Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Civil and Environmental Engineering | en_US |
| dc.contributor.advisor | Ni, Y. Q. (CEE) | en_US |
| dc.creator | Moradi Pour, Parviz | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/10684 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | An improved modal strain energy method for bridge damage identification | en_US |
| dcterms.abstract | Increasing the importance of infrastructures demands an effective and timely structural health monitoring (SHM) systems. Structural damage detection using modal strain energy (MSE) is one of the efficient and reliable SHM techniques. However, some existing MSE methods have been validated only for special types of the structures such as beams or steel truss bridges or have had an unsatisfactory performance. This circumstance demands either improving the available methods or proposing new approaches. The current study focuses on improving a two-stage MSE-based damage detection method to accurately detect and quantify the damage in bridges. Primarily, it is attempted to more accurately establish an equation for the MSE stored in each element of the structure before and after the damage. This can be achieved by mathematically considering the actual damaged stiffness matrix into the traditional MSE equation as an unknown parameter. Establishing a more exact amount of MSE change during the damage leads to attaining a more sensitive matrix which assists realizing the damage more accurately at an early stage of forming with higher reliability. It is also tried to generalize the improved method to be applicable for any bridge. The improved MSE method for detecting the structural damage has two consequent stages, stage one, locating the damage, and stage two, quantifying the damage. The crucial key for identifying the location of damage in the structure is to calculate the elemental MSE change of the structure before and after the damage. Therefore, an elemental MSE-based indicator is used to show the ratio of the MSE change for each element. The elements with the higher amount of MSE change ratio are the most likely elements to be damaged and are nominated for further investigation in the second stage. Sensitivity matrix is used to quantify the damage which is a matrix derived from MSE change with respect to extent of the damage as an unknown independent variable. To validate the improved method, numerical studies are performed on some structures including, a fixed-end beam, a three-story frame, a steel truss bridge and a concrete bridge frame model. Consequently, experimental verifications are conducted on a simply supported beam, a cantilever beam and a threestory steel frame model. To examine the application of the improved method to a real model also, it is applied to the 4-DOF three-story structure of Los Alamos National Laboratory (LANL). In most of the numerical verifications, different scenarios including single and multiple damages, affected by up to seven percent noise are considered. Finally, to observe the applicability of the improved method in reality, it is applied to the I-40 Bridge in New Mexico; the USA using the available data. The results indicate that the improved method is able to detect any single or multiple damage at any element or node of the structure at most of the cases studied. In numerical case studies, the improved method is precisely able to detect and quantify the damage with minimal error. However, in experimental case studies, real structure and bridge, there are few errors because of some sources such as the difference between physical structure and FEM model, material properties modelling, incomplete and limited measurements, data processing, software and unknown factors and uncertainties. According to the findings of this dissertation the improved method is proper for health monitoring of complex bridges and well identifies the damage in the most cases and being more accurate and efficient than its predecessors in terms of well recognition of the location of the damage and identifying its extent. The findings of this study can confidently contribute to academic studies and bridge industry to realize the genuine condition and behaviour of complex bridges during the damage to minimize the loss of lives and property by identifying the unforeseen structural damages. | en_US |
| dcterms.extent | xxvii, 219 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2018 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Bridges -- Evaluation | en_US |
| dcterms.LCSH | Bridges -- Maintenance and repair | en_US |
| dcterms.LCSH | Structural health monitoring | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
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