Damage assessment of a bridge based on mode shapes estimated by responses of passing vehicles

Oshima, Yoshinobu,Yamamoto, Kyosuke,Sugiura, Kunitomo Techno-Press 2014 Smart Structures and Systems, An International Jou Vol.13 No.5

In this study, an indirect approach is developed for assessing the state of a bridge on the basis of mode shapes estimated by the responses of passing vehicles. Two types of damages, i.e., immobilization of a support and decrease in beam stiffness at the center, are evaluated with varying degrees of road roughness and measurement noise. The assessment theory's feasibility is verified through numerical simulations of interactive vibration between a two-dimensional beam and passing vehicles modeled simply as sprung mass. It is determined that the damage state can be recognized by the estimated mode shapes when the beam incurs severe damage, such as immobilization of rotational support, and the responses contain no noise. However, the developed theory has low robustness against noise. Therefore, numerous measurements are needed for damage identification when the measurement is contaminated with noise.

Linear system parameter as an indicator for structural diagnosis of short span bridges

김철우,Ryo Isemoto,Kunitomo Sugiura,Mitsuo Kawatani 국제구조공학회 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

This paper intended to investigate the feasibility of bridge health monitoring using a linear system parameter of a time series model identified from traffic-induced vibrations of bridges through a laboratory moving vehicle experiment on scaled model bridges. This study considered the system parameter of the bridge-vehicle interactive system rather than modal ones because signals obtained under a moving vehicle are not the responses of the bridge itself but those of the interactive system. To overcome the shortcomings of modal parameter-based bridge diagnosis using a time series model, this study considered coefficients of Autoregressive model (AR coefficients) as an early indicator of anomaly of bridges. This study also investigated sensitivity of AR coefficients in detecting anomaly of bridges. Observations demonstrated effectiveness of using AR coefficients as an early indicator for anomaly of bridges.

Damage assessment of a bridge based on mode shapes estimated by responses of passing vehicles

Yoshinobu Oshima,Kyosuke Yamamoto,Kunitomo Sugiura 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.13 No.5

In this study, an indirect approach is developed for assessing the state of a bridge on the basis of mode shapes estimated by the responses of passing vehicles. Two types of damages, i.e., immobilization of a support and decrease in beam stiffness at the center, are evaluated with varying degrees of road roughness and measurement noise. The assessment theory\'s feasibility is verified through numerical simulations of interactive vibration between a two-dimensional beam and passing vehicles modeled simply as sprung mass. It is determined that the damage state can be recognized by the estimated mode shapes when the beam incurs severe damage, such as immobilization of rotational support, and the responses contain no noise. However, the developed theory has low robustness against noise. Therefore, numerous measurements are needed for damage identification when the measurement is contaminated with noise.

A Bayesian approach for vibration-based long-term bridge monitoring to consider environmental and operational changes

Kim, Chul-Woo,Morita, Tomoaki,Oshima, Yoshinobu,Sugiura, Kunitomo Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.2

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

A Bayesian approach for vibration-based long-term bridge monitoring to consider environmental and operational changes

Chul-Woo Kim,Tomoaki Morita,Yoshinobu Oshima,Kunitomo Sugiura 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.2

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

Polymer concrete filled circular steel beams subjected to pure bending

Eiichi Watanabe,Walter O. Oyawa,Kunitomo Sugiura 국제구조공학회 2004 Steel and Composite Structures, An International J Vol.4 No.4

In view of the mounting cost of rehabilitating deteriorating infrastructure, further compounded by intensified environmental concerns, it is now obvious that the evolvement and application of advanced composite structural materials to complement conventional construction materials is a necessity for sustainable construction. This study seeks alternative fill materials (polymer-based) to the much-limited cement concrete used in concrete-filled steel tubular structures. Polymers have been successfully used in other industries and are known to be much lighter, possess high tensile strength, durable and resistant to aggressive environments. Findings of this study relating to elasto-plastic characteristics of polymer concrete filled steel composite beams subjected to uniform bending highlight the enormous increase in stiffness, strength and ductility of the composite beams, over the empty steel tube. Moreover, polymer based materials were noted to present a wide array of properties that could be tailored to meet specific design requirements e.g., ductility based design or strength based design. Analytical formulations for design are also considered.

Linear system parameter as an indicator for structural diagnosis of short span bridges

Kim, Chul-Woo,Isemoto, Ryo,Sugiura, Kunitomo,Kawatani, Mitsuo Techno-Press 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

This paper intended to investigate the feasibility of bridge health monitoring using a linear system parameter of a time series model identified from traffic-induced vibrations of bridges through a laboratory moving vehicle experiment on scaled model bridges. This study considered the system parameter of the bridge-vehicle interactive system rather than modal ones because signals obtained under a moving vehicle are not the responses of the bridge itself but those of the interactive system. To overcome the shortcomings of modal parameter-based bridge diagnosis using a time series model, this study considered coefficients of Autoregressive model (AR coefficients) as an early indicator of anomaly of bridges. This study also investigated sensitivity of AR coefficients in detecting anomaly of bridges. Observations demonstrated effectiveness of using AR coefficients as an early indicator for anomaly of bridges.