IoT enabled diagnosis and prognosis framework for structural health monitoring

Kumar, Prashant; Raju, Kota Solomon

doi:10.1007/s12652-023-04646-1

Cited by 3 publications

References 28 publications

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Use of IoT for structural health monitoring of civil engineering structures: a state-of-the-art review

Bhatta,

Dang

2024

Urban Lifeline

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The primary goal of Structural Health Monitoring (SHM) is to assess performance and determine the physical state of the structures. Technological improvements and the ubiquitous accessibility of Wi-Fi networks have enhanced real-time SHM based on the Internet of Things (IoT). Extensive structural health evaluation can be conducted using real-time test data collected from various IoT sensors on civil infrastructures. These sensors monitor multiple structural health parameters, and the data is accessible via cloud-based storage platforms. This paper presents an overview of IoT technologies and provides an extensive literature review of IoT applications for civil infrastructures, highlighting associated challenges.

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Use of IoT for structural health monitoring of civil engineering structures: a state-of-the-art review

Bhatta,

Dang

2024

Urban Lifeline

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Building information modeling supported bridge structural health diagnosis and prognosis

Huang,

Lu,

Hua

et al. 2024

Structural Health Monitoring

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This study introduced a framework that facilitates bridge diagnostic and prognostic evaluations and related visualizations, leveraging building information modeling (BIM) techniques and data-driven structural health monitoring. Diagnostic and prognostic algorithms are proposed and able to provide intuitive and accessible structural insights via three-dimensional visualizations supported by the BIM techniques. Through the data communication channel established, virtual model information was successfully embedded into the bridge health evaluations, emphasizing the contribution of BIM techniques for data analysis. The proposed algorithms were applied to a case study of a reinforced concrete bridge. Strain distribution along the bridge deck was mapped in the 3D virtual model, which was able to precisely identify the critical location for potential damage. The residual fatigue life of different parts of the bridge deck was estimated and visualized by considering the main effects of traffic loading, exhibiting good alignments with the diagnostic results. The proposed framework is able to provide understandable and actionable structural information for stakeholders, facilitating the timely identification of structural issues and long-term planning of maintenance schedules.

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Unsupervised Learning Techniques for Vibration-Based Structural Health Monitoring Systems Driven by Data

Colace,

Gupta,

Lorusso

et al. 2023

Handbook of Research on AI and ML for Intelligent Machines and Systems

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Structural damage detection is a crucial issue for the safety of civil buildings, which are subject to gradual deterioration over time and at risk from sudden seismic events. To prevent irreparable damage, the scientific community has directed its attention toward developing innovative methods for structural health monitoring (SHM), which can provide a timely and reliable assessment of structural conditions. In this domain, the significance of unsupervised learning approaches has grown considerably, as they enable the identification of structural irregularities solely based on data obtained from intact structures to train statistical models. Despite the importance of studies on unsupervised learning methods for structural health monitoring, no reviews are specifically dedicated to this topic, considering the application part. The review of studies, therefore, made it possible to highlight the progress achieved in this field and identify areas where improvements could still be made to develop increasingly accurate and effective methods for structural damage detection.

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IoT enabled diagnosis and prognosis framework for structural health monitoring

Cited by 3 publications

References 28 publications

Use of IoT for structural health monitoring of civil engineering structures: a state-of-the-art review

Use of IoT for structural health monitoring of civil engineering structures: a state-of-the-art review

Building information modeling supported bridge structural health diagnosis and prognosis

Unsupervised Learning Techniques for Vibration-Based Structural Health Monitoring Systems Driven by Data

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