Mini-symposia

This mini-symposium will showcase recent developments of sensing and sensor technology and its applications to structural health monitoring of civil infrastructure. The topics of this mini-symposium include but not limited to: smart sensor, wireless sensing, vision/ infrared/hyperspectral sensing, UAV/UGV based sensing, noncontact sensing, GNSS sensor, LiDAR, etc. 

SHM applications to large infrastructural systems, including bridges, dams, wind turbines, and energy systems, are still quite limited due to their high costs, localized nature of the measurements using off-the-shelf sensing technologies, and the inability of global analysis algorithms to detect local damage. In order to address these challenges, significant research efforts are being carried out focusing on the integration of smart multifunctional materials and SHM systems. This can be achieved by leveraging state-of-the-art materials engineering advances, including new nano-/micro- structural composites (e.g. self-sensing smart concretes and smart pavements), smart sensors, including self-powered sensor networks, real time vibration-based systems, novel methods for system identification and operational modal analysis using distributed smart sensor networks, modern information and communication systems, machine learning and signal processing technologies, advanced structural analysis, and more. The MS specifically addresses those topics, including major open challenges, such as the improvement of smart materials and sensor systems, the accuracy of data sampling, the development of effective diagnostic methods based on smart materials and sensors, the analysis and management of big data for structural performance evaluations and more. 

Nondestructive evaluation (NDE) is a precursor to SHM. It includes the complete gamut of nondestructive testing (NDT) techniques including mainly those based on mechanical (modal, acoustic) and electromagnetic (magnetic, eddy current, radar, microwave, terahertz, thermography, optical, x-ray) waves. Those techniques are associated with a significant amount of data generated and signals to be processed as well as converting those data to images and combined with statistical aspects, such that it can be understood by a broader public in the end. This holistic process can be considered to be NDE. Many of the NDT techniques (i.e. acoustic emission, guided waves, fibre optics, etc.) have been converted into SHM applications. However, developments in NDE are a continuous source to challenge SHM ideas. This mini-symposium will therefore target on how to characterize and evaluate materials in a non-destructive way specifically considered for infrastructure applications in view of quality assurance and condition monitoring, the latter to be also considered in the context of residual operational life assessment or even operational life extension.

Acoustic Emission has been applied for monitoring Civil Infrastructures to find active defects using global and/or local monitoring approaches. In this mini-symposium, we aim to demonstrate the applications of AE in variety of structures such as bridges, pipelines, nuclear power plants, dams, etc, using state-of-the-art AE technologies.

The aim of this session is to report the recent research advances on innovative data-driven techniques for structural health monitoring. The audience may benefit from the proposed special session to acquire the understandings and recognitions of achievements in structural health monitoring research activities, based on the new technologies, e.g. computer vision, artificial intelligence, smart sensing, swarm and machine learning techniques etc. 

Data driven or model-free approaches have been proposed for the identification and performance evaluations of complex structural systems. However, it is still challenging to carry out structural identification/evaluation based on monitoring data from the SHM systems. This mini-symposium calls for theoretical or practical contributions related to the innovative methodologies and techniques for data driven system identification and performance evaluations based on signal processing, big data, compressive sensing and sparse representation, artificial intelligence with machine learning/deep learning techniques, etc. 

Papers are welcomed on the identification of system properties such as modal characteristics from vibration measurements.
The identified properties can be exploited to calibrate numerical models or to evaluate damage at different levels by model or non-model based methods.
As the extracted system properties are influenced by environmental conditions (e.g. temperature), papers that filter these influences will also be part of this MS.  

 

In addition to innovative sensing technology, there is an urgent need to develop advanced analytic tools which enable data-driven damage detection (diagnosis) and prediction (prognosis) in a real-time or near real-time manner. Machine learning has currently emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through sensing. In particular, the probabilistic machine learning paradigm, which is capable of describing how to represent and manipulate uncertainty in modelling and prediction, has a central role in massive data analytics. This mini-symposium provides a platform to exchange the latest research on the application of various machine learning and artificial intelligence methods for SHM, such as convolutional neural networks, compressive sensing, sparse learning, ensemble learning, transform learning, deep reinforcement learning, generative modelling, and big data analytics. 

The objective of this mini-symposium is to provide a forum for discussing case studies on the use of fibre optic sensing in real world applications of infrastructure monitoring. The submissions to this mini-symposium can include both academic research and commercial applications, and all types of fibre optic sensing techniques are welcome (discrete and distributed, short-gauge and long-gauge, based on interferometry, fibre-Brag grating, scattering, etc.). However, the emphasis should be on the application of the fibre optic sensing techniques in real structures, and the outcomes (results, lessons learned, recommendations) of using these techniques in infrastructure monitoring. 

