Keynote Speakers


Distinguished Professor Farhad Ansari

Christopher B. and Susan S. Burke Professor of Civil Engineering, UIC Distinguished Professor and Associate vice Chancellor for Research

Title: Discrete and Distributed Methods for Structural Health Monitoring of Civil Structures

Abstract: The presentation will introduce special techniques for structural health monitoring of Bridges by discrete and distributed optical fiber sensors.   It will cover both basic research as well as practical applications in structural systems.  In particular, applications and capabilities of FBG and PPP-BOTDA based sensors for discrete and distributed detection of microcracks and determination of loads in structural systems will be described.   The fundamental studies will involve quantification of microcrack detection capability of the sensors in terms of the Brillouin gain spectrum (BGS) for microcracks with small crack opening displacements (COD). The applications of the distributed sensors in terms of detection of damage in bridges as well as the tension loss in cables of cable-stayed Bridges will be provided.  In terms of discrete measurements, the use of FBG based sensors for monitoring the structural loads and deformation characteristics of highway bridges will be described. Field applications pertain to the use of Brillouin based sensors for monitoring of cracks in concrete bridges, and weight of trucks in motion by shear based FBG rosettes.  Laboratory experiments will involve experiments on the scaled model of cable-stayed bridges.

Biography: UIC Distinguished Professor, Farhad Ansari, is the Christopher B. and Susan S. Burke Chair in Civil Engineering at the University of Illinois, Chicago. He is acknowledged as the pioneer in applying optical fiber sensors for structural health monitoring and has consulted on and designed structural monitoring systems for bridges and high-rise buildings around the world, including New York’s Brooklyn Bridge; and turn of the century tall buildings in Chicago. Ansari served as president of the International Society for Structural Health Monitoring of Intelligent Infrastructure (ISHMII) from 2009-2013. He is a Founding Fellow of ISHMII, and currently serves as editor-in-chief of the Journal of Civil Structural Health Monitoring.  Farhad Ansari focuses his research on intelligent infrastructure, civil structure rehabilitation, and structural monitoring through sensors and nondestructive testing.


Dr Genda Chen

Professor and Robert W. Abbett Distinguished Chair in Civil Engineering at Missouri University of Science and Technology, Director of INSPIRE University Transportation Center, and Director of System and Process Assessment Research Laboratory

Title: SHM Roles in Autonomous Inspection and Preventive Maintenance of Bridges

Abstract: Missouri University of Science and Technology (Missouri S&T) is leading a ten-partner, five-year University Transportation Center with a theme of “Inspecting and Preserving Infrastructure through Robotic Exploration (INSPIRE).” The goal of the INSPIRE Center is to transform in representative demonstration cases the current labor-intensive, inconsistent, and expensive ad hoc process of bridge inspection and maintenance into an efficient, safe, reliable, and cost-effective data-driven decision-making protocol. In this presentation, the needs for an autonomous bridge inspection and maintenance program are first established. A framework of such a program integrating sensor measurement, nondestructive evaluation (NDE), and data analytics into visual inspection through a mobile platform of robotics is then envisioned to improve the reliability of inspection data and results, streamline the inspection and maintenance process, and augment the inspection of fracture critical members. Next, key to the success of the program, structural health monitoring (SHM) technologies such as lab-on-sensor innovation for the understanding of structural behaviors, microwave imaging for the internal condition monitoring of bridge structures, and adaptive wavelet transform for the extraction of damage and deterioration from images are introduced. Finally, industry-university collaborations, which is critical to realizing the envisioned integrating framework, are dicussed and the potential SHM impacts to bridge preservation are identified. In general, a global lab-on-sensor system is key to quantifying structural behaviors and, together with local NDEs, enables both qualitative and quantitative assessments of the condition of bridge systems or even transportation networks. The bridge condition identified during inspection can be used to prioritize the maintenance of bridges. An unmanned aerial vehicle with one or two remotely-controlled arms can potentially make bridge inspection and maintenance an integrated task. The autonomous inspection and maintenance program likely results in cheaper, faster, and more reliable solutions in bridge preservation.

