@mastersthesis {992, title = {Synthesis of multiaxis stationary non-Gaussian shaped vibration}, year = {2020}, school = {University of Vigo}, address = {Vigo}, abstract = {
Random vibration is present in many fi elds of engineering, although one where it has particular relevance is the industry of ground transportation. The interaction between the wheels and the road induces vibration that transmits to all the components in the vehicle, as well as to the passengers, producing mechanical damage, noise and discomfort. It is hence important to address the effect of vibration during the design and validation phases of development of the vehicle. For that purpose, a method for the synthesis of signals that can be used for numerical simulation or physical testing of the system being designed is needed. In this thesis, an algorithm for the synthesis of random vibration signals is developed, that takes into account the multiaxial and non-Gaussian nature of the process allowing individual adjustment of the kurtosis of the different degrees-of-freedom involved. The proposed algorithm avoids distortion of the spectrum when the kurtosis is being adjusted hence allowing for independent control of the spectral and kurtosis properties of the process. Theoretical expressions relating the control parameters to the kurtosis and the spectrum of the process are provided. An additional bene fit of the proposed algorithm is the possibility to modify the higher-order moments beyond the kurtosis.
}, keywords = {multiaxial vibration, random vibration, vibration synthesis}, author = {Dami{\'a}n Gonz{\'a}lez} } @article {948, title = {Maximally stationary window design for overlap-add based random vibration synthesis}, journal = {Mechanical Systems and Signal Processing}, volume = {122}, year = {2019}, month = {05/2019}, pages = {642-657}, abstract = {
The accurate synthesis of realistic waveforms conforming to certain speci ca-
tions is a fundamental step in random vibration testing. Since real-time imple-
mentation of digital signal processing systems for random vibration and noise
synthesis necessarily operates frame by frame, the overlap-add (OLA) method,
by which frames are windowed and overlapped, is widely used in practice to
avoid artifacts at frame boundaries. When a wide-sense stationary random
signal is desired, however, the OLA method presents a shortcoming, because
the inherent periodicity of the frame-by-frame process unavoidably produces a
cyclostationary signal, i.e., its statistics present an undesired periodic behav-
ior. We analyze the impact of the window coecients in the cyclostationarity
properties of the synthetic process, and then present algorithms for window de-
sign with the goal of maximizing a measure of its stationarity, considering both
second- and fourth-order statistical properties. The proposed designs are shown
to signi cantly improve the stationarity properties when compared to commonly
used windows.
}, keywords = {random vibration}, doi = {10.1016/j.ymssp.2018.12.038}, author = {Dami{\'a}n Gonz{\'a}lez and R. L{\'o}pez-Valcarce} } @conference {931, title = {Spectral and statistical evaluation of the properties of the vibration measured at the base of an automotive seat for non-Gaussian random noise synthesis}, booktitle = {Int. Conf. on Noise and Vibration Engineering, ISMA-USD 2018}, year = {2018}, month = {09/2018}, address = {Leuven, Belgium}, abstract = {
The first step in the definition of the specifications for the vibration tests of any automotive component
is the recording and evaluation of the properties of the input vibration during field measurements. In this
paper, we explore the properties of the vibration measured at the base of the driver seat when driving
through different surfaces, with the purpose of defining a model for non-Gaussian random vibration
testing. The recorded acceleration signals are first transformed to a 6 Degree of Freedom (DOF) space,
and then segmented into stationary sections that are later analyzed. The non-Gaussian nature of the
recorded vibration is demonstrated through different Gaussianity hypothesis tests, and the distribution of
the third and fourth order moments, as well as the crest factor, are computed and analyzed. The second-order\ 
spectral content reveals significant correlation at specific frequencies, while the significance of
third order polyspectra is checked through hypothesis testing. Based on our observations, a practical
definition of the random process is proposed based on second-order spectral content, univariate kurtosis
and crest factor levels.
}, keywords = {random vibration}, author = {Dami{\'a}n Gonz{\'a}lez and R. L{\'o}pez-Valcarce} }