Sharif Digital Repository

Damage detection of civil structures and infrastructures using partial modal information has been an interesting field of research. So far, three main algorithms are introduced for health monitoring of structures. The first method relies on identifying stiffness and mass properties, as physical parameters, of structures using inverse eigenvalue problem considering mass modifications in 2D and 3D shear-frame models of structures. Comparing the identified matrices with the primary values, one can detect the damage occurrence, its level and severity in the structure. Applicability of this method in health monitoring of offshore jacket platforms as one of noteworthy civil infrastructures has... 

Under conventional seismic design strategies, civil engineering structures are designed to undergo inelastic deformation to dissipate earthquake energy, leading to residual displacements and nonlinear deformations in the structure. As a result, there is an essential need for structural health monitoring methods to detect and process these nonlinear behaviors. In this dissertation, a model-free Hysteresis Loop Analysis (HLA) method is developed to identify damage and monitor the structure's performance online, under the earthquake excitations in both severe linear and nonlinear scenarios. The structural models used to validate this method includes three types of one-story, five-story, and... 

Structural health monitoring is a process that aims to provide accurate and immediate information about the condition and performance of the structure. Processed is a very important eld in the eld of civil, aerospace and marine engineering, because the use of structural health monitoring allows us to increase human and environmental safety while reducing economic damage. e main component of the health monitoring process is the real-time reconstruction of displacement and three-dimensional stress in the structure using a network of strain gauges and other sensors. e inverse nite element method is a relatively new method and stress measurement that has been shown to be fast and accurate for... 

Damage and collapse of structural systems due to externally applied loadings, are inevitable, which cause financial and human losses. Therefore, the application of structural health monitoring (SHM) strategies has attracted a lot of attention in order to estimate structural damages, optimal maintenance and preventing structural collapse. Hence, in recent decades, the development of research activities in the field of structural health monitoring and its application in civil engineering, has led to the invention of various techniques and methods in assessing the safety of structures. These methods not only should be accurate enough for confidently identifying diverse severity of damages, but... 

Civil structures are on the verge of changing which leads energy dissipation capacity to decline. Structural Health Monitoring (SHM) as a process in order to implement a damage detection strategy and assess the condition of structure plays a key role in structural reliability. Earthquake is a recognized factor in variation of structures condition, inasmuch as inelastic behavior of a building subjected to design level earthquakes is plausible. In this study Hilbert Hunag Transformation (HHT) is superseded by Ensemble Empirical Mode decomposition (EEMD) and Hilbert Transform (HT) together. Albeit this method is closely resemble HHT, EEMD brings more appropriate Intrinsic Mode Functions (IMFs).... 

Structural Health Monitoring (SHM) of civil infrastructures is of paramount importance in ensuring the safety and reliability of these structures. SHM involves the use of sensors and data analysis techniques to continuously monitor the structural condition of infrastructure, detect damage or degradation, and provide insights for maintenance and repair. Concrete cracks are one of the most common and critical types of damage in civil infrastructure, which can compromise the structural integrity and safety of the infrastructure if left undetected and untreated. Therefore, the development of effective and efficient crack detection techniques using computer vision and machine learning can... 

Karun 4 arch concrete dam with a height of 230 meters is designed and built in one of the most complex natural places. Therefore, monitoring the behavior and evaluating the safety and stability of this dam, both with regard to the height and nature of the dam itself and with regard to its national and international dimensions, is of special importance and sensitivity. This sensitivity is doubled due to some problems and issues encountered in the body of the Karun 4 dam, which of course are considered probable and possible phenomena in arch concrete dams. The Karun 4 Dam construction site is located in the southwest of Iran on the Karun River, immediately upstream of the Karun 3 Dam reservoir... 

This thesis presents a probabilistic framework for prioritizing the highway bridge network for seismic retrofitting and structural health monitoring. The basis of this framework is the risk analysis of the bridge network, which includes bridges and the links connecting them in the transportation network. Risk is defined as the probability of exceeding the sum of all losses incurred to the community in the event of a hazard. These losses include the direct economic cost of bridge repairs and damage to vehicles due to bridge failure, the socioeconomic cost of increased travel time for transportation network users, the indirect economic cost of excess fuel consumption and depreciation of... 

The purpose of this research is to monitor the health of structures using the updated finite element model, in which digital images are used to optimize the numerical model. Structural Health Monitoring (SHM) is always an important and significant issue that has attracted the attention of many researchers in recent years. In general, some researches have been conducted in this field using physical sensors that provide discrete data to the system for analysis. Using cameras to monitor the structure makes it possible to extract continuous and integrated data from the structure using digital images, which is a significant advantage compared to physical sensors.In this research, a steel... 

The purpose of the study: The purpose of this study is to identify the crack position in homogeneous plates through health monitoring methods based on vibration. Identifying structural damage is one of the issues that attention can prevent the sudden collapse of structures and causing heavy loss of life and property. For this reason, extensive studies have been conducted in this field in recent decades. In this study, plates are examined as one of the most used structural members, and their damage is identified through a proposed method based on wavelet transform. Research method: In this study, through the wavelet transform method, the dynamic responses of a homogeneous plate excited by a... 

The ultimate goal of this study is to evaluate the condition of concrete structures using computer vision methods and using powerful tools such as machine learning methods based on visual information. This assessment is performed by detecting damage in these structures. With the aging of structures such as dams, bridges and tall buildings, structural health monitoring is an important task in ensuring their safety and stability. Therefore, rapid assessment of the health of structures and diagnosis of damage after destructive events is of great value in terms of providing resilience of structures. Visual inspection of structures by experts is one of the basic methods of evaluating structures.... 

This study aims to identify the structural damage using deep learning. Damage to structures reduces their lifespan. Therefore, continuous monitoring of structures is necessary to detect any possible damages that occurred due to various causes. Structural health monitoring systems that use wired sensors to measure signals are costly and time-consuming to install. Whereas, wireless sensor-based damage detection systems are relatively cost-effective. However, one of the most important problems in using them is the loss or non-recording of some data, which severely affects the accuracy of a structural damage detection system. On the other hand, health monitoring using machine learning-based... 

The main goal of this research is detection, localization, and determining the severity of structural damages. The importance of this objective is to prevent abrupt destruction and severe human and financial losses. Damage detection is divided into local and global detection, and global detection contains static and vibration-based methods. In this research, the vibration-based method is used. Due to the complexity of this method, accurate and powerful tools are required for detecting effective features in damages; Deep Learning (DL), which is part of a broader family of machine learning methods based on artificial neural networks (ANN), could be used. Accordingly, in this project, the... 

With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,...