Research and applications in bridge health monitoring

2014 ◽  
pp. 550-550
Author(s):  
F Catbas ◽  
J Casas ◽  
H Furuta ◽  
D Frangopol
Keyword(s):  
Health Monitoring ◽  
Bridge Health Monitoring

scholarly journals Numerical Parametric Study on the Effectiveness of the Contact-Point Response of a Stationary Vehicle for Bridge Health Monitoring

2021 ◽  
Vol 11 (15) ◽  
pp. 7028
Author(s):  
Ibrahim Hashlamon ◽  
Ehsan Nikbakht ◽  
Ameen Topa ◽  
Ahmed Elhattab
Keyword(s):  
Numerical Model ◽  
Health Monitoring ◽  
Contact Point ◽  
Response Spectra ◽  
Roughness Effects ◽  
Moving Vehicle ◽  
Bridge Health Monitoring ◽  
Vehicle Response ◽  
Instrumented Vehicle ◽  
The Time Domain

Indirect bridge health monitoring is conducted by running an instrumented vehicle over a bridge, where the vehicle serves as a source of excitation and as a signal receiver; however, it is also important to investigate the response of the instrumented vehicle while it is in a stationary position while the bridge is excited by other source of excitation. In this paper, a numerical model of a stationary vehicle parked on a bridge excited by another moving vehicle is developed. Both stationary and moving vehicles are modeled as spring–mass single-degree-of-freedom systems. The bridges are simply supported and are modeled as 1D beam elements. It is known that the stationary vehicle response is different from the true bridge response at the same location. This paper investigates the effectiveness of contact-point response in reflecting the true response of the bridge. The stationary vehicle response is obtained from the numerical model, and its contact-point response is calculated by MATLAB. The contact-point response of the stationary vehicle is investigated under various conditions. These conditions include different vehicle frequencies, damped and undamped conditions, different locations of the stationary vehicle, road roughness effects, different moving vehicle speeds and masses, and a longer span for the bridge. In the time domain, the discrepancy of the stationary vehicle response with the true bridge response is clear, while the contact-point response agrees well with the true bridge response. The contact-point response could detect the first, second, and third modes of frequency clearly, unlike the stationary vehicle response spectra.

scholarly journals Challenges in Bridge Health Monitoring: A Review

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4336
Author(s):  
Piervincenzo Rizzo ◽  
Alireza Enshaeian
Keyword(s):  
United States ◽  
Health Monitoring ◽  
Highway Bridges ◽  
The United States ◽  
Anomalous Behavior ◽  
Existing Structures ◽  
Bridge Health Monitoring ◽  
Using Data ◽  
The Many ◽  
Major Factors

Bridge health monitoring is increasingly relevant for the maintenance of existing structures or new structures with innovative concepts that require validation of design predictions. In the United States there are more than 600,000 highway bridges. Nearly half of them (46.4%) are rated as fair while about 1 out of 13 (7.6%) is rated in poor condition. As such, the United States is one of those countries in which bridge health monitoring systems are installed in order to complement conventional periodic nondestructive inspections. This paper reviews the challenges associated with bridge health monitoring related to the detection of specific bridge characteristics that may be indicators of anomalous behavior. The methods used to detect loss of stiffness, time-dependent and temperature-dependent deformations, fatigue, corrosion, and scour are discussed. Owing to the extent of the existing scientific literature, this review focuses on systems installed in U.S. bridges over the last 20 years. These are all major factors that contribute to long-term degradation of bridges. Issues related to wireless sensor drifts are discussed as well. The scope of the paper is to help newcomers, practitioners, and researchers at navigating the many methodologies that have been proposed and developed in order to identify damage using data collected from sensors installed in real structures.

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