Bayesian Model Updating Approach for Systematic Damage Detection of Plate-Type Structures

2012 ◽  
pp. 85-94 ◽  
Author(s):  
Masahiro Kurata ◽  
Jerome P. Lynch ◽  
Kincho H. Law ◽  
Liming W. Salvino
Keyword(s):  
Damage Detection ◽  
Bayesian Model ◽  
Model Updating ◽  
Plate Type

scholarly journals Probabilistic Damage Detection and Identification of Coupled Structural Parameters using Bayesian Model Updating with Added Mass

2021 ◽  
Author(s):  
jice zeng ◽  
Young Hoon Kim
Keyword(s):  
Convergence Rate ◽  
Damage Detection ◽  
Bayesian Model ◽  
Model Updating ◽  
Coupling Effect ◽  
Structural Parameters ◽  
Added Mass ◽  
Distribution Functions ◽  
Single Chain ◽  
Characteristic Equations

Damage detection inevitably involves uncertainties originated from measurement noise and modeling error. It may cause incorrect damage detection results if not appropriately treating uncertainties. To this end, vibration-based Bayesian model updating (VBMU) is developed to utilize vibration responses or modal parameters to identify structural parameters (e.g., mass and stiffness) as probability distribution functions (PDF) and uncertainties. However, traditional VBMU often assumes that mass is well known and invariant because simultaneous identification of mass and stiffness may yield an unidentifiable problem due to the coupling effect of the mass and stiffness. In addition, the posterior PDF in VBMU is usually approximated by single-chain based Markov Chain Monte Carlo (MCMC), leading to a low convergence rate and limited capability for complex structures. This paper proposed a novel VBMU to address the coupling effect and identify mass and stiffness by adding known mass. Two vibration data sets are acquired from original and modified systems with added mass, giving the new characteristic equations. Then, the posterior PDF is reformulated by measured data and predicted counterparts from new characteristic equations. For efficiently approximating the posterior PDF, Differential Evolutionary Adaptive Metropolis (DREAM) Algorithm are adopted to draw samples by running multiple Markov chains parallelly to enhance convergence rate and sufficiently explore possible solutions. Finally, a numerical example with a ten-story shear building and a laboratory-scale three-story frame structure are utilized to demonstrate the efficacy of the proposed VBMU framework. The results show that the proposed method can successfully identify both mass and stiffness, and their uncertainties. Reliable probabilistic damage detection can also be achieved.

Damage detection in an offshore platform using incomplete noisy FRF data by a novel Bayesian model updating method

2020 ◽  
Vol 217 ◽  
pp. 108023 ◽  
Author(s):  
Amin Fathi ◽  
Akbar Esfandiari ◽  
Manouchehr Fadavie ◽  
Alireza Mojtahedi
Keyword(s):  
Damage Detection ◽  
Bayesian Model ◽  
Model Updating ◽  
Offshore Platform

A Probabilistic Model Updating Algorithm for Fatigue Damage Detection in Aluminum Hull Structures

2010 ◽  
Author(s):  
Masahiro Kurata ◽  
Jun-Hee Kim ◽  
Jerome P. Lynch ◽  
Kincho H. Law ◽  
Liming W. Salvino
Keyword(s):  
Damage Detection ◽  
Bayesian Model ◽  
High Speed ◽  
Model Updating ◽  
Detection Method ◽  
Residual Life ◽  
Search Space ◽  
Computational Effort ◽  
Detection Approach ◽  
Naval Engineering

The use of aluminum alloys in the design of naval structures offers the benefit of light-weight ships that can travel at high-speed. However, the use of aluminum poses a number of challenges for the naval engineering community including higher incidence of fatigue-related cracks. Early detection of fatigue induced cracks enhances maintenance of the ships and is critical for preventing the catastrophic failure of the hull. Furthermore, monitoring the integrity of the aluminum hull can provide valuable information for estimating the residual life of hull components. This paper presents a model-based damage detection methodology for fatigue assessment of hulls that are instrumented with a long-term hull monitoring system. At the core of the data driven damage detection approach is a Bayesian model updating algorithm enhanced with systematic enumeration and pruning of candidate solutions. The Bayesian model updating approach significantly reduce the computational effort by systematically narrowing the search space using errors functions constructed using the estimated modal properties associated with the condition of the structure. This study proposes the use of the Bayesian model updating technique to detect damage in an aluminum panel modeled using high-fidelity finite element models. The performance of the proposed damage detection method is tested through simulation of a progressively growing fatigue crack introduced in the vicinity of a welded stiffener element. An experimental study verifies the accuracy of the proposed damage detection method using an aluminum plate excited with a controlled excitation in the laboratory.

Structural Damage Assessment Using Output-Only Measurement: Localization and Quantification

2013 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Null Space ◽  
Singular Spectrum Analysis ◽  
Damage Index ◽  
Computation Efficiency ◽  
Output Only

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.

Automated model updating of multiple cracked cantilever beams for damage detection

2017 ◽  
Vol 138 ◽  
pp. 499-512 ◽  
Author(s):  
Ahmet Can Altunışık ◽  
Fatih Yesevi Okur ◽  
Volkan Kahya
Keyword(s):  
Damage Detection ◽  
Model Updating ◽  
Cantilever Beams

VIBRATION-BASED STRUCTURAL DAMAGE DETECTION UNDER VARYING TEMPERATURE CONDITIONS

2013 ◽  
Vol 13 (05) ◽  
pp. 1250082 ◽  
Author(s):  
XIAO-QING ZHOU ◽  
WEN HUANG
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Environmental Changes ◽  
Model Updating ◽  
Modal Testing ◽  
Structural Damage Detection ◽  
Vibration Data ◽  
Temperature Conditions ◽  
Vibration Properties

In vibration-based structural damage detection, it is necessary to discriminate the variation of structural properties due to environmental changes from those caused by structural damages. The present paper aims to investigate the temperature effect on vibration-based structural damage detection in which the vibration data are measured under varying temperature conditions. A simply-supported slab was tested in laboratory to extract the vibration properties with modal testing. The slab was then damaged and the modal testing was conducted again, in which the temperature varied. The modal data measured under different temperature conditions were used to detect the damage with a two-stage model updating technique. Some damage was falsely detected if the temperature variation was not considered. Natural frequencies were then corrected to those under the same temperature conditions according to the relation between the temperature and material modulus. It is shown that all of the damaged elements can be accurately identified.

Sign in / Sign up

Export Citation Format

Share Document