Structural damage diagnosis of steel truss bridges by outlier detection

This study discusses structural damage diagnosis of real steel truss bridges by measuring trafficinduced vibration of bridges and utilizing a damage indicator derived from linear system parameters of a time series model. On-site damage experiments were carried out on real steel truss bridges. Artificial damage was applied to the bridge by severing a truss member with a cutting machine.Vehicle-induced vibrations of the bridges before and after applying damagewere measured and used in structural damage diagnosis of the bridges. Changes in the damage indicator are detected by Mahalanobis-Taguchi system (MTS) which is one of multivariate outlier analyses. The damage indicator and outlier detection was successfully applied to detect anomalies in the steel truss bridges utilizing vehicle-induced vibrations. Observations through this study demonstrate feasibility of the proposed approach for real world applications.

A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle

Previous research based on theoretical simulations has shown the potential of the wavelet transform to detect damage in a beam by analysing the time-deflection response due to a constant moving load. However, its application to identify damage from the response of a bridge to a vehicle raises a number of questions. Firstly, it may be difficult to record the difference in the deflection signal between a healthy and a slightly damaged structure to the required level of accuracy and high scanning frequencies in the field. Secondly, the bridge is going to have a road profile and it will be loaded by a sprung vehicle and time-varying forces rather than a constant load. Therefore, an algorithm based on a plot of wavelet coefficients versus time to detect damage (a singularity in the plot) appears to be very sensitive to noise. This paper addresses these questions by: (a) using the acceleration signal, instead of the deflection signal, (b) employing a vehicle-bridge finite element interaction model, and (c) developing a novel wavelet-based approach using wavelet energy content at each bridge section which proves to be more sensitive to damage than a wavelet coefficient line plot at a given scale as employed by others.

The use of an instrumented vehicle in a wavelet based damage detection approach for bridge structures

Periodic monitoring of structures such as bridges is necessary as their condition can deteriorate due to environmental conditions and ageing, causing the bridge to become unsafe. This monitoring - so called Structural Health Monitoring (SHM) - can give an early warning if a bridge becomes unsafe. This paper investigates an alternative wavelet-based approach for the monitoring of bridge structures which consists of the use of a vehicle fitted with accelerometers on its axles. A simplified vehicle-bridge interaction model is used in theoretical simulations to examine the effectiveness of the approach in detecting damage in the bridge. The accelerations of the vehicle are processed using a continuous wavelet transform, allowing a time-frequency analysis to be performed. This enables the identification of both the existence and location of damage from the vehicle response. Based on this analysis, a damage index is established. A parametric study is carried out to investigate the effect of parameters such as the bridge span length, vehicle speed, vehicle mass, damage level, signal noise level and road surface roughness on the accuracy of results. In addition, a laboratory experiment is carried out to validate the results of the theoretical analysis and assess the ability of the approach to detect changes in the bridge response.

Seismic damage detection for a steel braced frame structure

A new approach for global detection of seismic damage in a single-storey steel concentrically braced frame (CBF) structure is presented. The filtered lateral in-plane acceleration response of the CBF structure is integrated twice to provide the lateral in-plane displacement which is used to infer buckling and yielding damage. The level of interstorey drift of the CBF during a seismic excitation allows the yield and buckling of the bracing members to be identified and indirectly detects damage based on exceedance of calculated lateral in-plane displacement limits. A band-pass filter removes noise from the acceleration signal followed by baseline correction being used to reduce the drift in velocity and displacement during numerical integration. This pre-processing results in reliable numerical integration of the frame acceleration that predicts the displacement response accurately when compared to the measured lateral displacement of the CBF structure. Importantly, the structural damage is not assumed through removal of bracing members, rather damage is induced through actual seismic loading. The buckling and yielding displacement threshold limits used to identify damage are demonstrated to accurately identify the initiation of buckling and yielding.

A field experiment on a steel Gerber-truss bridge for damage detection utilizing vehicle-induced vibrations

