Dominant Frequency Amplitude Research Articles

Vibration Response of Soil under Low-Frequency Vibration Using the Discrete Element Method

The vibration response of soil is a key property in the field of agricultural soil tillage. Vibration components of tillage machinery are generally used to reduce tillage resistance and improve work efficiency, and the pressure variation under low-frequency vibration will affect the fragmentation and dispersion of farmland soil. However, the gradient of pressure variation, frequency domain response, and effective transmission range is unclear. A new method based on the DEM (discrete element method) is presented to study the vibration response and pressure transmission under low-frequency vibration. Bench test results have shown that peak pressure positively correlates with the vibration frequency and attenuates rapidly at a vibration distance of 100 to 250 mm. The resulting data were also selected to determine the simulation model’s parameters. Amplitude, vibration frequency, and soil depth were used as test factors in single-factor simulation tests, and their effects on the peak pressure, frequency domain response, and effective transmission distance were analyzed. The results showed a positive relationship between the peak pressure and the test factors. The peak pressure increased with a maximum gradient of 19.02 kPa/mm at a vibration distance of 50 mm. The amplitude, vibration frequency, and soil depth positively correlated with the dominant frequency amplitude. The main frequency was independent of amplitude and soil depth. At a vibration distance of 250 mm, the dominant frequency was approximately twice the vibration frequency at 7–11 Hz and approximately equal to the vibration frequency at 13–15 Hz. Multiple exponential functions were used to fit the peak pressure attenuation function, obtaining an effective transmission distance range of 347.15 to 550.37 mm for the 5 kPa cut-off pressure. For a soil depth of 300 mm, the vertical shear wave diffusion angle was greater than the horizontal shear wave diffusion angle. This study clarifies the vibration response of soil under low-frequency vibration, which helps to design vibration-type, soil-engaging components of tillage machinery and match vibration parameters for energy-saving and resistance reduction purposes in soil tillage.

Accurate Flow Regime Classification and Void Fraction Measurement in Two-Phase Flowmeters Using Frequency-Domain Feature Extraction and Neural Networks

Two-phase flow is very important in many areas of science, engineering, and industry. Two-phase flow comprising gas and liquid phases is a common occurrence in oil and gas related industries. This study considers three flow regimes, including homogeneous, annular, and stratified regimes ranging from 5–90% of void fractions simulated via the Mont Carlo N-Particle (MCNP) Code. In the proposed model, two NaI detectors were used for recording the emitted photons of a cesium 137 source that pass through the pipe. Following that, fast Fourier transform (FFT), which aims to transfer recorded signals to frequency domain, was adopted. By analyzing signals in the frequency domain, it is possible to extract some hidden features that are not visible in the time domain analysis. Four distinctive features of registered signals, including average value, the amplitude of dominant frequency, standard deviation (STD), and skewness were extracted. These features were compared to each other to determine the best feature that can offer the best separation. Furthermore, artificial neural network (ANN) was utilized to increase the efficiency of two-phase flowmeters. Additionally, two multi-layer perceptron (MLP) neural networks were adopted for classifying the considered regimes and estimating the volumetric percentages. Applying the proposed model, the outlined flow regimes were accurately classified, resulting in volumetric percentages with a low root mean square error (RMSE) of 1.1%.

Numerical Simulation Research on Cutting Rock with a PDC Cutter Assisted by an Impact Force

Extensive studies have been carried out on cutting rock with a PDC cutter, but cutting rock assisted by impact force is rarely studied. In this paper, cutting rock using conical and cylindrical PDC cutters assisted by impact force were researched with the explicit dynamic model. The laws of cutting rock using a cylindrical cutter assisted by impact force are the same as those of a conical cutter. There are thresholds of impact frequency and amplitude when they are single variables. When impact frequency is lower than the threshold frequency, the impact frequency is the dominant frequency in the frequency spectrum of weight on bit (WOB), and the amplitude of dominant frequency and removal volume decreases with the increase of impact frequency. When the impact frequency is higher than the threshold frequency, there is no dominant frequency in the frequency spectrum of WOB, and the removal volume behaves the same. When the impact force is lower than the threshold amplitude, there is no dominant frequency in the frequency spectrum of WOB, and it does not affect the removal volume but the removal volume is positively correlated with the impact amplitude. When the impact amplitude is higher than the threshold amplitude, the removal volume is also positively correlated with the impact amplitude, and the removal volume assisted by low-frequency (20 Hz and 40 Hz) impact force is higher. The frequency threshold and amplitude threshold of the conical cutter are smaller than those of the cylindrical cutter. Although the cutting depth and removal volume of the conical cutter are lower than those of the cylindrical cutter, the amplifications of cutting depth and removal volume of the conical cutter are higher than those of the cylindrical cutter when assisted by impact force.

