Novel Footstep Features Using Dominant Frequencies for Personal Recognition

2021 ◽  
pp. 1-1
Author(s):  
Fuxiang Liu ◽  
Qi Jiang
Keyword(s):  
Personal Recognition ◽  
Dominant Frequencies

Experimental Measurement of In-Plane Rolling Nonpneumatic Tire Vibrations Using High-Speed Imaging

2019 ◽  
Vol 47 (3) ◽  
pp. 196-210
Author(s):  
Meghashyam Panyam ◽  
Beshah Ayalew ◽  
Timothy Rhyne ◽  
Steve Cron ◽  
John Adcox
Keyword(s):  
High Speed ◽  
Image Correlation ◽  
Dynamic Mode Decomposition ◽  
Dynamic Mode ◽  
High Speed Imaging ◽  
Correlation Algorithm ◽  
Mode Decomposition ◽  
Series Of Experiments ◽  
Plane Deformations ◽  
Dominant Frequencies

ABSTRACT This article presents a novel experimental technique for measuring in-plane deformations and vibration modes of a rotating nonpneumatic tire subjected to obstacle impacts. The tire was mounted on a modified quarter-car test rig, which was built around one of the drums of a 500-horse power chassis dynamometer at Clemson University's International Center for Automotive Research. A series of experiments were conducted using a high-speed camera to capture the event of the rotating tire coming into contact with a cleat attached to the surface of the drum. The resulting video was processed using a two-dimensional digital image correlation algorithm to obtain in-plane radial and tangential deformation fields of the tire. The dynamic mode decomposition algorithm was implemented on the deformation fields to extract the dominant frequencies that were excited in the tire upon contact with the cleat. It was observed that the deformations and the modal frequencies estimated using this method were within a reasonable range of expected values. In general, the results indicate that the method used in this study can be a useful tool in measuring in-plane deformations of rolling tires without the need for additional sensors and wiring.

scholarly journals Vibrational and Acoustical Characteristics of Ear Pinna Simulators That Differ in Hardness

2021 ◽  
Vol 11 (3) ◽  
pp. 327-334
Author(s):  
Ryota Shimokura ◽  
Tadashi Nishimura ◽  
Hiroshi Hosoi
Keyword(s):  
External Auditory Canal ◽  
Sound Pressure ◽  
Bone Conduction ◽  
Calibration Method ◽  
Vibration Acceleration ◽  
Spectral Peaks ◽  
Ear Cartilage ◽  
A Current ◽  
Air Conduction ◽  
Dominant Frequencies

Because cartilage conduction—the transmission of sound via the aural cartilage—has different auditory pathways from well-known air and bone conduction, how the output volume in the external auditory canal is stimulated remains unknown. To develop a simulator approximating the conduction of sound in ear cartilage, the vibrations of the pinna and sound in the external auditory canal were measured using pinna simulators made of silicon rubbers of different hardness (A40, A20, A10, A5, A0) as measured by a durometer. The same procedure, as well as a current calibration method for air conduction devices, was applied to an existing pinna simulator, the Head and Torso Simulator (hardness A5). The levels for vibration acceleration and sound pressure from these pinna simulators show spectral peaks at dominant frequencies (below 1.5 kHz) for the conduction of sound in cartilage. These peaks were likely to move to lower frequencies as hardness decreases. On approaching the hardness of actual aural cartilage (A10 to A20), the simulated levels for vibration acceleration and sound pressure approximated the measurements of human ears. The adjustment of the hardness used in pinna simulators is an important factor in simulating accurately the conduction of sound in cartilage.

scholarly journals Acoustic communication and the evolution of hearing in fishes

2000 ◽  
Vol 355 (1401) ◽  
pp. 1285-1288 ◽  
Author(s):  
Friedrich Ladich
Keyword(s):  
Inner Ear ◽  
Acoustic Communication ◽  
Acoustic Signals ◽  
Spectral Content ◽  
Auditory Thresholds ◽  
Selective Pressures ◽  
Vocal Signals ◽  
Species Specific ◽  
Hearing Abilities ◽  
Dominant Frequencies