Biography: Dr Genda Chen is Professor and Robert W. Abbett Distinguished Chair in Civil Engineering at Missouri University of Science and Technology, Director of INSPIRE University Transportation Center, and Director of System and Process Assessment Research Laboratory. He received his Ph.D. degree from State University of New York at Buffalo in 1992 and joined Missouri S&T in 1996 after over three years of bridge design, inspection, and construction practices with Steinman Consulting Engineers in New York City. He was granted three patents and authored over 350 publications in structural health monitoring, smart materials and structures, interface mechanics and deterioration, bridge engineering, and multi-hazard effects. He received the 1998 National Science Foundation CAREER Award, the 2004 Academy of Civil Engineers Faculty Achievement Award, and the 2009, 2011, and 2013 Missouri S&T Faculty Research Awards. He is Chair of the 9th International Conference on Structural Health Monitoring of Intelligent Infrastructure in 2019, Associate Editor of the Journal of Civil Structural Health Monitoring, Editorial Member of Advances in Structural Engineering, a council member of the International Society for Structural Health Monitoring of Intelligent Infrastructure, and an executive member of the U.S. Panel on Structural Control and Monitoring. He was elected to ASCE Fellow in 2007 and Structural Engineering Institute (SEI) Fellow in 2013. In 2016, he was nominated and inducted into the Academy of Civil Engineers at Missouri S&T and became an honorary member of Chi Epsilon.


 Professor Yozo Fujino

University of Tokyo

Title: Infrastructure condition in Japan and new governmental infrastructure R&D program 

Abstract: The economic sustainability, security and well-being of a nation depend heavily on the reliable functioning of infrastructure.  After five decades of development, Japanese stocks of infrastructure have reached enormous amount of over US$7000 billion. Built between the 1960s and 1980s, majority of infrastructure have stood for three to four decades. Most works on highways started in late 1960s, bridges in early 1970s, dams and harbors in early 1980s.
Some of the infrastructures are not in good condition now. Demand for rapid availability of infrastructure in the past might have led to poor design; poor construction quality or structures built using undeveloped technology. Some of bridges are deteriorating due to increasing traffic volumes, the use of anti-freezing salts and humid environment. The collapse of Sasago Tunnel on the Chuo Expressway near Tokyo in 2012 has brought public attention to the issue of infrastructure degradation and led to doubts about their current quality and safety.

Realizing this condition, Japanese government decided to invest on research and development for efficient infrastructure management. A new R&D program named “Infrastructure maintenance, renovation and management” was launched in 2013 under the Japanese Council of Science, Technology and Innovation (CSTI)‘s  Strategic Innovation Program (SIP). The 5-years program covers various subjects with key technologies in condition assessment, non-destructive testing, monitoring and robotics; long-term performance prediction, development of high-quality durable material for repair and replacement, and infrastructure management using advanced information and communication technologies (ICT). The program consists of over 60 research projects involving universities, research institutes and industries. This initiative is expected to prevent further accidents and setting an example for efficient infrastructure maintenance by reducing the burden of maintenance works and cost.


Professor Hong Hao

John Curtin Distinguished Professor, FTSE, FIEAUST, FASCE, FISEAM, Centre for Infrastructure Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University

Title: Innovative Data Analysis Techniques for Structural Health Monitoring

Abstract: Many sources of uncertainties, which could be introduced into the structure during their construction and operational stages, make the reliable structural health monitoring (SHM) difficult. Environmental effect, finite element modelling error, methodology error and noise in the measurement data are the most significant types of uncertainties. The accuracy of structural condition assessment and the reliability of SHM results may be significantly affected. Besides, different data analysis techniques and damage indices may result in different structural damage identification results, even from the same measured data. This paper discusses and introduces a few signal processing techniques for SHM, to achieve a better accuracy and reliability of structural damage identification. The damage indices based on these new signal processing techniques are less susceptible to the uncertainties, but more sensitive to minor structural damage. These include: 1) Vibration Phase Space Topology. A damage index named change of phase space topology derived from the measured vibration responses is defined to detect the location of structural damage; 2) Phase Trajectory Change. The phase trajectories of multi-type vibration responses are obtained from a bridge under moving loads, and a damage index is defined as the separated distance between the trajectories of undamaged and damaged structures to detect the damage location; 3) Chaotic system based technique. A novel technique based on analyzing the responses of a nonlinear oscillator, i.e. Duffing-Homels system, with the recorded UGW signal as an added input is proposed for the detection of minor structural damage. Both numerical and experimental verifications on various structures have been conducted to validate the accuracy and reliability of the proposed approaches to analyse the measurement data and detect the minor structural damage. The results demonstrate that these approaches are sensitive and accurate to detect the structural damage, but not sensitive to uncertainty effects.

