This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

This book is organized around the various sensing techniques used to achieve structural health monitoring. Its main focus is on sensors, signal and data reduction methods and inverse techniques, which enable the identification of the physical parameters, affected by the presence of the damage, on which a diagnostic is established. Structural Health Monitoring is not oriented by the type of applications or linked to special classes of problems, but rather presents broader families of techniques: vibration and modal analysis; optical fibre sensing; acousto-ultrasonics, using piezoelectric transducers; and electric and electromagnetic techniques. Each chapter has been written by specialists in the subject area who possess a broad range of practical experience. The book will be accessible to students and those new to the field, but the exhaustive overview of present research and development, as well as the numerous references provided, also make it required reading for experienced researchers and engineers.

The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.

Proceedings of the Tenth International Workshop on Structural Health Monitoring, September 1–3, 2015. Selected research on the entire spectrum of structural health techniques and areas of applicationAvailable in print, complete online text download or individual articles. Series book comprising two volumes provides selected international research on the entire spectrum of structural health monitoring techniques used to diagnose and safeguard aircraft, vehicles, buildings, civil infrastructure, ships and railroads, as well as their components such as joints, bondlines, coatings and more. Includes special sections on system design, signal processing, multifunctional materials, sensor distribution, embedded sensors for monitoring composites, reliability and applicability in extreme environments. The extensive contents can be viewed below.

Non destructive testing aimed at monitoring, structural identification and di- nostics is of strategic importance in many branches of civil and mechanical - gineering. This type of tests is widely practiced and directly affects topical issues regarding the design of new buildings and the repair and monitoring of existing ones. The load bearing capacity of a structure can now be evaluated using well established mechanical modelling methods aided by computing facilities of great capability. However, to ensure reliable results, models must be calibrated with - curate information on the characteristics of materials and structural components. To this end, non destructive techniques are a useful tool from several points of view. Particularly, by measuring structural response, they provide guidance on the validation of structural descriptions or of the mathematical models of material behaviour. Diagnostic engineering is a crucial area for the application of non destructive testing methods. Repeated tests over time can indicate the emergence of p- sible damage occurring during the structure's lifetime and provide quantitative estimates of the level of residual safety.

This is the third book in a series on Computational Methods in Earthquake Engineering. The purpose of this volume is to bring together the scientific communities of Computational Mechanics and Structural Dynamics, offering a wide coverage of timely issues on contemporary Earthquake Engineering. This volume will facilitate the exchange of ideas in topics of mutual interest and can serve as a platform for establishing links between research groups with complementary activities. The computational aspects are emphasized in order to address difficult engineering problems of great social and economic importance.

Long span suspension bridges cost billions. In recent decades, structural health monitoring systems have been developed to measure the loading environment and responses of these bridges in order to assess serviceability and safety while tracking the symptoms of operational incidents and potential damage. This helps ensure the bridge functions properly during a long service life and guards against catastrophic failure under extreme events. Although these systems have achieved some success, this cutting-edge technology involves many complex topics that present challenges to students, researchers, and engineers alike. Systematically introducing the fundamentals and outlining the advanced technologies for achieving effective long-term monitoring, Structural Health Monitoring of Long-Span Suspension Bridges covers: The design of structural health monitoring systems Finite element modelling and system identification Highway loading monitoring and effects Railway loading monitoring and effects Temperature monitoring and thermal behaviour Wind monitoring and effects Seismic monitoring and effects SHMS-based rating method for long span bridge inspection and maintenance Structural damage detection and test-bed establishment These are applied in a rigorous case study, using more than ten years' worth of data, to the Tsing Ma suspension bridge in Hong Kong to examine their effectiveness in the operational performance of a real bridge. The Tsing Ma bridge is the world's longest suspension bridge to carry both a highway and railway, and is located in one of the world’s most active typhoon regions. Bridging the gap between theory and practice, this is an ideal reference book for students, researchers, and engineering practitioners.