• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.1-9
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• 2016

Railroad bridges account for 25% of the entire high-speed rail network. Railway bridges are subject to gradual structural degradation or fatigue accumulation due to consistent and repeating excitation by fast moving trains. Wireless sensing technology has opened up a new avenue for bridge health monitoring owing to its low-cost, high fidelity, and multiple sensing capability. On the other hand, measuring the transient response during train passage is quite challenging that the current wireless sensor system cannot be applied due to the intrinsic time delay of the sensor network. Therefore, this paper presents a framework for monitoring such transient responses with wireless sensing systems using 1) real-time excessive vibration monitoring through ultra-low-power MEMS accelerometers, and 2) post-event time synchronization scheme. The ultra-low power accelerometer continuously monitors the vibration and trigger network when excessive vibrations are detected. The entire network of wireless smart sensors starts sensing through triggering and the post-event time synchronization is conducted to compensate for the time error on the measured responses. The results of this study highlight the potential of detecting the impact load and triggering the entire network, as well as the effectiveness of the post-event time synchronized scheme for compensating for the time error. A numerical and experimental study was carried out to validate the proposed sensing hardware and time synchronization method.

• Journal of the Korean Society for Railway
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• v.16 no.6
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• pp.466-472
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• 2013

The use of a concrete track is gradually growing in urban and high-speed railways in many part of the world. The resilient pad, which is essentially when concrete tracks are used, plays the important role of relieving the impact caused by train loads. The simple fatigue test[1] to estimate the variable stiffness of resilient pads is usually performed, but it differs depending on the practical conditions of different railways. In this study, the static stiffness levels of used resilient pads according to passing tonnages levels were measured in laboratory tests. Also, the simple fatigue test and the multi-stress accelerated degradation test for new resilient pads were performed in a laboratory. The static stiffness of the used pad was compared with the results of tests of usage times and cycles. The results of the comparison showed that the variable static stiffness levels of the used pad were similar to results of the multi-stress accelerated degradation test considering the fatigue and heat load. With a T-NT equation related to the degree of the multi-stress accelerated degradation, a model of multi-stress accelerated degradation for a resilient pad was devised. It was found through this effort that the total acceleration factor was approximately 2.62. Finally, this study proposes an equation for a multi-stress accelerated degradation model for polyurethane resilient pads.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.125-135
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• 2015

The tendency of more longer span length being required economical in railway bridges is studying about PSC I shaped girder. In this case, it is important to analyze and choose the effective girder section for stiffness of bridge. This study investigates the dynamic properties and safety of PSC I shaped girder being used wide upper flange whose selection based on radii and efficiency factor of flexure for railway bridge in different span type. In addition, 40m PSC Box girder bridge adopted in Honam high speed railway is further analyzed to compare dynamic performance of PSC I shaped girder railway bridge with same span length. Time history response is acquired based on the mode superposition method. Static analysis is also analyzed using standard train load combined with the impact factor. Consequently, the result met limit values in every case including vertical displacement, acceleration and distort.