Structural health monitoring (SHM) refers to the process of design and implementing a condition monitoring and characterization strategy for engineering structures [1]. Needs for optimization of maintenance costs, objective and science-based inspection practices, increase of safety, emergence of new and improved construction materials and methods, new developments in measurement, sensing, processing and monitoring, as well as recent technological developments in various branches of science and engineering led to creation of relatively new, interdisciplinary branch of engineering – Structural Health Monitoring. SHM examines the use of low-cost, long term monitoring systems to keep civil infrastructure under constant surveillance, ensuring structural integrity. It has received great deal of attention all over the world due to its significant impact on safety and longevity of the structures.
This subject provides an introduction and motivation of SHM with a systematic approach to SHM process. It introduces the topics with basic definitions of measurement and monitoring, various available and emerging monitoring technologies, data acquisition systems and instrumentation, passive and active sensing technologies. The course will cover the principal methods used for local non-destructive evaluation (NDE) and global vibration based SHM techniques. Overview of signal processing basics, feature extraction and a comprehensive list of comparative features will be addressed. Brief overview of structural dynamics will be presented. The students will be provided with hands-on experience in experimental and operational modal analysis, and will learn with structural properties extraction from data. Basics on data interpretation and analysis for both static and dynamic monitoring are presented. It will also introduce students to the concepts of statistical pattern recognition, machine learning, artificial intelligence and neural network and demonstrate the application of these technologies to SHM. Techniques based on data-driven approach and model-based approach to develop SHM solutions are presented. Techniques of combining finite element modelling and field measurements for realistic loading simulations and spatial extrapolation of measured data are discussed and finally, real-world applications and current state of the technology are discussed.
