In this study, we focused mainly on establishing a new sensitive method to identify location of damages in Service Bridge. The improved method of combination of Autoregressive models (AR) and autoregressive models with exogenous inputs (ARX) was applied to identify the damage in Service Bridge. Firstly, an improved AR-ARX model was established for damage identification of bridge on service. Sec...

We present an exact algebraic algorithm for real-time continuous collision detection (CCD) for moving ellipsoids under affine deformations. An efficient collision test is first developed for two static ellipsoids, which takes less than 1 microsecond. Using this practical result and the properties of our algebraic condition, we produce a real-time solution to the CCD problem that computes the ex...

In this research, the problem of structural damage detection using noisy frequency response function information is addressed. A methodology for damage detection is proposed that uses an unconstrained optimization problem formulation. To solve the optimization problem genetic algorithms (GA) and a local hillclimbing procedure were used. The inherent unstructured nature of damage detection probl...

This paper investigates potential applications of the rough sets (RS) theory and artificial neural network (ANN) method on structural damage detection. An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA). The proposed approach is tested with a 14-bay steel truss model for struc...

A wireless sensing unit is designed for application in structural monitoring and damage detection system. Embedded in the wireless monitoring module, a two-tier prediction model, using auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX) is used for obtaining the damage sensitive feature. To validate the performance of the proposed wireless monitoring and damage detecti...