Experimental Investigations on Charge Induction and Microseismic Characteristics of the Coal and Rock under Different Loading Rates

The research on charge induction and microseismic characteristics of coal and rock under different loading rates is of great significance for rockburst prediction. In this study, the coal and sandstone samples from the No. 11 mine of Pingdingshan Coal Mine are prepared. The charge induction and microseismic synchronous comprehensive monitoring system is built. The uniaxial compression tests of coal and sandstone samples under the different loading rates are conducted. The charge induction and microseismic signal characteristics in the deformation and fracture process of the coal and rock under the different loading rates are studied. The results show that, with the increase of loading rate, the compressive strength of the coal and rock samples increases and the time from the peak stress to instability failure becomes shorter. At the same loading rate, the softening failure stage time of coal is longer than that of sandstone. With the increase of loading rate, the duration of charge-induced signal and microseismic signal is longer and the events’ number and amplitude of charge signal and microseismic signal increase in the deformation and fracture process of the coal and rock. Before the instability failure, the charge-induced signal and microseismic signal have both synchronous and asynchronous signals, and the amplitude of charge-induced and microseismic signals in each channel is different, which is related to the distance from the position of each sensor to the fracture point of the sample. During the instability failure, the charge induction and microseismic signals of each channel are generated synchronously, and the signal amplitude reaches the maximum values of 50 pC and 6 × 10−3 m/s at the same time. With the increase of specimen stress, the dominant frequency of microseismic signals first increases and then decreases, while the amplitude of dominant frequency increases synchronously. The dominant frequency amplitude of microseismic signals is the largest in instability failure. With the increase of loading rate, the spectrum amplitude of microseismic signals changes little in the compaction stage, but the spectrum amplitude increases in other stages. At the same loading speed, the events’ number of the microseismic signal of coal samples after peak stress is more than that of sandstone samples, and the signal amplitude is also larger. However, the spectrum distribution range of microseismic signals of coal samples is wider than that of sandstone samples, and the spectrum amplitude of coal samples is lower than that of sandstone. With the increase of loading rate, the time of the first generation of high-amplitude signals is advanced, and the stress of specimen becomes smaller when the first generation of high-amplitude signals occurs. With the increase of loading rate, the duration of microseismic and charge signal is longer, and the mean square amplitude of charge signal is larger.

Aquifer Diffusivity Estimation Through Joint Inversion of the Amplitude Ratios and Time Lags of Dominant Frequencies of Fluctuating Head

AbstractThis note introduces the estimation of aquifer diffusivity (D) through simultaneous inversion of the attenuation and lag of multiple head fluctuation frequencies due to a dynamic source or boundary, that is, a river. Spectral analysis, with optimized moving time window length and step size, was used to extract the dominant constituents and their attenuation through space; the cross‐power spectral density method was used to determine time lags. The Jacob‐Ferris analytical model was then used for inverting forD. Unlike most similar applications to date, here we propose using all frequencies with robust signal‐to‐noise ratios (five total in our test cases) and both the amplitude attenuation and time lag in the inversion. The method was implemented using observations from wells in the banks of the fluctuating Meghna River in Bangladesh that is connected with a semi‐confined sandy alluvial aquifer. The estimatedDusing the technique provides estimates that are very similar to those from pumping tests. The estimates are more accurate compared to previous implementation of the Jacob‐Ferris model on the same data that used only a dominant frequency's amplitude attenuation or time lag. The workflow and codes for the analysis are provided for straightforward implementation of the robust and cost‐effective method.

Field Vibration Feature and Related Factors Analysis of 110kV Transformers

Transformer vibration is closely related with its operating condition. In order to realize transformer operation condition evaluation, vibrations of sixty-two 110kV transformers are tested. The acceleration amplitude, base frequency amplitude, base frequency ratio, dominant frequency amplitude, dominant frequency ratio and frequency complexity are chosen as vibration features. Statistical analysis of the feature distribution is conducted to determine the normal range of the vibration features. In addition, the influence of operating life on transformer vibration features is also analyzed. The result shows that for most transformers vibration acceleration amplitude, base frequency amplitude, base frequency ratio, dominant frequency amplitude, dominant frequency ratio and frequency complexity are in the range below 5.0m/s2, 1.0m/s2, 0.3, 2.0 m/s2, 0.9 and 3.0, respectively. The vibration amplitude, base frequency and dominant frequency amplitude will increase obviously if transformer operating life is over 20 years. The analysis result will be used as data support for the operation condition assessment of transformers.

