Implication of bridge resilience design and lessons from negative examples

Wang, Erqiang; Liu, Zhao; Li, Meishuai; Zhao, Deyu

doi:10.1186/s43251-022-00077-8

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Recently, there have been several major bridge collapses around the world, including the Morandi Bridge failure in Genoa in 2018 [8] and the Nanfang'ao Bridge collapse in Yilan County in Taiwan in 2019, among others [9]. These incidents show the potential dangers when critical structural damage goes undetected.…”

Section: Brief Background Of Railway Bridges and Importance Of Struct...mentioning

confidence: 99%

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

Armijo,

Zamora-Sánchez

2024

Sensors

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Structural health monitoring (SHM) is critical for ensuring the safety of infrastructure such as bridges. This article presents a digital twin solution for the SHM of railway bridges using low-cost wireless accelerometers and machine learning (ML). The system architecture combines on-premises edge computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, the accelerometers stream raw vibration data, which are processed in the frequency domain and analyzed using machine learning to detect anomalies that indicate potential structural issues. The digital twin approach is demonstrated on an in-service railway bridge for which vibration data were collected over two years under normal operating conditions. By learning allowable ranges for vibration patterns, the digital twin model identifies abnormal spectral peaks that indicate potential changes in structural integrity. The long-term pilot proves that this affordable SHM system can provide automated and real-time warnings of bridge damage and also supports the use of in-house-designed sensors with lower cost and edge computing capabilities such as those used in the demonstration. The successful on-premises–cloud hybrid implementation provides a cost effective and scalable model for expanding monitoring to thousands of railway bridges, democratizing SHM to improve safety by avoiding catastrophic failures.

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Section: Brief Background Of Railway Bridges and Importance Of Struct...mentioning

confidence: 99%

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

Armijo,

Zamora-Sánchez

2024

Sensors

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“…Due to their large numbers and significant importance, the daily maintenance and repair work of these bridges deserves more attention [1][2][3]. Due to being mostly constructed in the previous century, these bridges are limited by the technology available at that time, and their design load standards and capacity cannot meet the current requirements [4]. Currently, the investment in highway bridge construction in China is mainly focused on large-scale bridges, while the funding for small and medium-span bridges is limited.…”

Section: Introductionmentioning

confidence: 99%

Research on construction monitoring of curvilinear continuous beam bridge jacking and horizontal moving construction

Zheng

2024

Archives of Civil Engineering

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This article investigates the issue of beam misalignment in continuous curved beam bridges. Taking the D0–D6 spans of the Gongbin Road elevated bridge as a basis, real-time monitoring of the stress and displacement of the beams is carried out during the jacking and shifting construction process. At the same time, the reaction forces of each support are monitored. The jacking force of the hydraulic jacks is controlled to ensure the stability and safety of the beam during the construction process. Finally, the jacking and shifting monitoring data is organized and compared with theoretical values. It is found that the stress values generated during the jacking phase of the bridge are below the stress control standard. No uplift phenomenon occurs at the supports, and the jacking height is controlled within a reasonable range. The construction process does not cause damage to the beams, and it is safe and reliable. During the shifting construction, the whole bridge was displaced using the jacking method, and the three working conditions were monitored throughout the process. The stress increment at the 2# and 4# sections was relatively small, and the measured stress increments for the entire bridge were all below the stress control standard. The displacement of the bridge abutment during the jacking process was minimal, with no contact with the abutment blocks, and no significant elastic deformation occurred. The jacking displacement was successfully achieved.

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“…2 of 24 2019, among others [9]. These incidents show the potential dangers when critical structural damage goes undetected.…”

mentioning

confidence: 99%

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

Armijo,

Zamora-Sánchez

2024

Preprint

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Structural health monitoring (SHM) is critical for ensuring the safety of infrastructures like bridges. This article presents a digital twin solution for SHM of railway bridges using low-cost wireless accelerometers and Machine Learning (ML). The system architecture combines edge on-premises computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, accelerometers stream raw vibration data, which is processed in the frequency domain and analyzed via machine learning to detect anomalies indicating potential structural issues. The digital twin approach is demonstrated on an in-service railway bridge, where vibration data was collected over two years under normal operating conditions. By learning allowable ranges for vibration patterns, the digital twin model identifies abnormal spectral peaks, suggesting changes in structural integrity. The long-term pilot proves that this affordable SHM system can provide automated and real-time warning of bridge damage and also supports the use of in-house designed sensors of lower-cost and edge computing capabilities than those used in the demonstration. The successful on-premises-cloud hybrid implementation provides a cost effective and scalable model for expanding monitoring to thousands of railway bridges, democratizing SHM to improve safety by avoiding catastrophic failures.

show abstract

Implication of bridge resilience design and lessons from negative examples

Cited by 4 publications

References 9 publications

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

Research on construction monitoring of curvilinear continuous beam bridge jacking and horizontal moving construction

Integration of Railway Bridge Structural Health Monitoring into the Internet of Things with a Digital Twin: A Case Study

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