A field experiment was conducted on a real continuous steel Gerber-truss bridge with artificial damage applied. This article summarizes the results of the experiment for bridge damage detection utilizing traffic-induced vibrations. It investigates the sensitivities of a number of quantities to bridge damage including the identified modal parameters and their statistical patterns, Nair’s damage indicator and its statistical pattern and different sets of measurement points. The modal parameters are identified by autoregressive time-series models. The decision on bridge health condition is made and the sensitivity of variables is evaluated with the aid of the Mahalanobis–Taguchi system, a multivariate pattern recognition tool. Several observations are made as follows. For the modal parameters, although bridge damage detection can be achieved by performing Mahalanobis–Taguchi system on certain modal parameters of certain sets of measurement points, difficulties were faced in subjective selection of meaningful bridge modes and low sensitivity of the statistical pattern of the modal parameters to damage. For Nair’s damage indicator, bridge damage detection could be achieved by performing Mahalanobis–Taguchi system on Nair’s damage indicators of most sets of measurement points. As a damage indicator, Nair’s damage indicator was superior to the modal parameters. Three main advantages were observed: it does not require any subjective decision in calculating Nair’s damage indicator, thus potential human errors can be prevented and an automatic detection task can be achieved; its statistical pattern has high sensitivity to damage and, finally, it is flexible regarding the choice of sets of measurement points.

Wavelet Based Damage Detection Approach for Bridge Structures Utilising Vehicle Vibration

This paper investigates a wavelet-based damage detection approach for bridge structures. By analysing the continuous wavelet transform of the vehicle response, the approach aims to identify changes in the bridge response which may indicate the existence of damage. A numerical vehicle-bridge interaction model is used in simulations as part of a sensitivity study. Furthermore, a laboratory experiment is carried out to investigate the effects of varying vehicle configuration, speed and bridge damping on the ability of the vehicle to detect changes in the bridge response. The accelerations of the vehicle and bridge are processed using a continuous wavelet transform, allowing time-frequency analysis to be carried out on the responses of the laboratory vehicle-bridge interaction system. Results indicate the most favourable conditions for successful implementation of the approach.

Fetal brain function in response to maternal alcohol consumption: Early evidence of damage

Background: Studies of the adverse neurobehavioral effects of maternal alcohol consumption on the fetus have been largely confined to the postnatal period, after exposure to alcohol has finished. This study explored the brain function of the fetus, at the time of exposure to alcohol, to examine its effect on information processing and stability of performance. Methods: Five groups of fetuses, defined by maternal alcohol consumption patterns, were examined: control (no alcohol); moderate (5 to 10 units/wk either drunk evenly across the week or as a binge, in 2 to 3 days); heavy (20+ units/wk drunk evenly or as a binge). Fetal habituation performance was examined on 3 occasions, separated by 7 days, beginning at 35 weeks of gestation. The number of trials required to habituate on each test session and the difference in performance across test sessions were recorded. Results: Fetuses exposed to heavy binge drinking required significantly more trials to habituate and exhibited a greater variability in performance across all test sessions than the other groups. Maternal drinking, either heavily but evenly or moderately as a binge, resulted in poorer habituation, and moderate binge drinking resulted in greater variability compared with no, or even, drinking. Conclusions: Decreased information processing, reflected by poorer habituation, and increased variability in performance may reflect the initial manifestations of structural damage caused by alcohol to the brain. These results will lead to a greater understanding of the effects of alcohol on the fetus's brain, enable the antenatal identification of fetal alcohol spectrum disorders, and lead to the early implementation of better management strategies. © 2012 by the Research Society on Alcoholism.


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A bridge-monitoring tool based on bridge and vehicle accelerations

Previous research on damage detection based on the response of a structure to a moving load has reported decay in accuracy with increasing load speed. Using a 3D vehicle – bridge interaction model, this paper shows that the area under the filtered acceleration response of the bridge increases with increasing damage, even at highway load speeds. Once a datum reading is established, the area under subsequent readings can be monitored and compared with the baseline reading, if an increase is observed it may indicate the presence of damage. The sensitivity of the proposed approach to road roughness and noise is tested in several damage scenarios. The possibility of identifying damage in the bridge by analysing the acceleration response of the vehicle traversing it is also investigated. While vehicle acceleration is shown to be more sensitive to road roughness and noise and therefore less reliable than direct bridge measurements, damage is successfully identified in favourable scenarios.

Experimental Autoimmune Uveoretinitis (EAU)-Related Tissue Damage and Angiogenesis Is Reduced in CCL2−/−CX3CR1gfp/gfp Mice

Purpose: To investigate the roles of the CCL2-CCR2 and CX3CL1-CX3CR1 pathways in experimental autoimmune uveoretinitis (EAU)-mediated retinal tissue damage and angiogenesis.

Methods: The C57BL/6J wild-type (WT) and CCL2−/−CX3CR1gfp/gfp (double knockout [DKO]) mice were immunized with IRBP1-20. Retinal inflammation and tissue damage were evaluated clinically and histologically at different days postimmunization (p.i.). Retinal neovascular membranes were evaluated by confocal microscopy of retinal flat mounts, and immune cell infiltration by flow cytometry.

