Identification of the Mechanical Joint Parameters with Model Uncertainty

Guo, Quanquan; Zhang, Lingmi

doi:10.1016/s1000-9361(11)60281-1

Cited by 10 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( ) is the probability of the observed data which is usually considered as a constant. Equation 6 Hasting [40] proposed the Monte Carlo Markov Chain (MCMC) algorithm for sampling the posterior probability by using equation (6). A good description about using MCMC algorithm in the context of structural dynamics can be found in [41].…”

Section: Parameter Identification Proceduresmentioning

confidence: 99%

“…Lopez et al [5] considered the connection between two substructures of a space structure as random springs and investigated the uncertainty in structural responses such as FRFs due to the uncertainty in joint parameters. Guo and Zhang [6] identified the uncertainty in joint model parameters by using updating approaches. Castelluccio and Brake [7] employed FE simulation to investigate the model input and form uncertainties in threaded fasteners.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic modelling and updating of a joint contact interface

Jalali

Khodaparast

Madinei

et al. 2019

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

Dynamic properties of the contact interfaces in joints and mechanical connections have a great influence on the overall dynamic properties of assembled structures. Uncertainty and nonlinearity are two major effects of contact interfaces which introduce challenges in accurate modeling. Randomness in surface roughness quality, surface finish and contact preload are the main sources of variability in the contact interfaces. On the other side, slip and slap are two mechanisms responsible for nonlinear behavior of joints. Stochastic linear/nonlinear models need to be developed for such uncertain structures to be used in dynamic response analysis or system parameter identification. In this paper, variability in linear behavior of an assembled structure containing a bolted lap-joint is investigated by using experimental results. A stochastic model is then constructed for the structure by employing a stochastic generic joint model and the uncertainty in the joint model parameters is identified by using a Bayesian identification approach.

show abstract

Section: Parameter Identification Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stochastic modelling and updating of a joint contact interface

Jalali

Khodaparast

Madinei

et al. 2019

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

show abstract

“…In this section, we discuss the use of interval analysis in solving the simple structural problem of an elastic beam with uncertain boundary conditions, represented by elastic springs endowed with interval stiffness. In many applications structural joints are very different with respect to the way that they are modeled (e.g., elastic springs) and joints parameter identification is a key problem in the modeling of complex structures [8].…”

Section: Numerical Examplementioning

confidence: 99%

Influence of the Parameterization in the Interval Solution of Elastic Beams

Gabriele

Varano

2014

Journal of Structures

View full text Add to dashboard Cite

We are going to analyze the interval solution of an elastic beam under uncertain boundary conditions. Boundary conditions are defined as rotational springs presenting interval stiffness. Developments occur according to the interval analysis theory, which is affected, at the same time, by the overestimation of interval limits (also known as overbounding, because of the propagation of the uncertainty in the model). We suggest a method which aims to reduce such an overestimation in the uncertain solution. This method consists in a reparameterization of the closed form Euler-Bernoulli solution and set intersection.

show abstract

“…Reference [12] suggests a new method to synthesize kinematic chains--embryonic graph and branch chains. The metamorphic mechanisms designed by references [13] to [17] are also types of SAM. Their main feature is that the DOF can be changed during configuration transformation.…”

Section: Self-adaptive Mechanismmentioning

confidence: 99%

The Application of Self-Adaptive Design in Improvement of the Restoring Strand Operation Mechanism

Liu

2013

KEM

View full text Add to dashboard Cite

Aiming at solving the problem that the existing restoring strand operation mechanism cannot realize self-adaption to the variation of position and shape of transmission lines, a method for self-adaptive mechanism design is introduced and summarized to meliorate the mechanism. This method is effective and practical, which can be applied to most common mechanism design: first of all, analyze the structural features of the self-adaptive mechanism; secondly, establish a universal method to determine the structure type named as initial kinematic chain which contains information of the degree of freedom (DOF), the number of links and the kinematic relations between every two of them; finally, considering the features of the existing mechanism, apply the self-adaption design to realize the required mechanism by inverting the initial kinematic chain, and build models and simulations to prove that the improved mechanism does have the ability of self-adaption to the location and shape variation of transmission lines.

show abstract

Identification of the Mechanical Joint Parameters with Model Uncertainty

Cited by 10 publications

References 8 publications

Stochastic modelling and updating of a joint contact interface

Stochastic modelling and updating of a joint contact interface

Influence of the Parameterization in the Interval Solution of Elastic Beams

The Application of Self-Adaptive Design in Improvement of the Restoring Strand Operation Mechanism

Contact Info

Product

Resources

About