Effect of Blade Trailing Edge Cutting Angle on Unstable Flow and Vibration in a Centrifugal Pump

Abstract The vibration induced by the unsteady fluid exciting force in a centrifugal pump is one of the important factors affecting the reliable operation of the pump. In this study, the cutting of the blade trailing edge of a straight blade is presented to improve the unstable flow and vibration in a centrifugal pump. Based on the large eddy simulation (LES) and fluid–solid coupling method, the transient pressure pulsation, unstable flow structure, and vibration displacement of a centrifugal pump were investigated with different cutting angles of the trailing edge under the design flow rate. The external characteristics of the centrifugal pumps were calculated and compared using the shear stress transport (SST) k–ω turbulence model. The results show that the heads and efficiencies of the pumps with 30 deg and 45 deg cutting angles of the trailing edge slightly improved. The pressure pulsation on the volute evaluated by dominant frequency–amplitude and pressure pulsation energy was reduced due to the lesser average vorticity intensity and trailing vortex area in the centrifugal pump. Therefore, the vibration displacement and the vibration energy at the low frequency of the impeller decreased.

Precise gamma based two-phase flow meter using frequency feature extraction and only one detector

Flow regime information can be used to enhance measurement accuracy of flowmeters. Void fraction measurement and regime identification of two-phase flows including, liquid and gas phases are crucial issues in oil and gas industries. In this study, three different regimes including annular, stratified and homogeneous in the range of 5%–90% void fractions, were simulated by Monte Carlo N-Particle (MCNP) Code. In simulated structure, a Cesium 137 source and only one NaI detector were used to record received transmitted photons. Fast Fourier Transform (FFT) was applied to the registered signals of the detector in order to analyze in the frequency domain. Several features of signals in the frequency domain were extracted. These features were the average value of fast Fourier transform, the amplitude of dominant frequency, variance, Kurtosis and RMS (root mean square). Different combinations of these features were investigated in order to find the best features with the best separation ability for using as the inputs of Artificial Neural Network (ANNs). Two different Multi-Layer Perceptron (MLP) neural networks were used to recognize flow regimes and predict the void fraction. In regime identification procedure, all of the three mentioned regimes were recognized correctly and in the volume fractions prediction procedure, the void fraction was also estimated with a Mean Relative Error (MRE) percentage of less than 0.5%. In all of the previous studies, at least two detectors were used. Using the proposed method in this paper, number of detectors was reduced to one.

Three-Dimensional Wave-Field Characteristics of Earth-Rock Dams with Different Hidden Hazards

The three-dimensional wave-field characteristics of dangerous earth-rock dams are the premise and foundation to identify the hidden hazards of the earth-rock dams via wave test method. Based on the equivalent elastic wave theory in isotropic mediums, the three-dimensional wave field of earth-rock dams with different defects was calculated using the finite element numerical simulation method. The characteristic and regularity of the three-dimensional wave field was explored. The result of the analysis shows that the size and position of the defects are closely related with the wave-field information received on the dam surface. The elasticity modulus and density of the defects have great effect on the wave field, and alternately, Poisson’s ratio of the defects has little effect on the wave field. The greater the difference between the wave velocity of the hazardous materials and the dam body is, the stronger the energy of the scattered wave will be, which in turn will produce clearer lineups of the scattered wave on the time-history profile. For a single wave movement signal, the dominant frequency amplitude is exponentially correlated with the longitudinal wave velocity of the hazardous materials. Therefore, in the process of wave detection for earth-rock dam hazards, the effect of the elasticity modulus, density, and wave velocity on the test signal should be taken into account. The dominant frequency amplitude can serve as one of the control parameters for interpretation of dam hazards by the analysis of the wave test signal.

