Recovery of Modal Information From a Beam Undergoing Random Vibration

1974 ◽  
Vol 96 (4) ◽  
pp. 1307-1313
Author(s):  
W. W. Parmenter ◽  
R. G. Christiansen
Keyword(s):  
Fourier Transform ◽  
Structural Analysis ◽  
Fast Fourier Transform ◽  
Random Process ◽  
Random Vibration ◽  
Structural Information ◽  
Process Theory ◽  
Acceleration Response ◽  
Vibration Data ◽  
Random Process Theory

An organized approach for implementing the techniques of random process theory in the recovery of structural information from random vibration data is presented. The boundaries of various configured Bernoulli-Euler like beams are subjected to random vibrations and the acceleration response of these beams is measured and recorded. The Fast Fourier Transform (FFT) makes the use of random process theory both a feasible and economical tool for experimental structural analysis.

A Study on Applicability of Predictive Maintenance and Vibration Data Analysis by Fast Fourier Transform into Major Equipment of Submarine

2021 ◽  
Vol 4 (1) ◽  
pp. 14-21
Author(s):  
Donghoon Kim ◽  
Sang Woo Kang ◽  
Ji Hoon Lee ◽  
Kyung Mo Nam ◽  
Seong Hun Seong ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Data Analysis ◽  
Fast Fourier Transform ◽  
Predictive Maintenance ◽  
Vibration Data ◽  
Major Equipment

A Simulation Method for Non-Gaussian Rough Surfaces Using Fast Fourier Transform and Translation Process Theory

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Yuechang Wang ◽  
Ying Liu ◽  
Gaolong Zhang ◽  
Yuming Wang
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Rough Surface ◽  
Tribological Behavior ◽  
Rough Surfaces ◽  
Simulation Method ◽  
Process Theory ◽  
Asperity Contact ◽  
Translation Process ◽  
Non Gaussian

The simulated rough surface with desired parameters is widely used as an input for the numerical simulation of tribological behavior such as the asperity contact, lubrication, and wear. In this study, a simulation method for generating non-Gaussian rough surfaces with desired autocorrelation function (ACF) and spatial statistical parameters, including skewness (Ssk) and kurtosis (Sku), was developed by combining the fast Fourier transform (FFT), translation process theory, and Johnson translator system. The proposed method was verified by several numerical examples and proved to be faster and more accurate than the previous methods used for the simulation of non-Gaussian rough surfaces. It is convenient to simulate the non-Gaussian rough surfaces with various types of ACFs and large autocorrelation lengths. The significance of this study is to provide an efficient and accurate method of non-Gaussian rough surfaces generation to numerically simulate the tribological behavior with desired rough surface parameters.

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