Random Vibration Fatigue - A Study Comparing Time Domain and Frequency Domain Approaches for Automotive Applications

2014 ◽  
Author(s):  
Giovanni Morais Teixeira
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Random Vibration ◽  
Automotive Applications ◽  
Vibration Fatigue

Random Vibration Fatigue: Frequency Domain Critical Plane Approaches

2013 ◽  
Author(s):  
Giovanni de Morais Teixeira ◽  
Radwan Hazime ◽  
John Draper ◽  
Dewi Jones
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Input Signal ◽  
Random Vibration ◽  
Equivalent Stress ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
System Response ◽  
Valuable Insight ◽  
Critical Plane

Frequency domain analysis offers a very efficient method for the fatigue durability assessment of structures subjected to vibration loading. It also allows engineers to gain valuable insight into system behavior and characteristics that are not easily recognized in the time domain. With some reasonable assumptions, most importantly linearity and steady state behavior, the response of a structure in many engineering applications can be simply evaluated through the “scaling” of the input signal by the Frequency Response Functions (FRFs). In cases where the input is random or stochastic in nature additional assumptions are needed to assess the behavior of the system. Usually such cases assume a stationary and ergodic input signal with a zero mean Gaussian distribution. When making such assumptions the system is still characterized by its FRFs. However, since the input signal is random it can be best described by its Power Spectral Density (PSD). Furthermore, the system response (characterized by the stress tensor) can be evaluated by “scaling” the PSD of the input signal(s) by the magnitude squared of the stress FRFs. The linearity assumption also allows the evaluation of a system response due to multiple inputs through superposition principles. When using stress based fatigue (to assess the durability of a component or a structure) there are several damage evaluation methodologies that can be used. Traditionally, for time domain analysis the von Mises equivalent stress had been the methodology of choice. More recently critical plane search methods have gained popularity and have shown much better correlation with laboratory experiments and field failures, especially under multi-axial and non-proportional loading. Some of these methods have found their way into frequency domain analysis. This paper highlights the application of critical plane methods for the multi-axial fatigue assessment of engineering structures that are subjected to non-deterministic random vibration. A case study is presented to illustrate the process and shows how the proposed method works.

JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

2018 ◽  
Vol 12 (7-8) ◽  
pp. 76-83
Author(s):  
E. V. KARSHAKOV ◽  
J. MOILANEN
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Interval ◽  
Single Spectrum ◽  
Simultaneous Inversion ◽  
Homogeneous Half Space ◽  
Time Domain Data ◽  
The Time Domain

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

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