Results: At day 25 p.i., DKO mice had lower clinical and histological scores and fewer CD45highCD11b+ infiltrating cells compared with WT mice. The F4/80+macrophages constitute 40% and 21% and CD11b+Gr-1+Ly6G+ neutrophils constitute 10% and 22% of retinal infiltrating cells in WT and DKO mice, respectively. At the late stages of EAU (day 60–90 p.i.), DKO and WT mice had similar levels of inflammatory score. However, less structural damage and reduced angiogenesis were detected in DKO mice. Neutrophils were rarely detected in the inflamed retina in both WT and DKO mice. Macrophages and myeloid-derived suppressor cells (MDSCs) accounted for 8% and 3% in DKO EAU retina, and 19% and 10% in WT EAU retina; 71% of infiltrating cells were T/B-lymphocytes in DKO EAU retina and 50% in WT EAU retina.

Conclusions: Experimental autoimmune uveoretinitis–mediated retinal tissue damage and angiogenesis is reduced in CCL2−/−CX3CR1gfp/gfp mice. Retinal inflammation is dominated by neutrophils at the acute stage and lymphocytes at the chronic stage in these mice. Our results suggest that CCR2+ and CX3CR1+monocytes are both involved in tissue damage and angiogenesis in EAU.

Design of Scaled Bridge Prototype for Energy Harvesting Testing

Energy harvesting from ambient vibration is a promising field, especially for applications in larger infrastructures such as bridges. These structures are more frequently monitored for damage detection because of their extended life, increased traffic load and environmental deterioration. In this regard, the possibility of sourcing the power necessary for the sensors from devices embedded in the structure, thus cutting the cost due to the management of battery replacing over the lifespan of the structure, is particularly attracting. Among others, piezoelectric devices have proven to be especially effective and easy to apply since they can be bonded to existing host structure. For these devices the energy harvesting capacity is achieved directly from the variation in the strain conditions from the surface of the structure. However these systems need to undergo significant research for optimisation of their harvesting capacity and for assessing the feasibility of application to various ranges of bridge span and load. In this regard scaled bridge prototypes can be effectively used not only to assess numerical models and studies in an inexpensive and repeatable way but also to test the electronic devices under realistic field conditions. In this paper the theory of physical similitude is applied to the design of bridge beams with embedded energy harvesting systems and health monitoring sensors. It will show both how bridge beams can be scaled in such a way to apply and test energy harvesting systems and 2) how experimental data from existing bridges can be applied to prototypes in a laboratory environment. The study will be used for assessing the reliability of the system over a train bridge case study undergoing a set load cycles and induced localised damage.

Development of a Vehicle-Bridge-Soil Dynamic Interaction Model for Scour Damage Modelling

Damage detection in bridges using vibration-based methods is an area of growing research interest. Improved assessment
methodologies combined with state-of-the-art sensor technology are rapidly making these approaches applicable for real-world
structures. Applying these techniques to the detection and monitoring of scour around bridge foundations has remained
challenging; however this area has gained attraction in recent years. Several authors have investigated a range of methods but
there is still significant work required to achieve a rounded and widely applicable methodology to detect and monitor scour.This
paper presents a novel Vehicle-Bridge-Soil Dynamic Interaction (VBSDI) model which can be used to simulate the effect of scour
on an integral bridge. The model outputs dynamic signals which can be analysed to determine modal parameters and the variation
of these parameters with respect to scour can be examined.The key novelty of this model is that it is the first numerical model for
simulating scour that combines a realistic vehicle loadingmodel with a robust foundation soil responsemodel.This paper provides a
description of the model development and explains the mathematical theory underlying themodel. Finally a case study application
of the model using typical bridge, soil, and vehicle properties is provided.

Extracting bridge frequencies from dynamic responses of two passing vehicles

A conventional way to identify bridge frequencies is utilizing vibration data measured directly from the bridge. A drawback with this approach is that the deployment and maintenance of the vibration sensors are generally costly and time-consuming. One of the solutions is in a drive-by approach utilizing vehicle vibrations while the vehicle passes over the bridge. In this approach, however, the vehicle vibration includes the effect of road surface roughness, which makes it difficult to extract the bridge modal properties. This study aims to examine subtracting signals of two trailers towed by a vehicle to reduce the effect of road surface roughness. A simplified vehicle-bridge interaction model is used in the numerical simulation; the vehicle - trailer and bridge system are modeled as a coupled model. In addition, a laboratory experiment is carried out to verify results of the simulation and examine feasibility of the damage detection by the drive-by method.