Biography: Hong Hao received BEng from Tianjin University, China, MSc and PhD from the University of California at Berkeley, USA. Currently he is John Curtin Distinguished Professor, Director of Research Centre for Infrastructure Monitoring and Protection in Curtin University. He has more than 800 technical publications including over 370 journal papers and 14 edited books and conference proceedings in earthquake engineering, blast and impact engineering and structural condition monitoring. He is one of the most highly cited researchers in civil engineering with H-Index 49 in Google Scholar and 40 in Scopus. He has won more than 20 research, research publication and research supervision awards. He has been invited to give over 50 keynote and many invited presentations in international conferences in many countries. His research results are included in textbooks, adopted in design codes, and used in many construction projects around world. He is the chief editor of International Journal of Protective Structures, and serves in the editorial board of another 10 journals. He was past President of the Australian Earthquake Engineering Society, and has served in many national and international professional committees including expert panel of Australian Research Council. Currently he is Deputy President of the International Association of Protective Structures, Australian Rep in the International Association of Earthquake Engineering, Advisory Board member of Australian Network on Structural Health Monitoring. He is fellow of Australian Academy of Technical Science and Engineering, fellow of Institution of Engineers Australia, fellow of American Society of Civil Engineers, and fellow of International Society of Engineering Asset Management.


Dr Rob Heywood

Principal of Heywood Engineering Solutions, Australian Centenary Scholarship and Warren Medal recipient

Title: Bridge in-service Performance Monitoring and Risk Management

Abstract: The continual increase in heavy vehicle loads over the last century has resulted in some Australian and international bridges operating with smaller margins compared to bridge assessment standards.  Bridge Asset managers and owners are seeking to manage the risks and uncertainties associated with the substructures and superstructures of these bridges, particularly given many of these small to medium span bridges are operating with little or no signs of distress.

The cost of strengthening these structures is unacceptable while restricting access is unpalatable leaving asset owners seeking to refine their understanding of the risks and uncertainties across the network knowing that bridges around the world collapse from time to time.  Consequently there is a need to identify bridges that can safely remain operational and those where intervention is appropriate.

This paper examines the role of bridge in-service performance monitoring (BiSP) in assisting owners and assessors close the plausibility gap between the assessed capacity and the observed performance as well as identifying when intervention is necessary and informing scenarios where distress has been observed.  The paper highlights the important role for bridge in-service performance monitoring in a risk savvy approach to bridge access and asset management.

Biography: Dr Rob Heywood is a structural engineer with a particular interest in assessing / extending the life of structures, understanding structural behaviour & identifying the cause/s of failure. A recent focus has been on closing the ‘plausibility gap’ between the observed and theoretical performance of bridges and the safe management of bridges subjected to loads that exceed their design load and their assessed capacity.

Rob is the Principal of Heywood Engineering Solutions, a recipient of the Australian Centenary Scholarship and the Warren Medal for his research into live loads applied to bridges, a member of the OECD DIVINE international research project investigating the dynamic interaction between heavy vehicles and infrastructure, a past Chairman of the Structural College Board of Engineers Australia and an Urban Search & Rescue engineer.

Rob has accepted invitations to speak on topics that include assessment of structures, forensic engineering, earthquake damage, detailing concrete structures, bridge-vehicles interaction, bridge testing, live loads on bridges and cyclone damage.  He was invited to present evidence to the Canterbury Earthquakes Royal Commission regarding the collapse of the CTV building where many lost their lives.




Professor Hui Li

Harbin Institute of Technology, China

Title: Data Science and Engineering for Structural Health Monitoring

Abstract: Structural health monitoring (SHM) technology study the damage or even characteristics of disaster evolving of structures by various types of sensors installed on structures and provide scientific support for the structural design, construction, maintenance and operation safety. The significant scientific issues of SHM can be concluded as ‘sensing’ and ‘data’. According to the widely application of SHM on civil infrastructures and accumulation of huge quantities of data, it is well-recognized that data sciences and engineering for SHM is increasingly becoming a world-wide research focus. The issue of ‘data’ is core target of SHM which includes the data acquisition, transmission and management, data analysis and mining, structural damage identification and structural safety assessment and so on. This paper reviews the recent research development of data sciences and engineering on our research group which includes data acquisition by compressive sensing based on group sparse optimization, computer vison and deep learning methods for data anomaly detection and structure condition assessment, the identification and modelling of spatio-temporal distribution of vehicle loads, and corrosion damage and crack identification by computer vision techniques. Finally, the artificial intelligence in civil engineering is the extension of SHM technique, and will make the civil structure have ability of “see”, “sensing”, “thinking” ,”talking”, “action” and “adaptation” (2S+2T+2A).

