Structural health monitoring of continuous prestressed concrete bridges using ambient thermal responses

2012 ◽  
Vol 40 ◽  
pp. 20-38 ◽  
Author(s):  
Nonthachart Kulprapha ◽  
Pennung Warnitchai
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Prestressed Concrete ◽  
Concrete Bridges ◽  
Prestressed Concrete Bridges ◽  
Structural Health

An Improved Design Based on Smart Film for Monitoring Crack Width of Concrete Bridges

2011 ◽  
Vol 308-310 ◽  
pp. 2478-2481
Author(s):  
Xing Xing Li ◽  
Ben Niu Zhang ◽  
Zhi Xiang Zhou ◽  
Lian Tang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Crack Width ◽  
Large Scale ◽  
Concrete Bridges ◽  
Challenging Problem ◽  
Structural Health ◽  
Crack Monitoring ◽  
Improved Design

Structural health monitoring is a promising way for evaluating the integrity and safety of large-scale bridges, and crack monitoring is thought to be a challenging problem in this field. An improved design based on smart film for monitoring crack width of concrete bridges is proposed in this paper. Experiments are also implemented to verify the effectiveness of this design.

A Simplified Methodology for Condition Assessment of Bridge Bearings Using Vibration Based Structural Health Monitoring Techniques

2021 ◽  
pp. 2150133
Author(s):  
Babar Nasim Khan Raja ◽  
Saeed Miramini ◽  
Colin Duffield ◽  
Shilun Chen ◽  
Lihai Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Condition ◽  
Condition Assessment ◽  
Concrete Bridges ◽  
Traffic Loading ◽  
Structural Health ◽  
Vibration Data ◽  
Bridge Bearing ◽  
Bridge Bearings

The mechanical properties of bridge bearings gradually deteriorate over time resulting from daily traffic loading and harsh environmental conditions. However, structural health monitoring of in-service bridge bearings is rather challenging. This study presents a bridge bearing condition assessment framework which integrates the vibration data from a non-contact interferometric radar (i.e. IBIS-S) and a simplified analytical model. Using two existing concrete bridges in Australia as a case study, it demonstrates that the developed framework has the capability of detecting the structural condition of the bridge bearings in real-time. In addition, the results from a series of parametric studies show that the effectiveness of the developed framework is largely determined by the stiffness ratio between bridge bearing and girder ([Formula: see text], i.e. the structural condition of the bearings can only be effectively captured when the value of [Formula: see text] ranges from 1/100 and 100.

scholarly journals Structural Health Monitoring Based on Acoustic Emissions: Validation on a Prestressed Concrete Bridge Tested to Failure

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7272
Author(s):  
Daniel Tonelli ◽  
Michele Luchetta ◽  
Francesco Rossi ◽  
Placido Migliorino ◽  
Daniele Zonta
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Prestressed Concrete ◽  
Acoustic Emissions ◽  
Maximum Load ◽  
Peak Frequency ◽  
Load Test ◽  
Concrete Bridge ◽  
Structural Health ◽  
Prestressed Concrete Bridge

The increasing number of bridges approaching their design life has prompted researchers and operators to develop innovative structural health monitoring (SHM) techniques. An acoustic emissions (AE) method is a passive SHM approach based on the detection of elastic waves in structural components generated by damages, such as the initiation and propagation of cracks in concrete and the failure of steel wires. In this paper, we discuss the effectiveness of AE techniques by analyzing records acquired during a load test on a full-size prestressed concrete bridge span. The bridge is a 1968 structure currently decommissioned but perfectly representative, by type, age, and deterioration state of similar bridges in operation on the Italian highway network. It underwent a sequence of loading and unloading cycles with a progressively increasing load up to failure. We analyzed the AE signals recorded during the load test and examined how far their features (number of hits, amplitude, signal strength, and peak frequency) allow us to detect, quantify, and classify damages. We conclude that AE can be successfully used in permanent monitoring to provide information on the cracking state and the maximum load withstood. They can also be used as a non-destructive technique to recognize whether a structural member is cracked. Finally, we noticed that AE allow classifying different types of damage, although further experiments are needed to establish and validate a robust classification procedure.

Introduction to the use of wavelet multiresolution analysis for intelligent structural health monitoring

2004 ◽  
Vol 31 (5) ◽  
pp. 719-731 ◽  
Author(s):  
M.M Reda Taha ◽  
A Noureldin ◽  
A Osman ◽  
N El-Sheimy
Keyword(s):  
Neural Networks ◽  
Signal Processing ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Multiresolution Analysis ◽  
Prestressed Concrete ◽  
Digital Signal ◽  
Detection Algorithm ◽  
Structural Health ◽  
Wavelet Multiresolution Analysis

This paper suggests the use of wavelet multiresolution analysis (WMRA) as a reliable tool for digital signal processing in structural health monitoring (SHM) systems. A damage occurrence detection algorithm using WMRA augmented with artificial neural networks (ANN) is described. The suggested algorithm allows intelligent monitoring of structures in real time. The probability of damage occurrence is determined by evaluating the wavelet norm index (WNI) representing the energy of a signal describing the change in the system dynamics due to damage. An example application of the proposed algorithm is presented using a finite element simulated structural dynamics of a prestressed concrete bridge. The new algorithm showed very promising results.Key words: structural health monitoring, neural networks, wavelet analysis, signal processing, damage detection.

scholarly journals Yonjung High-Speed Railway Bridge Assessment Using Output-Only Structural Health Monitoring Measurements under Train Speed Changing

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Mosbeh R. Kaloop ◽  
Jong Wan Hu ◽  
Mohamed A. Sayed
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Prestressed Concrete ◽  
High Speed ◽  
Model Identification ◽  
Steel Girders ◽  
Structural Health ◽  
High Speed Trains ◽  
Output Only ◽  
Bridge Assessment

Yonjung Bridge is a hybrid multispan bridge that is designed to transport high-speed trains (HEMU-430X) with maximum operating speed of 430 km/h. The bridge consists of simply supported prestressed concrete (PSC) and composite steel girders to carry double railway tracks. The structural health monitoring system (SHM) is designed and installed to investigate and assess the performance of the bridge in terms of acceleration and deformation measurements under different speeds of the passing train. The SHM measurements are investigated in both time and frequency domains; in addition, several identification models are examined to assess the performance of the bridge. The drawn conclusions show that the maximum deflection and acceleration of the bridge are within the design limits that are specified by the Korean and European codes. The parameters evaluation of the model identification depicts the quasistatic and dynamic deformations of PSC and steel girders to be different and less correlated when higher speeds of the passing trains are considered. Finally, the variation of the frequency content of the dynamic deformations of the girders is negligible when high speeds are considered.

Sign in / Sign up

Export Citation Format

Share Document