Fishes have evolved a diversity of sound–generating organs and acoustic signals of various temporal and spectral content. Additionally, representatives of many teleost families such as otophysines, anabantoids, mormyrids and holocentrids possess accessory structures that enhance hearing abilities by acoustically coupling air–filled cavities to the inner ear. Contrary to the accessory hearing structures such as Weberian ossicles in otophysines and suprabranchial chambers in anabantoids, sonic organs do not occur in all members of these taxa. Comparison of audiograms among nine representatives of seven otophysan families from four orders revealed major differences in auditory sensitivity, especially at higher frequencies (> 1kHz) where thresholds differed by up to 50 dB. These differences showed no apparent correspondence to the ability to produce sounds (vocal versus non–vocal species) or to the spectral content of species–specific sounds. In anabantoids, the lowest auditory thresholds were found in the blue gourami Trichogaster trichopterus , a species not thought to be vocal. Dominant frequencies of sounds corresponded with optimal hearing bandwidth in two out of three vocalizing species. Based on these results, it is concluded that the selective pressures involved in the evolution of accessory hearing structures and in the design of vocal signals were other than those serving to optimize acoustic communication.

A periodic seismic isolation foundation with an extremely broad low-frequency attenuation zone: Theoretical analysis and experimental verification

2021 ◽  
pp. 136943322110646
Author(s):  
Peng Zhou ◽  
Shui Wan ◽  
Xiao Wang ◽  
Yingbo Zhu ◽  
Muyun Huang
Keyword(s):  
Seismic Isolation ◽  
Seismic Waves ◽  
Periodic Structures ◽  
Finite Size ◽  
Low Frequency ◽  
Bridge Structure ◽  
Engineering Structures ◽  
P Waves ◽  
New Type ◽  
Dominant Frequencies

The attenuation zones (AZs) of periodic structures can be used for seismic isolation design. To cover the dominant frequencies of more seismic waves, this paper proposes a new type of periodic isolation foundation (PIF) with an extremely wide low-frequency AZ of 3.31 Hz–17.01 Hz composed of optimized unit A with a wide AZ and optimized unit B with a low-frequency AZ. The two kinds of optimized units are obtained by topology optimization on the smallest periodic unit with the coupled finite element-genetic algorithm (GA) methodology. The transmission spectra of shear waves and P-waves through the proposed PIF of finite size are calculated, and the results show that the AZ of the PIF is approximately the superposition of the AZs of the two kinds of optimized units. Additionally, shake tests on a scale PIF specimen are performed to verify the attenuation performance for elastic waves within the designed AZs. Furthermore, numerical simulations show that the acceleration responses of the bridge structure with the proposed PIF are attenuated significantly compared to those with a concrete foundation under the action of different seismic waves. Therefore, the newly proposed PIF is a promising option for the reduction of seismic effects in engineering structures.

Real Time Conditioning Monitoring for Failure Prediction

2017 ◽  
Author(s):  
J. Alejandro Franco-Piña ◽  
Luis Contreras ◽  
Juan C. Jauregui
Keyword(s):  
Real Time ◽  
Frequency Spectrum ◽  
Oil Quality ◽  
Electrical Current ◽  
Processing Method ◽  
Power Capacity ◽  
Data Processing Method ◽  
Field Programmable ◽  
Maintenance Activities ◽  
Dominant Frequencies

Nowadays, the growth in the diameter of the rotors and the power capacity of the machinery require the application of constant monitoring to predict failures and reduce maintenance activities. These activities prevent emergency stops and failures that require the replacement of components; however, these operations involve a high cost. The system presented in this paper integrates a fast data processing method that can analyze monitoring signals in real-time. The overall system includes a set of sensors for the measurement of acceleration, angular velocity, temperature, voltage, electrical current, and oil quality. The system presented is able to produce a frequency spectrum with a length of 8192 points. The FFT module was implemented in a FPGA (Field Programmable Gate Array) and it generates in real time, the frequency spectrum. This system adjusts the dominant frequencies to the wind turbine velocity.

scholarly journals A simple conceptual model to interpret the 100 000 years dynamics of paleo-climate records

2010 ◽  
Vol 17 (5) ◽  
pp. 585-592 ◽  
Author(s):  
C. S. Quiroga Lombard ◽  
P. Balenzuela ◽  
H. Braun ◽  
D. R. Chialvo
Keyword(s):  
Large Scale ◽  
Power Spectra ◽  
Greenland Ice Sheet ◽  
Ice Age ◽  
Solar Cycles ◽  
The Holocene ◽  
De Vries ◽  
Last Ice Age ◽  
Paleoclimate Records ◽  
Dominant Frequencies