Biography: H.Li. received her Ph.D. in theoretical and applied mechanics from the Harbin Institute of Technology (HIT) in 1994. She works at HIT as an associate professor (1996) and professor (1998). Now she is Changjiang Scholarship professor at HIT. Her research has been primarily in the areas of structural health monitoring, structural control, artificial intelligence applications, smart materials and structure, nanomaterials and composites, wind engineering and earthquake engineering. Dr. Li has directed more than $5M in funded research and published more than 300 technical papers/reports, including three books. Dr. Li is the current president of International Association for Structural Control and Health Monitoring, and president of ANCRiSST, the Board member of International Society of Structural Health Monitoring for Intelligent Infrastructure, the associate editors of Structural Health Monitoring, Civil Structural Health Monitoring, Vibration and Control, and the president of Structural Control and Health Monitoring in China. She has received numerous awards, including the Structural Health Monitoring Person of the Year Award, HoLiangHoLi Awards, the National Awards for Science and Technology, etc.


Professor Su Taylor

Professor of Structural Engineering and Dean of Research for the Faculty of Engineering and Physical Science, Queen’s University Belfast

Title: Advanced SHM using Computer Vision and Machine Learning

Abstract: The research presented in this paper aligns to the digital transformation of Structural Health Monitoring (SHM) Systems. SHM can provide valuable information on the structural capacity and changes in structural performance, generally as an indication of damage.  The applications of many SHM systems are currently limited by structure type, access for fixing of sensors, light levels and maintaining power supplies. This paper investigates the use of computer vision systems for SHM to ensure the safety and resilience of our civil infrastructure. Computer Vision is a new method of SHM which operates by recording motion pictures of a target area, or feature, on bridges and civil  infrastructure. The development and validation of a contactless deflection monitoring system which tracks features to sub pixel accuracy is presented. The image is also pre-filtered for changing light levels in the environment and due to crossing freight.   Machine learning is also used to identify events which provides useful data on real loading. The results of this research confirm the suitability of these  systems for information to accurately determine the health of bridges.

Biography: Su Taylor is a Professor of Structural Engineering and the Dean of Research for the Faculty of Engineering and Physical Science at Queen’s University Belfast, a UK Russell Group University.  She is a Vice President of  ISHMII and leads the Intelligent Infrastructure group within the School of Natural and Built Environment in Queens. This a multi-disciplinary group addressing global challenges in resilient infrastructure and she has attracted project funding of over £5m from the EU Marie Curie, USA-Ireland Platform, EPSRC, InnovateUK, Knowledge Transfer Partnerships, DfT and InfrastructureNI. A prioritisation of her research is the resilience our built environment by using advanced sensor technology and data management to supply critical information on structural integrity.




Ir. Professor You-Lin XU

Chair Professor of Structural Engineering & Dean of Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong, China

 Title: SHM-Based Life-Cycle Management of Long-Span Cable-Supported Bridges

Abstract: Long-span cable-supported bridges are important infrastructure to our society but subjected to deterioration once they are built due to ageing effects, natural hazards and man-made extreme events. A sudden failure or loss of functionality of the bridges may have severe economic, social and environmental impacts. Therefore, it is crucial to implement life-cycle management (LCM) strategies that could maintain performance of the bridges within acceptable levels in terms of cost-effective intervention actions through their life-cycle (Frangopol and Soliman, 2016). Life-cycle cost and structural performance are two basic but conflicting aspects required for serious consideration in the LCM of the bridges. A life-cycle cost consists of not only the initial design and construction cost, but also those due to operation, inspection, maintenance and repair during a specified lifetime (Frangopol and Messervey 2007). Structural performance can be reflected mainly in terms of functionality, safety, sustainability and reliability. Multi-objective optimization techniques along with the supplementary information, such as the cost of interventions, the status of structures, and the effect of maintenance on the structural performance, should be employed to find the optimum inspection/maintenance types and application times.


It is noted that uncertainties inevitably exist in structural models, response measurements, loading phenomena, deterioration mechanisms, and surrounding environment. These uncertainties can be classified as two broad categories: aleatory uncertainties which describe the inherent randomness of phenomenon being observed, and epistemic uncertainties which describe the errors associated with imperfect models of reality due to insufficient and inaccurate knowledge (Ang and Tang 2007). Because of these uncertainties, the reliability of the current LCM is difficult to be assessed. Structural health monitoring (SHM) technology has recently attracted increasing attention in the civil engineering community. More than a hundred long-span bridges worldwide have been equipped with SHM systems which are designed to assess the bridges’ functionality and safety while tracking the symptoms of operational incidents and potential damage. SHM technology is based on a comprehensive sensory system and a sophisticated data processing system implemented with advanced information technology and supported by cultivated computer algorithms. This technology allows actual loading conditions to be monitored, various types of structural responses to be measured, and deterioration and damage to be identified. SHM technology thus can provide a promising means and solid foundation for tackling the challenging issues in the LCM of the bridges.


