Staff View: Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

During the service life of various civil, mechanical and aerospace structures, damage can nucleate, accumulate and propagate leading to out-of-service conditions which are dangerous and can sometimes collapse. Therefore, Structural Health Monitoring (SHM) is a crucial tool for identifying the presen...

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Main Author:	Seyed Alireza, Ravanfar
Format:	Thesis
Published:	2017
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://studentsrepo.um.edu.my/7435/1/All.pdf http://studentsrepo.um.edu.my/7435/6/seyed.pdf http://studentsrepo.um.edu.my/7435/
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spelling	my.um.stud.74352020-08-16T19:26:52Z Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar Seyed Alireza, Ravanfar TA Engineering (General). Civil engineering (General) During the service life of various civil, mechanical and aerospace structures, damage can nucleate, accumulate and propagate leading to out-of-service conditions which are dangerous and can sometimes collapse. Therefore, Structural Health Monitoring (SHM) is a crucial tool for identifying the presence and the evolution of possible damage. This thesis, investigates rigorously two paramount concerns of the SHM: damage detection and parametric system identification. The first proposed method is applied to detect crack damage in a structure. The location of the crack is identified by defining the damage index called relative wavelet packet entropy (RWPE). Then, the damage severities at the identified locations are assessed using genetic algorithm (GA), through defining a database to reveal the relationships between the energies obtained and damage severities. However, most of existing damage detection methods requires reference data which are not always available. Meanwhile, there has also been a pressing need for real-time monitoring to avoid sudden catastrophic disasters. Therefore, a new reference-free damage detection algorithm is proposed. The RWPE measurements of different sensor-to-sensor pairs are applied for defining the reference-free damage index (RDI) of each sensor location. To improve the proposed algorithm, GA was utilized to identify the best choice for ‘‘mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function. This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. Initially, the connection coefficients for the scaling function of the proper selection of Daubechies wavelets are developed to derive the velocity and displacement from the measured acceleration responses. Then, the next step is to define the dominant components according to the relative energy distributions of wavelet packet transform (WPT) components of the acceleration responses, and transforming the equations of motion of the system in the time-domain to a reduced representation of the equations of motion based on the WPT. Finally, the least square error minimization method is implemented across the dominant components to determine the structural parameters of a linear system. Moreover, wavelet multiresolution analysis is applied to identify the tangent stiffness matrix and the hysteresis-restoring force of nonlinear structural systems without prior assumptions about the nonlinear characteristics of the systems. To demonstrate the validity and accuracy of the methods, numerical and experimental studies are conducted on a beam element and subsequently on a three-story building model. Results indicate that the wavelet-based damage detection method precisely identified the location and severity of damages even without reference data. In addition, the structural parameters of a system can be accurately estimated through the proposed system identification methods for both cases of linear and nonlinear conditions. Moreover, the accuracy and reliability of the proposed methods are investigated on various damage scenarios with different levels of severity, and noise levels. 2017 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/7435/1/All.pdf application/pdf http://studentsrepo.um.edu.my/7435/6/seyed.pdf Seyed Alireza, Ravanfar (2017) Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/7435/
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Student Repository
url_provider	http://studentsrepo.um.edu.my/
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Seyed Alireza, Ravanfar Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
description	During the service life of various civil, mechanical and aerospace structures, damage can nucleate, accumulate and propagate leading to out-of-service conditions which are dangerous and can sometimes collapse. Therefore, Structural Health Monitoring (SHM) is a crucial tool for identifying the presence and the evolution of possible damage. This thesis, investigates rigorously two paramount concerns of the SHM: damage detection and parametric system identification. The first proposed method is applied to detect crack damage in a structure. The location of the crack is identified by defining the damage index called relative wavelet packet entropy (RWPE). Then, the damage severities at the identified locations are assessed using genetic algorithm (GA), through defining a database to reveal the relationships between the energies obtained and damage severities. However, most of existing damage detection methods requires reference data which are not always available. Meanwhile, there has also been a pressing need for real-time monitoring to avoid sudden catastrophic disasters. Therefore, a new reference-free damage detection algorithm is proposed. The RWPE measurements of different sensor-to-sensor pairs are applied for defining the reference-free damage index (RDI) of each sensor location. To improve the proposed algorithm, GA was utilized to identify the best choice for ‘‘mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function. This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. Initially, the connection coefficients for the scaling function of the proper selection of Daubechies wavelets are developed to derive the velocity and displacement from the measured acceleration responses. Then, the next step is to define the dominant components according to the relative energy distributions of wavelet packet transform (WPT) components of the acceleration responses, and transforming the equations of motion of the system in the time-domain to a reduced representation of the equations of motion based on the WPT. Finally, the least square error minimization method is implemented across the dominant components to determine the structural parameters of a linear system. Moreover, wavelet multiresolution analysis is applied to identify the tangent stiffness matrix and the hysteresis-restoring force of nonlinear structural systems without prior assumptions about the nonlinear characteristics of the systems. To demonstrate the validity and accuracy of the methods, numerical and experimental studies are conducted on a beam element and subsequently on a three-story building model. Results indicate that the wavelet-based damage detection method precisely identified the location and severity of damages even without reference data. In addition, the structural parameters of a system can be accurately estimated through the proposed system identification methods for both cases of linear and nonlinear conditions. Moreover, the accuracy and reliability of the proposed methods are investigated on various damage scenarios with different levels of severity, and noise levels.
format	Thesis
author	Seyed Alireza, Ravanfar
author_facet	Seyed Alireza, Ravanfar
author_sort	Seyed Alireza, Ravanfar
title	Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
title_short	Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
title_full	Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
title_fullStr	Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
title_full_unstemmed	Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
title_sort	vibration-based structural damage detection and system identification using wavelet multiresolution analysis / seyed alireza ravanfar
publishDate	2017
url	http://studentsrepo.um.edu.my/7435/1/All.pdf http://studentsrepo.um.edu.my/7435/6/seyed.pdf http://studentsrepo.um.edu.my/7435/
_version_	1738506020469080064
score	13.211869

Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

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