was performed.

多孔質動圧軸受における正弦波加振時の潤滑特性に関する実験的研究（FFT周波数分析を用いた回転モード特定による起動時の軸回転挙動の検討）

多孔質動圧軸受における正弦波加振時の潤滑特性に関する実験的研究（FFT周波数分析を用いた回転モード特定による起動時の軸回転挙動の検討）

Spin Dynamics in the Ferromagnetic Resonance

The LLG equation including the spin-transfer torque term, and the frequency spectrum analysis method are used to study the dynamic process of ferromagnetic resonance. The effects of damping factor α, internal anisotropic field, magnetic field inclination, and spin-transfer torque caused by the spin current are studied. The following results are found as follows. The ferromagnetic resonance spectra as functions of the frequency ω for fixed magnetic field, and functions of magnetic field for fixed frequency are obtained, and it is found that the internal magnetic field also has contribution to the resonance field or frequency, and we know that the resonant frequency ω0≈he + h1 (in unit of γH0). In addition, when the damping factor increases from 0.01 to 0.03, the resonance frequencies increases slightly, and the resonance strength decreases. And the oscillatory waves of mx and my reach their stable values more quickly. Furthermore, the internal field perpendicular to the external field h0 as well as it parallel to h0 also has the effect to the resonant frequency. The positive and negative internal field will have reversed effects to the resonance field or frequency. And in the end when the spin current becomes larger the STT effect becomes stronger, even exceeds the ferromagnetic resonance effect, makes mz reversed, and mx and my decreased.

Damage mode identification of adhesive composite joints under hygrothermal environment using acoustic emission and machine learning

This paper studies the hygrothermal aging effect on the damage behaviors of adhesive composite joints by acoustic emission (AE) technique. Tensile tests and AE tests arelaunchedfor bothnon-aging and aging specimens under regular and hygrothermal environments, respectively. The clustering analysis, the time-domain analysis and the frequency-domain analysis are combined to identify various damage modes and to study the hygrothermal aging effect of single-lap joint (SLJ). First, the clustering analysis isperformed to study the damage mode correlation usingfour AE characteristic parameters including the time of duration, the peak amplitude, the RA value (the rise time divided by the peak amplitude) and the frequency centroid of gravity. Then, the time-domain analysis is conducted toinvestigate the hygrothermaleffectof the single-lap joint (SLJ). Finally, the frequency spectrum analysis is carried out tostudythe frequency range for the shear failure of adhesive layer. In addition, the dominant damage mode of SLJ is identified using the wavelet-based decomposition of the ultimate AE signals with the largest energy.

Frequency spectrum analysis of lightweight foamed concrete using microwave dielectric measurement technique

AbstractThe dielectric characterization of concrete is a significant parameter to study the microwave signal transmission for the building materials. In this paper, a microwave measurement system has been developed using open ended coaxial sensor and vector network analyzer for frequency spectrum analysis of lightweight foamed concrete. The measurement setup is validated prior to make sure the system is working properly. The results of dielectric constant and loss factor of different densities lightweight concrete samples are measured and analyzed from 150 kHz to 8 GHz. From the analysis, the lightweight foamed concrete is a frequency spectrum friendly building material. In addition, the relationship between the dielectric constant and density of the lightweight foamed concrete is found to be interrelated. The empirical modeling of some selected frequencies has been formed. The models are useful for the future application on determining the dielectric constant and characteristic of lightweight concrete samples.

Finite Element Seismic Analysis of Soil–Tunnel Interactions in Clay Soils

Seismic waves propagate from bedrock through the soil layers and during this propagation they pass different layers of soil and rock until they reach the soil surface. These waves can be amplified or damped by the soil layers. Underground structures response, like tunnels, is related to a number of factors such as soil type and earthquake frequency. In this paper the simulation of the models is done in two-dimensional plain strain system with finite element mesh generation which consists of soil–tunnel using frequency spectrum analysis. All analyses consist of three actual ground motion records with low, intermediate and high-frequency content. Two different clay soils (Normally or Lightly Over-Consolidate Clay and Heavily Over-Consolidate Clay) have been used in free field and models consist of cylindrical tunnel. In this study, the results of both free field (models without structure) and soil–tunnel analysis have been compared to show the effect of the tunnel on responses. Effect of soil–tunnel interaction in all earthquakes with different frequency content on-site response, amplification, acceleration response and stress and strain propagation in the tunnel’s perimeter are discussed. Based on the results of the analysis, acceleration frequency at different depths of models had different characteristics. Both clay soils amplified seismic waves on the soil surface in free filled models and the soil–structure interaction effects on the tunnel dynamic responses.

Nonlinear dynamic behavior of cemented granular materials under impact loading

Nonlinear sound propagation in stressed cemented granular materials is investigated using the split Hopkinson pressure bar (SHPB) system, via frequency spectra analysis. The sandstone is selected for performing the experimental investigation. The sound velocity is deduced from experimental measurement of amplitude ratio of incident to transmitted waves, showing a power (1/6) law scaling with confining pressure, confirming the applicability of Hertzian nonlinear elasticity on cemented granular materials. Analysis on the measured magnitude of second-harmonic gives the coefficient of nonlinearity whose order of magnitude is consistent with that deduced from acoustoelastic method with a relationship βAE ≈ (1.5 ∼ 4.5)βWM. The transmitted wave amplitude is also analyzed by applying repetitive impact load, demonstrating that relatively high intensity incident wave as well as lower confining pressure induces intensive weakening of the rocks.

Experimental characterizing combustion emissions and thermodynamic properties of a thermoacoustic swirl combustor

Many practical lean-premixed combustion systems involved in land-based power plants, gas turbines and boilers are susceptible to self-excited combustion instability, which is characterized by detrimental periodic pressure oscillations. Little attention has been paid on experimentally characterizing the chemical emissions and thermodynamic properties of a thermoacoustic swirl combustor. In this work, the effects of (1) fuel-air equivalence ratio Φ and fuel flow rate QCH4 on generating such combustion instability and its impact on chemical emissions and thermodynamic properties in a swirling combustor are experimentally studied. For this, a methane-fueled lab-scale swirl combustor is designed and tested. To monitor the thermodynamic properties of the combustor, an acoustic pressure sensor, an infrared thermal imaging camera, K-type thermal couples, and an infrared flue gas analyzer are applied. It is found that the fuel-air ratio plays an important role on generating combustion instability at different frequencies and amplitudes. This is confirmed by conducting autocorrelation and frequency spectrum analyses of the acoustic pressure time trace. Furthermore, the dominant mode swap (mode-switching) between a low frequency ω1 and a high non-harmonic one is experimentally observed. Whether the mode switching from high (harmonic or non-harmonic) to low frequency or low to high frequency is found to depend strongly on QCH4. As the equivalence ratio is changed from lean to rich, i.e. 0.8 ≤ Φ ≤ 1.2, NOx emission is increased from 1 ppm to 37 ppm. However, CO emission is decreased by 2 order of magnitudes from 1000 ppm first and then increased. The minimum CO emission is approximately 3.0 ppm. In addition, O2 concentration is decreased by more than 80% with increased Φ, depending on the methane flow rate. This means that the combustion efficiency characterized by the O2 emission is decreased dramatically from 99.5% to 68% with Φ increased from 0.6 to 1.2. The present work sheds light on the characteristics of chemical emissions and thermodynamic properties, when a thermoacoustic swirl combustor is operated with methane-air equivalence ratio Φ varied from lean to rich condition and different QCH4. It opens up a practical means to design a stably operated but low-emission thermoacoustic swirl combustor.