The Use of Vibration Data for Damage Detection in Bridges: A Comparison of System Identification
نویسندگان
چکیده
This paper briefly outlines the rationale for structural health monitoring as an integral component of bridge management systems. Two different approaches, system identification and statistical pattern recognition, are summarised and applied in turn to vibration data collected from three scale model-reinforced concrete bridges. The results show that the system identification paradigm can successfully locate and quantify the damage to the decks when they are loaded to incipient collapse, especially when experience is used to determine the parameters to use in the finite element updating procedure. However, the study also demonstrated that this approach requires a large amount of high quality data, requirements that cannot always be met readily in the field. In contrast, although the statistical pattern recognition approach was not able to quantify or locate the damage, it was able to clearly indicate that damage had occurred from relatively few measurements. A comparison of the strengths and weaknesses of the two approaches suggests that they should be used in a complementary manner. The statistical pattern recognition approach can be employed as a simple, cost efficient way to indicate that damage has occurred. It can then trigger a more detailed investigation using system identification.
منابع مشابه
Comparison Study on Neural Networks in Damage Detection of Steel Truss Bridge
This paper presents the application of three main Artificial Neural Networks (ANNs) in damage detection of steel bridges. This method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. The changes in structural response is used to identify the states of structural damage. To circumvent the difficulty arising from the non-linear n...
متن کاملReal-time damage detection of bridges using adaptive time-frequency analysis and ANN
Although traditional signal-based structural health monitoring algorithms have been successfully employed for small structures, their application for large and complex bridges has been challenging due to non-stationary signal characteristics with a high level of noise. In this paper, a promising damage detection algorithm is proposed by incorporation of adaptive signal processing and Artificial...
متن کاملCRACK DETECTION IN CONCRETE BEAM USING OPTIMIZATION METHOD
Structural damage detection is a field that has attracted a great interest in the scientific community in recent years. Most of these studies use dynamic analysis data of the beams as a diagnostic tool for damage. In this paper, a massless rotational spring was used to represent the cracked sections of beams and the natural frequencies and mode shape were obtained. For calculation of rotational...
متن کاملSubsea Free Span Pipeline Damage Detection Based on Wavelet Transform under Environmental Load
During their service life, marine pipelines continually accumulate damage as a result of the action of various environmental forces. Clearly, the development of robust techniques for early damage detection is very important to avoid the possible occurrence of a disastrous structural failure. Most of vibration-based damage detection methods require the modal properties that are obtained from mea...
متن کاملPerformance of Vibration-Based Damage Detection Methods in Bridges
The important advances achieved in the modal identification, sensors and structural monitoring of bridges have motivated the bridge engineering community to develop damage detection methods based on vibration monitoring. Some of these methods have already been demonstrated under certain conditions in bridges with deliberate damage (Farrar et al., 1998). However, the performance of these methods...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004