2004
DOI: 10.1016/s0888-3270(03)00040-2
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Identification of unusual events in multi-channel bridge monitoring data

Abstract: Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure such as bridges. However, converting large amounts of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of s… Show more

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Cited by 56 publications
(37 citation statements)
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“…In the study by Omenzetter et al (2004), hourly measurements of strain and internal pressure (i.e. stresses) were taken during and after construction of the Singapore-Malaysia Second Link Bridge, which was built using the balanced cantilever method over a two month period.…”
Section: Strain Methods That Detects Damage Using Signal Processingmentioning
confidence: 99%
“…In the study by Omenzetter et al (2004), hourly measurements of strain and internal pressure (i.e. stresses) were taken during and after construction of the Singapore-Malaysia Second Link Bridge, which was built using the balanced cantilever method over a two month period.…”
Section: Strain Methods That Detects Damage Using Signal Processingmentioning
confidence: 99%
“…Case studies on SHM [4][5][6][7], specially focused on damage identification and structural safety maintenance, for application on large infrastructures as well as on residential and commercial buildings, have become increasingly narrated in the literature. Examples of the decentralized systems and advances on the development of sensors are frequently introduced in the structural monitoring area [8][9][10].…”
Section: Importance Of Shm For Structural Safety Maintenancementioning
confidence: 99%
“…The first one [28] employs wavelet transform. Raw strain data are filtered into high and low frequency components using the Daubechies discrete wavelet transform [29].…”
Section: Tuas Second Link: Long Term Performance Monitoringmentioning
confidence: 99%