scholarly journals Identification of ship wake structures by a time–frequency method

2015 ◽  
Vol 765 ◽  
pp. 229-251 ◽  
Author(s):  
T. Torsvik ◽  
T. Soomere ◽  
I. Didenkulova ◽  
A. Sheremet
Keyword(s):  
High Frequency ◽  
Individual Component ◽  
Energy Content ◽  
Low Frequency ◽  
Frequency Method ◽  
Ship Wake ◽  
Time Frequency ◽  
Time Space ◽  
Short Time ◽  
Ship Speed

AbstractThe wake of a ship that sails at relatively large Froude numbers usually contains a number of components of different nature and with different heights, lengths, timings and propagation directions. We explore the possibilities of the spectrogram representation of one-point measurements of the ship wake to identify these components and to quantify their main properties. This representation, based on the short-time Fourier transform, facilitates a reliable decomposition of the wake into constituent components and makes it possible to quantify their variations in the time–space domain and the energy content of each component, from very low-frequency precursor waves up to high-frequency signals within the frequency range of typical wind-generated waves. A method for estimation of the ship speed and the distance of its sailing line from the measurement site is proposed, which only uses information available within the record of the ship wake surface elevation, but where it is assumed that the wake pattern does not deviate significantly from the classical Kelvin wake structure. The wake decomposition using the spectrogram method allows investigation of the energy content that can be attributed to each individual component of the wake. We demonstrate that the majority (60–80 %) of wake energy from strongly powered large ferries that sail at depth Froude numbers ${\sim}0.7$ is concentrated in components that are located near the edge of the wake wedge. Finally, we demonstrate that the spectrogram representation offers a convenient way to identify a specific signature of single types of ships.

scholarly journals An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan
Keyword(s):  
Machine Tool ◽  
Frequency Domain ◽  
Surface Topography ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Time Frequency ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

Estimation of Fluctuating Propeller Torque of Full-Scale Ship Using Free-Running Model in Waves

2015 ◽  
Author(s):  
Michio Ueno ◽  
Yoshiaki Tsukada
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Full Scale ◽  
Engine Torque ◽  
Engine Model ◽  
Frequency Components ◽  
Free Running ◽  
External Forces ◽  
Ship Propeller ◽  
Ship Speed

The authors propose a method to estimate full-scale propeller torque consisting of low-frequency and high-frequency components in waves using measured data of free-running model ship. The duct fan auxiliary thruster (DFAT) [1] and the rudder-effectiveness and speed correction (RSC) [2,3] ensure similar model ship motion to full-scale in external forces, where RSC controls the model ship propeller rate of revolution and the auxiliary thrust depending on measured model ship speed. Analyzing a fluctuating component of effective inflow velocity to propeller due to waves, the method estimates full-scale fluctuating propeller torque in waves. This method also makes it possible to adopt into free-running model ship tests any engine model simulating interaction between propeller torque and engine torque. Trial application of the method exemplifies the property of full-scale fluctuating propeller torque comparing with that of model ship.

Prediction of High Frequency Sonic Boom Noise Transmission Into Buildings Using a Hybrid Analytical-Ray Tracing Approach

2012 ◽  
Author(s):  
Joseph M. Corcoran ◽  
Marcel C. Remillieux ◽  
Ricardo A. Burdisso
Keyword(s):  
Ray Tracing ◽  
High Frequency ◽  
Acoustic Radiation ◽  
Low Frequency ◽  
Sonic Boom ◽  
Acoustic Transmission ◽  
Frequency Method ◽  
Low Frequencies ◽  
Sonic Booms ◽  
Acoustic Responses

As part of the effort to renew commercial supersonic flight, a predictive numerical tool to compute sonic boom transmission into buildings is under development. Due to the computational limitations of typical numerical methods used at low frequencies (e.g. Finite Element Method), it is necessary to develop a separate approach for the calculation of acoustic transmission and interior radiation at high frequencies. The high frequency approach can then later be combined with a low frequency method to obtain full frequency vibro-acoustic responses of buildings. An analytical method used for the computation of high frequency acoustic transmission through typical building partitions is presented in this paper. Each partition is taken in isolation and assumed to be infinite in dimension. Using the fact that a sonic boom generated far from the structure will approximate plane wave incidence, efficient analytical solutions for the vibration and acoustic radiation of different types of partitions are developed. This is linked to a commercial ray tracing code to compute the high frequency interior acoustic response and for auralization of transmitted sonic booms. Acoustic and vibration results of this high frequency tool are compared to experimental data for a few example cases demonstrating its efficiency and accuracy.

scholarly journals Comparison of Pure-Tone Average Methods for Estimation of Hearing Loss Caused by Environmental Exposure to Lead and Cadmium: Does the Pure-Tone Average Method Which Uses Low-Frequency Ranges Underestimate the Actual Hearing Loss Caused by Environmental Lead and Cadmium Exposure?