Structural Health Monitoring (SHM) of civil infrastructures has been examined and applied by academia and bridge authorities as well as those in industries in terms of a potential solution to modify labor-intensive inspection with labor- and cost-effective inspection making full use of Sensing Technology, Information and Communication Technology (ICT) and Internet of Thing (IoT). Although adoption of SHM approaches in industry is on the rise, despite significant research activity, SHM technology has not yet been widely accepted by working level officials and authorities; this is probably caused by few satisfactory results in real-world applications. Furthermore, since the data are all collected in experiment or field environments, uncertainty quantification and management of in-situ measurements also play a critical role in the extraction of features which can influence decisions in the process of prognosis and diagnosis of instrumented structures. The aim of this Mini-Symposium is to provide a forum in which scientists and engineers from academia and industry can present their state-of-the-art research results on SHM technology, focusing on real-world applications and successes. 

The use of SHM systems is increasingly growing worldwide, the cost of sensors and monitoring systems is also decreasing, and there are many software applications and algorithms, each time more effective for damage detection and identification. Nonetheless, some investors and bridge operators and managers are still reluctant for SHM systems and, in some cases, is not easy to foresee the long-term benefits. A key aspect for cost-benefit analysis for new SHM Systems is the availability of information on specific cases, statistical data on short and long-term maintenance savings, system updating costs, analysis costs, damage detection reliability and its economic impact if early detection is achieved, etc.
Main objective of this symposium is to bring together researchers, experts, industry and operators to discuss cost-benefit issues for SHM systems, analyze specific cases and to design strategies for data collecting for long-term benefit and cost evaluation.
Research and application papers are encouraged on the following topics:
• Cost-benefit SHM cases
• SHM data processing and analysis costs
• SHM Instrumentation and/or system updating costs
• Damage detection reliability-cost analysis
• Long-term cost forecast
• Cost-analysis methodologies for SHM systems
• Maintenance-SHM cost balance

In this mini-symposium, the impact of SHM application on enhancing the bridge evaluation will be discussed. Bridge design codes provide an equation for estimating the load carrying capacity of bridges which are based on the resistance of elements, applied dead loads and traffic loads. In situ monitoring of bridges, provides a better understanding on capacity of the elements, the load distribution among elements of bridges, etc. The data provided by SHM sensors can be used for evaluating the load carrying capacity of bridges more precisely. 

This mini-symposium covers theoretical, computational and experimental work on system identification and structural health monitoring of Civil energy infrastructures, like onshore or offshore wind turbines, dams, high voltage transmission lines, pipelines, etc., giving special attention to real-world applications. 

This MS will present the state of art and practice in SHM of offshore, marine and subsea structures such as wind and tidal turbines, rigs, risers and pipelines. 

The assessment of health condition and preventive conservation of Cultural Heritage Structures is of primary concern in many countries all over the world, especially in seismic prone areas. Within this context, SHM strategies based on both static and dynamic monitoring are quickly increasing in diffusion and importance. The Mini-Symposium is intended to focus on methodological aspects, recent developments and applications of fully non-destructive assessment and SHM of historic structures (e.g. monuments, churches, towers, historic bridges and infrastructures). Suitable topics include, but are not limited to:
• Multi-disciplinary strategies of preventive conservation and SHM;
• SHM algorithms for system and/or damage identification of historic structures;
• Effects of environmental and operational variability on health-sensitive features;
• Innovative sensing techniques;
• Data fusion of measurements of different physical parameters;
• Design, implementation and management of long-term monitoring systems;
• Post-earthquake and seismic assessment;
• Seismic interferometry;
• Vibration-based tuning of FE models and surrogate models for structural identification;
• Optimal sensor placement techniques.
 

The scope of this Mini-symposium is to provide a venue for reporting recent advances and successful applications in the field of Seismic Structural Health Monitoring, for exchanging lessons learned and discern most promising directions for focused future work. The symposium deals with theoretical and computational issues and applications and welcomes contributions that cover, but are not limited to, identification and damage detection, real time monitoring systems and projects, integration of seismic SHM in procedures for risk assessment and emergency management. 

The application of advanced structural sensing, monitoring, and data analytics techniques can enhance disaster prevention and resilience of civil infrastructure systems against natural disasters such as earthquakes, typhoons / hurricanes, and extreme weather events through two functions: (i) pre-event risk assessment, structural performance evaluation, and (ii) post-disaster rapid assessment, response, and recovery.
The purpose of this MS is to share and discuss technical needs and future directions of SHM technologies that contribute to infrastructure disaster prevention and resilience. The MS welcomes relevant research from academic, government, and industry sectors including studies that utilize measurement data before and during disasters for decision making. The invited topics include but are not limited to sensors technology, sensing systems, data analytics, system identification, damage diagnosis and prognosis, model- and data- driven decision making techniques, etc. In addition, the MS welcomes report on performance evaluation of infrastructures in previous disaster events (earthquake, Tsunami, flood) using data, and case studies on the economic advantages of sensing and monitoring technologies for infrastructure damage diagnosis and restoration.
 

