@Article{sv.2020.09783,
AUTHOR = {Nan Wu, Kuan Lu, Yulin Jin, Haopeng Zhang, Yushu Chen},
TITLE = {The Applications of Order Reduction Methods in Nonlinear Dynamic Systems},
JOURNAL = {Sound \& Vibration},
VOLUME = {54},
YEAR = {2020},
NUMBER = {2},
PAGES = {113--125},
URL = {http://www.techscience.com/sv/v54n2/38974},
ISSN = {2693-1443},
ABSTRACT = {Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal
decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD
method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional
decomposition (PDD) method is applied to the 2 DOFs spring system considering
the uncertain stiffness to study the amplitude-frequency response. The numerical
results obtained by the PDD method agree well with the Monte Carlo simulation
(MCS) method. The results of the PDD method can approximate to MCS better
with the increasing of the polynomial order. Meanwhile, the Uniform-Legendre
polynomials can eliminate perturbation of the PDD method to a certain extent
via comparing it with the Gaussian-Hermite polynomials.},
DOI = {10.32604/sv.2020.09783}
}