Abstract. Spectral analyses performed on records of cosmogenic nuclides reveal a group of dominant spectral components during the Holocene period. Only a few of them are related to known solar cycles, i.e., the De Vries/Suess, Gleissberg and Hallstatt cycles. The origin of the others remains uncertain. On the other hand, time series of North Atlantic atmospheric/sea surface temperatures during the last ice age display the existence of repeated large-scale warming events, called Dansgaard-Oeschger (DO) events, spaced around multiples of 1470 years. The De Vries/Suess and Gleissberg cycles with periods close to 1470/7 (~210) and 1470/17 (~86.5) years have been proposed to explain these observations. In this work we found that a conceptual bistable model forced with the De Vries/Suess and Gleissberg cycles plus noise displays a group of dominant frequencies similar to those obtained in the Fourier spectra from paleo-climate during the Holocene. Moreover, we show that simply changing the noise amplitude in the model we obtain similar power spectra to those corresponding to GISP2 δ18O (Greenland Ice Sheet Project 2) during the last ice age. These results give a general dynamical framework which allows us to interpret the main characteristic of paleoclimate records from the last 100 000 years.

Spectral characterization of ciliary beating: variations of frequency with time

1985 ◽  
Vol 249 (1) ◽  
pp. C160-C165 ◽  
Author(s):  
D. Eshel ◽  
Y. Grossman ◽  
Z. Priel
Keyword(s):  
Mathematical Model ◽  
Power Spectra ◽  
Ciliary Beating ◽  
Isolated Lung ◽  
Ciliary Cell ◽  
The Mathematical Model ◽  
Beating Frequency ◽  
Over Time ◽  
Dominant Frequencies

Ciliary beating frequency in tissue culture from frog palate and isolated lung was optically examined using instrumentation that was adjusted to measure a fraction of the surface area of a single ciliary cell. Consecutive 1-s segments of the analogue signal were fast Fourier transformed (FFT) to obtain a power spectrum. At room temperature, these power spectra changed over time from 1 s to the next. Each spectrum contained several dominant frequencies of similar intensities. Cooling the preparation resulted in a single-peak spectrum that was constant over time. A mathematical model is proposed to simulate these findings. The results and the mathematical model support the hypothesis that ciliary beating frequency fluctuates over short periods of time.

scholarly journals Time series analysis of trial-to-trial variability of MEG power spectrum during rest state, unattented listening and frequency-modulated tones classification

2021 ◽  
Author(s):  
Lech Kipiński ◽  
Wojciech Kordecki
Keyword(s):  
Stochastic Process ◽  
Time Series ◽  
Power Spectrum ◽  
Spectral Density ◽  
Cognitive Task ◽  
Clinical Neuroscience ◽  
Rest State ◽  
Short Time ◽  
Low Complex ◽  
Dominant Frequencies

AbstractThe nonstationarity of EEG/MEG signals is important for understanding the functioning of human brain. From the previous research we know that even very short, i.e. 250—500ms MEG signals are variance-nonstationary. The covariance of stochastic process is mathematically associated with its spectral density, therefore we investigate how the spectrum of such nonstationary signals varies in time.We analyze the data from 148-channel MEG, that represent rest state, unattented listening and frequency-modulated tones classification. We transform short-time MEG signals to the frequency domain using the FFT algorithm and for the dominant frequencies 8—12 Hz we prepare the time series representing their trial-to-trial variability. Then, we test them for level- and trend-stationarity, unit root, heteroscedasticity and gaussianity and based on their properties we propose the ARMA-modelling for their description.The analyzed time series have the weakly stationary properties independently of the functional state of brain and localization. Only their small percentage, mostly related to the cognitive task, still presents nonstationarity. The obtained mathematical models show that the spectral density of analyzed signals depends on only 2—3 previous trials.The presented method has limitations related to FFT resolution and univariate models, but it is not computationally complicated and allows to obtain a low-complex stochastic models of the EEG/MEG spectrum variability.Although the physiological short-time MEG signals are in principle nonstationary in time domain, its power spectrum at the dominant frequencies varies as weakly stationary stochastic process. Described technique has the possible applications in prediction of the EEG/MEG spectral properties in theoretical and clinical neuroscience.

Sign in / Sign up

Export Citation Format

Share Document