2018 ◽  
Vol 23 (5) ◽  
pp. 259-269 ◽  
Author(s):  
Da-An Huh ◽  
Yun-Hee Choi ◽  
Myung Sun Ji ◽  
Kyong Whan Moon ◽  
Seok J. Yoon ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Environmental Exposure ◽  
High Frequency ◽  
Pure Tone ◽  
Low Frequency ◽  
Cadmium Exposure ◽  
Metal Exposure ◽  
Frequency Method ◽  
Pure Tone Average ◽  
Lead And Cadmium

Previous studies have reported that exposure to lead and cadmium can damage the inner ear receptor, which perceives high-frequency sounds. However, few studies have used the pure-tone average (PTA), including high-frequency ranges, for the estimation of hearing loss caused by lead and cadmium exposure. We estimated hearing loss using the PTA test, in low-frequency, speech frequency, and high-frequency ranges and compared the differences in the results using 3 PTA calculation methods. We analyzed the data of 2,387 participants, between the ages of 19 and 85 years, that were obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) of 2010–2012. A dose-response relationship between hearing loss and heavy metal exposure was observed in the high-frequency method after adjustment for confounding factors. When using the high-frequency PTA, it was found that doubling of the levels of lead and cadmium in the blood was associated with a 1.88- (95% CI 1.11–3.17) and 1.89-fold (95% CI 1.02–3.50) increase in the OR for hearing loss. In the case of the low-frequency and speech frequency PTA, however, there were no significant relationships between hearing loss and the concentrations of lead and cadmium in the blood. The outcomes of the present study suggest that the estimation of hearing loss caused by environmental exposure to lead and cadmium is affected by the frequencies used in the PTA calculation.

Applied Research on Segmented-Hilbert-Huang Transform Algorithm in Fault Feature Extraction of Main Reducer

2013 ◽  
Vol 823 ◽  
pp. 417-421 ◽  
Author(s):  
Feng Yun Huang ◽  
Huan Huan Sun ◽  
Hao Pan ◽  
Wei Ru Zhang
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Vibration Signal ◽  
Model Decomposition ◽  
Frequency Dictionary ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Frequency Representation ◽  
Scale Characteristics ◽  
Frequency Impulse

For the multi-time scale characteristics of vibration signal, a composite multi-frequency dictionary combining the low-frequency Fourier dictionary and the high-frequency impulse time-frequency dictionary is constituted, to decompose multi-component vibration signal into the combination of several one-component signals. The use of empirical model decomposition (EDM) in high-frequency impulse Component signal including feature information is to realize segmented Hilbert-Huang transform of signal and to acquire the time-frequency representation of every one-component signal, which is the process of fault information extraction of vibration signal. The application of the method in main reducer fault diagnosis verifies the engineering practicability and validity of the new algorithm.

scholarly journals Application of Short Time Fourier Transform and Wavelet Transform for Sound Source Localization Using Single Moving Microphone in Machine Condition Monitoring

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Meifal Rusli
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Sound Source ◽  
Low Frequency ◽  
Peak Position ◽  
Source Position ◽  
Short Time Fourier Transform ◽  
Sound Sources ◽  
Time Frequency ◽  
Short Time

<p class="TTPParagraphothers"><em>The paper discusses means to predict sound source position emitted by fault machine components based on a single microphone moving in a linear track with constant speed.</em> The position of sound source that consists of some frequency spectrum is detected by time-frequency distribution of the sound signal through Short Time Fourier Transform (STFT) and Continues Wavelet Transform (CWT). <em>As the amplitude of sound pressure increases when the microphone moves closer, the source position and frequency are predicted from the peaks of time-frequency contour map</em><em>. </em>Firstly, numerical simulation is conducted using two sound sources that generate four different frequencies of sound. The second case is experimental analysis using rotating machine being monitored with unbalanced, misalignment and bearing defect. The result shows that application of both STFT and CWT are able to detect multiple sound sources position with multiple frequency peaks caused by machine fault. The STFT can indicate the frequency very clearly, but not for the peak position. On the other hand, the CWT is able to predict the position of sound at low frequency very clearly. However, it is failed to detect the exact frequency because of overlapping.</p>

scholarly journals Motoneuron firing patterns underlying fast oscillations in phrenic nerve discharge in the rat

2012 ◽  
Vol 108 (8) ◽  
pp. 2134-2143 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Michael G. Z. Ghali ◽  
Robert F. Rogers
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Medium Frequency ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Novel Method ◽  
Frequency Coherence ◽  
Fast Oscillations ◽  
First Time

Fast oscillations are ubiquitous throughout the mammalian central nervous system and are especially prominent in respiratory motor outputs, including the phrenic nerves (PhNs). Some investigators have argued for an epiphenomenological basis for PhN high-frequency oscillations because phrenic motoneurons (PhMNs) firing at these same frequencies have never been recorded, although their existence has never been tested systematically. Experiments were performed on 18 paralyzed, unanesthetized, decerebrate adult rats in which whole PhN and individual PhMN activity were recorded. A novel method for evaluating unit-nerve time-frequency coherence was applied to PhMN and PhN recordings. PhMNs were classified according to their maximal firing rate as high, medium, and low frequency, corresponding to the analogous bands in PhN spectra. For the first time, we report the existence of PhMNs firing at rates corresponding to high-frequency oscillations during eupneic motor output. The majority of PhMNs fired only during inspiration, but a small subpopulation possessed tonic activity throughout all phases of respiration. Significant time-varying PhMN-PhN coherence was observed for all PhMN classes. High-frequency, early-recruited units had significantly more consistent onset times than low-frequency, early/middle-recruited and medium-frequency, middle/late-recruited PhMNs. High- and medium-frequency PhMNs had significantly more consistent offset times than low-frequency units. This suggests that startup and termination of PhMNs with higher firing rates are more precisely controlled, which may contribute to the greater PhMN-PhN coherence at the beginning and end of inspiration. Our findings provide evidence that near-synchronous discharge of PhMNs firing at high rates may underlie fast oscillations in PhN discharge.

