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Based on Multiple Parameters Research on Damage Identification of Pre-damaged Reinforced Concrete Beam

Wiqas Ahmad  
【摘要】:Highway bridges are the most vulnerable engineering structures that are deteriorating continuously in rate comparatively much higher than estimated due to uncertainty in mechanical loadings and unfriendly environmental conditions such as temperature fluctuation,climate changing,hurricanes,floods,strong winds and earth quakes.The number of highway bridges is increasing with the rapid development and spreading of transportation networks.So,bridge damage detection is being vital important in order to secure structural integrity and operational safety of the bridge prior to costly repair or even catastrophic collapse.In these damage detection methods,multiple parameters based damage detection is a reliable and effective non-destructive damage identification technique that received remarkable attention from the scientific and engineering communities for evaluation and assessment of bridge structures.These parameters are natural frequency,mode shape and damping that can express the vibration behaviour of a structure.Nowadays,these multiple parameters to utilise by researchers for damage detection problems and to be applied on real structures pose some limitations on the basic level of research.This research thesis provides prominent multiple parameters of vibration based methods for damage detection using shift in natural frequency,changes in mode shape and damping that compensate the limitations and inadequacies of these multiple parameters for damage detection.The research work is approached both by numerical and experimental investigations and the results are further improved using the theory of modal curvature.In the past decades,a significant amount of research has been conducted based on shift in natural frequency as damage diagnostic tool.It is known that the natural frequency can be easily obtained from vibration response with only few measurement points.Because natural frequency is a fundamental property of a structure which is directly related to stiffness of material,so whenever damage induces in a structure,stiffness is decreased which leads to gradual reduction in natural frequency.Obviously,there is relationship between structural damage and changes in natural frequency which can be used to detect damage effectively.It should be noted that the sensitivity of natural frequency shifts to detect damage is too low that requires either very precise measurements or large levels of damage.Also,shift in natural frequency doesn't hold any information about location of damage and therefore damage can't be located measuring shift in natural frequency only.Mode shape based damage detection is quite obvious method used by many researchers to overcome the limitations of natural frequency.A mode shape depicts the estimated curvature of a structure vibrating at a given mode corresponds to a specific natural frequency.Mode shape contains local information which makes it more sensitive to local damages and can be used to detect the damage and its location.However,measurement of mode shape requires a series of sensors to install that should be very costly and size of the damage can't be measured accurately.Modal Curvature is the second derivative of mode shape and an alternative to use for mode shape to obtain spatial information about damage for structures exhibiting bending behaviour.The derivative process has the effect of amplifying any discontinuities in the mode shape caused by the damage.The changes in the curvature mode shape increase with increasing size of damage.This information can be used to obtain the amount of damage in the structure.Theory of modal curvature is adopted on numerical reinforced concrete beam having various damage scenarios simulated with finite element method using ANSYS(Analysis System)computer simulation software in order to compensate the limitations of shift in natural frequency and changes in mode shape.Consequently,modal curvature of mode shape can be used to accurately detect the damage and predict the size of the damage.


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