Lagunita Theme


Call for Papers

Key Info

Notification of Acceptance - March 8, 2019

Final Paper Submission Deadline - May 1, 2019

A special volume of the Proceedings will be published with all the accepted papers.

The 12th International Workshop on Structural Health Monitoring will be held at the Stanford University, CA, USA, from September 10-12, 2019. The workshop features reviews of SHM growth in the last two decades and the perspectives of future SHM directions in research and applications. Papers in support of autonomous and/or intelligent systems and the Industry Internet of Things (IIOT) will be highlighted besides general applications in aerospace, mechanical and civil infrastructure.

The biennial workshop aims to assess the current state-of-the-art technologies and to identify key breakthroughs and emerging R&D challenges that are critical to structural health monitoring. The workshop is also intended to promote communication exchange and cross-fertilization between multiple platforms.

Technical presentations will be made by invited and selected distinguished speakers, and plenary discussions on the future directions and “road-map” will be organized. Potential applications of the techniques to military and civil structures will be discussed. An exhibition area will be available for product and technology demonstrations.

Please visit for detailed guidelines on abstract submission.

Click here to download the PDF version of call for papers.


Major topics for the workshop include:


• Novel smart sensors
• Sensors for extreme environments
• MEMS/NEMS sensors
• Fiber optics
• Piezoelectric/magneto-electric sensors
• CNT sensors

Remote Sensing/Aerial Sensing

• Remote sensing and remote support
• Robotic and UAV platforms for SHM and maintenance intervention

Sensor Networks/System Integration

• Bio-inspired sensor networks
• Remote & wireless communication
• Self-diagnostic networks
• Self-configurable & fault-tolerance networks
• Advanced manufacturing techniques
• Hardware-software integration
• Sensor network reliability

Multifunctional Materials and Structures

• Multifunctional materials
• Self-sensing materials
• Novel energy storage systems
• Energy harvesting and self-diagnostic structures
• Novel composite materials

Diagnostics/Signal Processing/State Awareness

• Advanced signal processing
• Statistical signal processing
• Data mining/fusion
• Real-time diagnostics
• Machine learning
• System identification
• Environmental compensation
• Neural networks
• Inverse methods
• Big data analysis

Prognostics/Health Management/Safety Assurance

• Remaining life estimation
• Quality control
• Life-cycle monitoring
• Integrated structural health management
• System-wide safety assurance
• Condition assessment

Cyber-physical systems for aerospace/civil SHM

• Data-driven simulations and diagnostics
• Digital twins
• Integration of data-driven and physics-based methods
• Multi-physics, multi-scale modeling approaches
• Manufacturing with sensor data
• Multi-objective design optimization
• SHM-based design.


• Quantification techniques
• Probability of detection (POD)
• Reliability methods
• Validation/certification processes, etc.

Applications/Industry Internet of Things (IIOT)

• Asset Health Management of critical infrastructure such as Manufacturing plants or Oil/gas infrastructure
• Life-cycle health management of OEM products
• Application to Civil infrastructure: Bridges, highway systems, buildings, power plants, underground structures
• Application to Transportation Systems: Aircraft and space vehicles, rotorcraft, satellites, space, stations trains, ships, submarines, automobiles
• Autonomous Systems: Drones, UAVs, self-driving cars, robotics, energy management systems
• Medical Devices: Wearable devices, implants with sensing capabilities, health monitoring devices


Prof. Fu-Kuo Chang (Organizer)
Aeronautics and Astronautics
Stanford University, Stanford CA 94305
Tel: +1-650-723-3466, Fax: +1-650-725-3377

Prof. Alfredo Guemes (Co-Organizer)
ETSI Aeronautics
Madrid, Spain
Tel: +34-91-336-6327