Vertical Track Irregularity Influence on the Wheel High-Frequency Vibration in Wheel-Rail System

A three-dimensional deformable finite element model of wheel-rail system is established. The vertical vibration natural frequencies are calculated by modal analysis. The improved central difference method by ABAQUS explicit nonlinear dynamics module is chosen to calculate the vertical vibration of wheel axle. Through the vibration measurement experiment ofLMAwheel by China Academy of Railway Sciences, the contact parameter is optimized and the model is modified. According to the nonlinear simulation results, the important influence of vertical track irregularity on the wheel set high-frequency vibration is discovered. The advantage frequencies through spectrum are close to the vertical vibration natural frequencies of seventh, eighth, ninth, and tenth mode. When the velocity is 350 km/h, system’s nonlinear dynamic characteristic is higher than the results at 200 km/h. The critical wavelength of vertical track irregularity on the wheel vertical vibration is about 0.8 m. In addition, a particular attention should be paid to one situation that the main dominant frequency amplitude is more than 50% of the acceleration amplitude even if the peak acceleration is low.

Optimization of novel spectral estimator for fractionated electrogram analysis is helpful to discern atrial fibrillation type

IntroductionParoxysmal versus persistent atrial fibrillation (AF) can be distinguished based on differences in the spectral parameters of fractionated atrial electrograms. Maximization of these differences would improve characterization of the arrhythmogenic substrate. A novel spectral estimator (NSE) has been shown previously to provide greater distinction in AF spectral parameters as compared with the Fourier transform estimator. Herein, it is described how the differences in NSE spectral parameters can be further improved. MethodIn 10 persistent and 9 paroxysmal AF patients undergoing electrophysiologic study, fractionated electrograms were acquired from the distal bipolar ablation electrode. A total of 204 electrograms were recorded from the pulmonary vein (PV) antra and from the anterior and posterior left atrial free wall. The following spectral parameters were measured: the dominant frequency (DF), which reflects local activation rate, the DF amplitude (DA), and the mean spectral profile (MP), which represents background electrical activity. To optimize differences in parameters between paroxysmal versus persistent AF patients, the NSE was varied by selectively removing subharmonics, using a threshold. The threshold was altered in steps to determine the optimal subharmonics removal. ResultsAt the optimal threshold level, mean differences in persistent versus paroxysmal AF spectral parameters were: ΔDA=+0.371mV, ΔDF=+0.737Hz, and ΔMP=−0.096mV. When subharmonics were not removed, the differences were substantially less: ΔDA=+0.301mV, ΔDF=+0.699Hz, and ΔMP=−0.063mV. ConclusionsNSE optimization produces greater spectral parameter difference between persistent versus paroxysmal AF data. Quantifying spectral parameter differences can be assistive in characterizing the arrhythmogenic substrate.

Comparison of spectral estimators for characterizing fractionated atrial electrograms

BackgroundComplex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF) are commonly assessed using the discrete Fourier transform (DFT), but this can lead to inaccuracy. In this study, spectral estimators derived by averaging the autocorrelation function at lags were compared to the DFT.MethodBipolar CFAE of at least 16 s duration were obtained from pulmonary vein ostia and left atrial free wall sites (9 paroxysmal and 10 persistent AF patients). Power spectra were computed using the DFT and three other methods: 1. a novel spectral estimator based on signal averaging (NSE), 2. the NSE with harmonic removal (NSH), and 3. the autocorrelation function average at lags (AFA). Three spectral parameters were calculated: 1. the largest fundamental spectral peak, known as the dominant frequency (DF), 2. the DF amplitude (DA), and 3. the mean spectral profile (MP), which quantifies noise floor level. For each spectral estimator and parameter, the significance of the difference between paroxysmal and persistent AF was determined.ResultsFor all estimators, mean DA and mean DF values were higher in persistent AF, while the mean MP value was higher in paroxysmal AF. The differences in means between paroxysmals and persistents were highly significant for 3/3 NSE and NSH measurements and for 2/3 DFT and AFA measurements (p<0.001). For all estimators, the standard deviation in DA and MP values were higher in persistent AF, while the standard deviation in DF value was higher in paroxysmal AF. Differences in standard deviations between paroxysmals and persistents were highly significant in 2/3 NSE and NSH measurements, in 1/3 AFA measurements, and in 0/3 DFT measurements.ConclusionsMeasurements made from all four spectral estimators were in agreement as to whether the means and standard deviations in three spectral parameters were greater in CFAEs acquired from paroxysmal or in persistent AF patients. Since the measurements were consistent, use of two or more of these estimators for power spectral analysis can be assistive to evaluate CFAE more objectively and accurately, which may lead to improved clinical outcome. Since the most significant differences overall were achieved using the NSE and NSH estimators, parameters measured from their spectra will likely be the most useful for detecting and discerning electrophysiologic differences in the AF substrate based upon frequency analysis of CFAE.