This paper therefore proposes an SHM-based LCM framework for long-span cable-supported bridges and their relationship is shown in Figure 1. It involves seven major tasks: (1) to integrate multiscale finite element modelling and model updating with stress analysis for predicting both global and local structural responses with external loadings, dynamic characteristics and responses measured by the SHM system; (2) to determine the optimal placement of multi-type sensors for the best global and local response reconstruction of civil structures with the input of structural responses measured by the SHM system; (3) to assess the current health status of the structures based on the previous loading histories and using the SHM-based damage detection method; (4) to perform proper inspection, maintenance and repair work on the basis of the evaluated structural health states; (5) to develop loading models based on incessant field measurement data from the SHM system so that the previous loading histories can be analyzed and future loadings can be forecast; (6) to conduct damage prognosis and predict the remaining service life of the civil structures; and (7) to develop LCM strategies for making optimal decision under multiple objective and various constraints. The seven major tasks are interconnected and will be introduced in detail in this paper.


Figure 1 General components of SHM-based LCM framework


It is noted that the successful implementation of the entire SHM-based LCM framework is quite complicated and challenging, and many techniques and disciplines are involved in this framework. Although not all the seven major tasks have been completed yet in a systematic way, some relevant works which have been done by the author and his research team are presented in this paper with reference to the Tsing Ma suspension bridge and the Stonecutters cable-stayed bridge in Hong Kong. These works include (1) the Tsing Ma Bridge and its SHM system; (2) the loading assessment and loading models of the Tsing Ma Bridge based on incessant field measurement data from the SHM system; (3) the multiscale finite element modelling and model updating of the Stonecutters Bridge; (4) the SHM-based stress analysis of the Tsing Ma Bridge due to multiple dynamic loadings; (5) the SHM-based fatigue damage prognosis and fatigue reliability analysis of the Tsing Ma Bridge; and (6) the SHM-based bridge rating system and inspection. The results from this case study indicate that the proposed SHM-based LCM framework has a potential to be used in practice for long-span cable-supported bridges with SHM systems. However, some further works shall be done following the proposed framework in order to turn the potential to the reality. These further works include (1) the determination of the optimal placement of multi-type sensors for the best global and local response reconstruction of the bridge through the input of measured responses from the SHM system; (2) the assessment of the current health status of the bridge using the SHM-based damage detection method; and (3) the development of SHM-based LCM strategies for making optimal decision under multiple objective and various constraints.

Biography: Professor You-Lin Xu is Dean of the Faculty of Construction and Environment and Chair Professor of Structural Engineering at The Hong Kong Polytechnic University. He was Head of the Department of Civil and Environmental Engineering from 2007 to 2013. He received his PhD from the University of Sydney in Australia. Professor Xu has conducted researches and served as a consultant in structural engineering for over three decades, with special interests in wind effects on long-span bridges and tall buildings, structural health monitoring of mega infrastructure, structural vibration control and smart structures. He has published over 240 SCI journal papers, delivered over 90 keynote or invited lectures at international conferences/ symposiums/ workshops. Professor Xu also served in various capacities for relevant international associations and international journals. He is on the Civil Engineering list of the Most Cited Researchers developed for Shanghai Ranking’s Global Ranking of Academic Subjects 2016 by Elsevier. In recognition of his outstanding research achievements, he received several prestigious awards, including the ASCE Robert H. Scanlan Medal in 2012, the Qian Ling Xi Computational Mechanics Award in 2010 and Croucher Award in 2006. Professor Xu has written three books, they are: Structural Health Monitoring of Long-Span Suspension Bridges, Wind Effects on Cable-Supported Bridges and Smart Civil Structures published by Spon Press (Taylor & Francis), John Wiley & Sons, and CRC Press (Taylor & Francis) respectively. He has been engaged in many high-impact knowledge-transfer projects, including the health monitoring projects on the Tsing Ma Bridge and the Stonecutters Bridge in Hong Kong, the CCTV Tower in Beijing and the Shanghai Tower in Shanghai. He is a Fellow of The Hong Kong Institution of Engineers, the American Society of Civil Engineers, the Engineering Mechanics Institute of the U.S.A., and the Institution of Structural Engineers of the U.K.