This mini-symposium shall give an overview of tools and methods for structural health monitoring of large extended geotechnical structures, with a strong focus on long distance monitoring techniques. These include distributed and quasi-distributed fiber-optic sensing technologies as well as remote sensing methods. Presentations and discussions shall cover the different sensing technologies (FBG, distributed Rayleigh, Raman and Brillouin sensing, laser scanning, interferometric radar etc.), as well as installation considerations (sensor cable design and characterization, concrete embedding, concrete surface application, soil embedding, etc.).
Focus shall be on contributions covering industry applications and real-life case studies, providing hands-on experience from use-cases such as settlement, deformation and crack monitoring along slopes, tunnels, dams, embankments, retaining walls. pipelines or other extended geotechnical structures.
 

Civil infrastructure systems, due to their inherent vulnerability, are at risk from aging, fatigue and deterioration processes. The exposure of civil infrastructure to combined effects of discrete and continuous damaging events under uncertainty pose a major challenge to the reliable prediction of the performance and service life of structural systems. To reduce this uncertainty, it is necessary to integrate life-cycle predictions with the results of inspection and data from SHM. This Mini-Symposium is aimed at exploring the value of SHM in the life-cycle assessment, inspection and maintenance of civil infrastructure including buildings, bridges, roads, railways, and dams, among others. Emphasis is placed on the use of cost-effective monitoring systems for data acquisition to support better decision-making strategies on the life-cycle and service life of civil infrastructure systems. 

Structural Health Monitoring (SHM) can be successful for real structures if it is based on numerical models with physical meaning. Such models facilitate a better understanding of the local and global structural behavior and enable a better interpretation of the measured data. ‘Digital Twins’ are recently considered as a step forward in SHM uniting a physics-based model with a sensor network and continuous data flow to a direct mirror of the physical system. However, the term Digital Twin is frequently used in different context and with different goals. The aim of this MS is to provide an overview on current concepts, practical experience and challenges of SHM with physics-based models and digital twins applied to large engineering structures. 

Blind Source Separation (BSS) is a fundamental problem that has broad applications in many fields, such as machine learning, pattern identification and signal processing. The aim of BSS is to reconstruct signals (sources) of interest and their mixing function from sole (response) observations. Typical BSS methods, such as the Independent Component Analysis (ICA) technique, the Second-Order Statistics (SOS) technique, and the Bayesian approach have recently attracted increasing interest for application to SHM-relevant problems. This mini-symposium focuses on a benchmark study of SHM-oriented BSS by using two sorts of real-world data: (i) acceleration response data acquired from a five-story steel-frame model for the separation of multiple dynamic excitations and for locating the separated excitations; (ii) strain response data collected from a long-span bridges for the extraction and separation of different ingredient (sources), including temperature-induced ingredient, highway traffic-induced ingredient, railway traffic-induced ingredient, and wind-induced ingredient, which is greatly beneficial to damage detection and reliability assessment. Participants can apply their own BSS approaches to the above data. 

 

The information and integrity management of infrastructures is challenged by limited resources and an incentive for efficiency together with life safety and societal wealth requirements. For addressing these challenges, Structural Health Monitoring should be rigorously connected to a systematic infrastructure information management and integrity management planning and optimisation. In this context, we are encouraging and welcoming contributions of researchers across scientific disciplines with contributions e.g. (1) on the modelling and value quantification of information and (2) integrity management processes and (3) the modelling and utilization of digital, big data and industry 4.0 information. 

National and World Treasures of invaluable monuments and historic structures need SHM advances to help preserve them for the coming generations as marks of the development of civilizations. The capabilities provided by SHM shall meet the demand of such preservation by providing, definition of amniguities relevant to ancient materials and systems, field assessments with minimum physical interventions, defect monitoring, threshold limit alarm notifications and optimization of surrounding conditions to enhance the life span of the monument.
As SHM is crucially needed to support world advancement, it is equally needed to preserve our history to always gain lessons and knowledge from it and look at the future with wiser eyes.
 

A forum to discuss the newest challenges of the aging infrastructures in Australia/Oceania as well as the latest solutions in addressing this and making our structures smarter
 

The ISHMII Committee on Standardization is currently responsible for the development of ISHMII series codes on SHM of Civil Infrastructure as international model codes, which include: Level 1 − ISHMII Code: General Principles, Definitions and Approaches; Level 2 − ISHMII Guidelines for Different Types of Major Structures or Major Sensing Technologies, and Level 3 − Recommended SHM Guidelines (or Standards) for Different Countries or Regions. Presented in this mini-symposium are the research activities related to (i) developing international model codes (ISHMII code series) for SHM of infrastructure; (ii) establishing the architecture of intelligent infrastructure; (iii) maintaining the state-of-the-art and the state-of-practice knowledge database on SHM and intelligent infrastructure; and (iv) the exchange of information and harmonization on SHM documentations, specifications, and guidelines from different counties and regions.