Uncertainty analysis of mechanical dynamics by combining response surface method with signal decomposition technique

Cui, Jiang; Zhao, Zhihua; Liu, Jiawei; Hu, Pengxiang; Zhou, Runeng; Ren, Gexue

doi:10.1016/j.ymssp.2020.107570

Cited by 18 publications

(10 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The mono-component is represented by the product function (PF), which is scaled by an envelope amplitude multiplied with a pure frequency modulated signal. In the procedure of uncertainty quantification for multibody systems, the implementation of LMD can alleviate the effect of instantaneous phase difference accumulation (IPDA) [5].…”

Section: Local Mean Decompositionmentioning

confidence: 99%

“…(7) The signal PF i (t) is subtracted from the original signal to update the residual signal u i (t) by u i (t) = u i (t) − PF i (t). Then, the new residual u i (t) is assigned to s ij (t) and steps (1)(2)(3)(4)(5)(6) are repeated for n times until u i (t) is a monotonic signal or contains no oscillations. Finally, the original signal can be decomposed as:…”

Section: Local Mean Decompositionmentioning

confidence: 99%

“…Research has shown that slight fluctuations of these uncertain parameters may cause significant deviation of the dynamic response [3]. Furthermore, the effect of uncertainty propagation in the procedure of dynamic analysis of mechanical systems attracts more and more attentions [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…After that, in this context, the Legendre polynomials [36] and the polynomial chaos expansion [37] are employed in the dynamic analysis of the multibody system under interval uncertainty. Additionally, the surrogate models constructed by the response surface method [5] and the Kriging model [38] are also presented in the procedure of interval propagation for multibody systems. In Cui's work [5], the signal decomposition technique was firstly introduced in the area of uncertainty analysis, and the RS-LMD method (response surface combing with local mean decomposition) was proposed to propagate interval uncertainty in the long time dependent dynamic analysis.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Interval Uncertainty Quantification for the Dynamics of Multibody Systems Combing Bivariate Chebyshev Polynomials with Local Mean Decomposition

Jiang

Bai

2022

Mathematics

View full text Add to dashboard Cite

Interval quantification for multibody systems can provide an accurate dynamic prediction and a robust reliability design. In order to achieve a robust numerical model, multiple interval uncertain parameters should be considered in the uncertainty propagation of multibody systems. The response bounds obtained by the bivariate Chebyshev method (BCM) present an intensive deterioration with the increase of time history in the interval dynamic analysis. To circumvent this problem, a novel method that combines the bivariate Chebyshev polynomial and local mean decomposition (BC-LMD) is proposed in this paper. First, the multicomponent response of the system was decomposed into the sum of several mono-component responses and a residual response, and the corresponding amplitude and phase of the mono-component were obtained. Then, the bivariate function decomposition was performed on the multi-dimensional amplitude, phase, and residual to transform a high-dimensional problem into several one-dimensional and two-dimensional problems. Subsequently, a low order Chebyshev polynomial can be used to construct surrogate models for the multi-dimensional amplitude, phase, and residual responses. Then, the entire coupling surrogate model of the system can be established, and the response bounds of the system can be enveloped. Illustrative examples of a slider-crank mechanism and a double pendulum are presented to demonstrate the effectiveness of the proposed method. The numerical results indicate that, compared to the BCM, BC-LMD can present a tight envelope in the long time-dependent dynamic analysis under multiple interval parameters.

show abstract

Section: Local Mean Decompositionmentioning

confidence: 99%

Section: Local Mean Decompositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interval Uncertainty Quantification for the Dynamics of Multibody Systems Combing Bivariate Chebyshev Polynomials with Local Mean Decomposition

Jiang

Bai

2022

Mathematics

View full text Add to dashboard Cite

show abstract

“…The optimal position of the roof low roadway is investigated, which can be used to pre-extraction gas from this seam to cover the coal roadway excavation, and also to extraction gas from the upper corner during mining. The experimental scheme is designed according to the response surface methodology 36 – 39 , and the response values are derived from the FLUENT numerical simulation experiments, and the optimal solution is predicted. The design of the roof low roadway has effectively managed the gas accumulation problem in the upper corner.…”

Section: Introductionmentioning

confidence: 99%

Study on the optimal position of the roof low roadway based on the response surface methodology

Zhu

Fang

Huo

et al. 2021

Sci Rep

View full text Add to dashboard Cite

For determine the optimum position of the roof low roadway, the optimal solution is derived according to the response surface methodology. The UDEC numerical simulation of the overburden gives the porosity distribution of the strike fractured zone, the upper limit heights of the caving zone and the fractured zone are obtained as 18 m and 65 m, respectively. Based on the porosity distribution, the FLUENT numerical models of the goaf zone, air inlet roadway, air return roadway, working face and roof low roadway were established to simulate the gas concentration in the upper corner and gas drainage volume in roof low roadway during mining. Using the vertical and horizontal distance of the roof low roadway as the influencing factors, the experimental scheme of the position of the roof low roadway was designed according to the response surface method, and the response values were obtained from the FLUENT simulation experiments, predicting that the vertical and horizontal distances of the roof low roadway were 7.7 m and 5.9 m respectively when the interaction between the gas concentration in the upper corner and gas drainage volume in roof low roadway was optimal. Field tests showed that the average gas concentration in the upper corner and the average gas drainage volume in roof low roadway were 0.432% and 40.861 m3/min respectively, both of which were less than 10% of the error from the simulations. The design of the roof low roadway has effectively managed the gas accumulation problem in the upper corner.

show abstract

A novel probabilistic analysis method for long-term dynamical response analysis

Meng,

Jin

2024

Acta Mech

View full text Add to dashboard Cite

Uncertainty analysis of mechanical dynamics by combining response surface method with signal decomposition technique

Cited by 18 publications

References 49 publications

Interval Uncertainty Quantification for the Dynamics of Multibody Systems Combing Bivariate Chebyshev Polynomials with Local Mean Decomposition

Interval Uncertainty Quantification for the Dynamics of Multibody Systems Combing Bivariate Chebyshev Polynomials with Local Mean Decomposition

Study on the optimal position of the roof low roadway based on the response surface methodology

A novel probabilistic analysis method for long-term dynamical response analysis

Contact Info

Product

Resources

About