In recent years,Structural Health Monitoring (SHM) has emerged as a new research area in civil engineering.Most existing health monitoring methodologies require direct measurement of input excitation for implementatio...In recent years,Structural Health Monitoring (SHM) has emerged as a new research area in civil engineering.Most existing health monitoring methodologies require direct measurement of input excitation for implementation.However,in many cases,there is no easy way to measure these inputs-or alternatively to externally excite the structure.Therefore,SHM methods based on ambient vibration have become important in civil engineering.In this paper,an approach is proposed based on the Damage Location Vector (DLV) method to handle the ambient vibration case.Here,this flexibility-matrix-based damage localization method is combined with a modal expansion technique to eliminate the need to measure the input excitation.As a by-product of this approach,in addition to determining the location of the damage,an estimate of the damage extent also can be determined.Finally,a numerical example analyzing a truss structure with limited sensors and noisy measurement is provided to verify the efficacy of the proposed approach.展开更多
Due to their intrinsically nonlinear characteristics,development of control strategies that are implementable and can fully utilize the capabilities of semiactive control devices is an important and challenging task.I...Due to their intrinsically nonlinear characteristics,development of control strategies that are implementable and can fully utilize the capabilities of semiactive control devices is an important and challenging task.In this study,two control strategies are proposed for protecting buildings against dynamic hazards,such as severe earthquakes and strong winds,using one of the most promising semiactive control devices,the magnetorheological (MR) damper.The first control strategy is implemented by introducing an inverse neural network (NN) model of the MR damper.These NN models provide direct estimation of the voltage that is required to produce a target control force calculated from some optimal control algorithms.The major objective of this research is to provide an effective means for implementation of the MR damper with existing control algorithms.The second control strategy involves the design of a fuzzy controller and an adaptation law.The control objective is to minimize the difference between some desirable responses and the response of the combined system by adaptively adjusting the MR damper.The use of the adaptation law eliminates the need to acquire characteristics of the combined system in advance. Because the control strategy based on the combination of the fuzzy controller and the adaptation law doesn't require a prior knowledge of the combined building-damper system,this approach provides a robust control strategy that can be used to protect nonlinear or uncertain structures subjected to random loads.展开更多
文摘In recent years,Structural Health Monitoring (SHM) has emerged as a new research area in civil engineering.Most existing health monitoring methodologies require direct measurement of input excitation for implementation.However,in many cases,there is no easy way to measure these inputs-or alternatively to externally excite the structure.Therefore,SHM methods based on ambient vibration have become important in civil engineering.In this paper,an approach is proposed based on the Damage Location Vector (DLV) method to handle the ambient vibration case.Here,this flexibility-matrix-based damage localization method is combined with a modal expansion technique to eliminate the need to measure the input excitation.As a by-product of this approach,in addition to determining the location of the damage,an estimate of the damage extent also can be determined.Finally,a numerical example analyzing a truss structure with limited sensors and noisy measurement is provided to verify the efficacy of the proposed approach.
基金Hong Kong Research Grant Council Competitive Earmarked Research Grant HKUST 6218/99Ethe National Science Foundation under grant CMS 99-00234.
文摘Due to their intrinsically nonlinear characteristics,development of control strategies that are implementable and can fully utilize the capabilities of semiactive control devices is an important and challenging task.In this study,two control strategies are proposed for protecting buildings against dynamic hazards,such as severe earthquakes and strong winds,using one of the most promising semiactive control devices,the magnetorheological (MR) damper.The first control strategy is implemented by introducing an inverse neural network (NN) model of the MR damper.These NN models provide direct estimation of the voltage that is required to produce a target control force calculated from some optimal control algorithms.The major objective of this research is to provide an effective means for implementation of the MR damper with existing control algorithms.The second control strategy involves the design of a fuzzy controller and an adaptation law.The control objective is to minimize the difference between some desirable responses and the response of the combined system by adaptively adjusting the MR damper.The use of the adaptation law eliminates the need to acquire characteristics of the combined system in advance. Because the control strategy based on the combination of the fuzzy controller and the adaptation law doesn't require a prior knowledge of the combined building-damper system,this approach provides a robust control strategy that can be used to protect nonlinear or uncertain structures subjected to random loads.