Selective loss of high-frequency oscillations in phrenic and hypoglossal activity in the decerebrate rat during gasping

2006 ◽  
Vol 291 (5) ◽  
pp. R1414-R1429 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Power Distribution ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
High Amplitude ◽  
Medial Branch ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Nerve Recordings

Respiratory motor outputs contain medium-(MFO) and high-frequency oscillations (HFO) that are much faster than the fundamental breathing rhythm. However, the associated changes in power spectral characteristics of the major respiratory outputs in unanesthetized animals during the transition from normal eupneic breathing to hypoxic gasping have not been well characterized. Experiments were performed on nine unanesthetized, chemo- and barodenervated, decerebrate adult rats, in which asphyxia elicited hyperpnea, followed by apnea and gasping. A gated fast Fourier transform (FFT) analysis and a novel time-frequency representation (TFR) analysis were developed and applied to whole phrenic and to medial branch hypoglossal nerve recordings. Our results revealed one MFO and one HFO peak in the phrenic output during eupnea, where HFO was prominent in the first two-thirds of the burst and MFO was prominent in the latter two-thirds of the burst. The hypoglossal activity contained broadband power distribution with several distinct peaks. During gasping, two high-amplitude MFO peaks were present in phrenic activity, and this state was characterized by a conspicuous loss in HFO power. Hypoglossal activity showed a significant reduction in power and a shift in its distribution toward lower frequencies during gasping. TFR analysis of phrenic activity revealed the increasing importance of an initial low-frequency “start-up” burst that grew in relative intensity as hypoxic conditions persisted. Significant changes in MFO and HFO rhythm generation during the transition from eupnea to gasping presumably reflect a reconfiguration of the respiratory network and/or alterations in signal processing by the circuitry associated with the two motor pools.

Detection of Life Characteristic Signals Based on High Order Statistics

2012 ◽  
Vol 239-240 ◽  
pp. 807-810
Author(s):  
Jian Jun Li ◽  
Jian Feng Zhao
Keyword(s):  
Order Statistics ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Time Estimation ◽  
High Order ◽  
Signal To Noise ◽  
Time Frequency ◽  
Noise Ratio ◽  
Short Time ◽  
High Order Statistics

Life parameters signal has characteristics of extremely low frequency, low signal-to-noise ratio, and the easy submerged in strong clutter noises. The method for detecting life signal based on filter bank and high order statistics is presented, in which neither the Gaussian supposition of the observed signal, nor a prior information about the waveform and arrival time of the observed signal is necessary. The principle of method is to separate the spectrum of input signal into many narrow frequency bands, whose Sub-band signal is followed by a short-time estimation of higher-order statistics so as to suppress Gaussian noises. Simulated results show that the method not only can completely descript life signals in the time-frequency domain, but improve the signal-to-noise ratio and the ability of detecting algorithm. Moreover, the method is effective and practical.

scholarly journals EVALUATION OF STRESS IN STEEL STRUCTURES USING ELECTROMAGNETIC METHODS BASED ON UTILIZATION OF MICROSTRIP ANTENNA SENSOR AND MONITORING OF AC MAGNETIZATION PROCESS

2016 ◽  
Vol 6 (4) ◽  
pp. 32-36 ◽  
Author(s):  
Przemysław Łopato ◽  
Grzegorz Psuj ◽  
Michał Herbko ◽  
Michał Maciusowicz
Keyword(s):  
Plastic Deformation ◽  
High Frequency ◽  
Magnetic Hysteresis ◽  
Low Frequency ◽  
Steel Structures ◽  
Magnetic Hysteresis Loop ◽  
Magnetization Process ◽  
Frequency Range ◽  
Frequency Method ◽  
Electromagnetic Methods

In this paper the results of utilization of electromagnetic methods operating in low and high frequency range for evaluation of stress state and plastic deformation in steel elements are presented. In low frequency range Barkhausen noise and magnetic hysteresis loop method for evaluation of stress level and growth of plastic deformation changes were utilized. The methods allow to monitor parameters related to magnetization process under AC filed. Additionally in this paper the possibility of utilization of high frequency method for estimation of deformation extent (i.e. elongation) caused by stress will be presented. In this experiment the frequency response (the reflection coefficient S11) is measured. The strong relation of antennas resonant frequency to patch dimensions is utilized in order to obtain information about deformation of the sample.

Sign in / Sign up

Export Citation Format

Share Document