SHM Maps and Conjugation

Sparse and Low-rank Methods for Structural Identification and SHM

Recent advances in Statistical Learning techniques have enabled the development of new algorithms for monitoring, data cleansing, data compression, structural identification, damage identification, and structural dynamics in general. This keynote presents novel sparse and low-rank methods to address the inverse problems in structural dynamics, identification, and data-driven health monitoring. ...

Metalinguistic, shmetalinguistic: the phonology of shm-reduplication

Power-efficient wireless sensor reachback for SHM

Wireless sensor networks have recently received great attention from the scientic community, because they hold the key to revolutionize many aspects of our economy and life. On the other hand, the design, implementation and operation of a wireless sensor network in a SHM system requires the synergy of many disciplines, including civil engineering, signal processing, networking, etc. The process...

Damage quantification and localization algorithms for indirect SHM of bridges

This paper presents algorithms for diagnosing the severity and location of damage in a laboratory bridge model. We use signal processing and machine learning approaches to analyze the vibration responses collected both directly from the bridge model and indirectly from a vehicle passing over the model. Features are selected using principal component analysis (PCA), and a regression is performed...

Recent developments in NDT and SHM in the United States

Recent research work on non-destructive testing (NDT) and structural health monitoring (SHM) for civil engineering materials and structures from the United States is described. Developments in three topic areas are discussed: non-linear analysis of ultrasound and vibration for concrete, internal imaging for concrete using two different data types and SHM and NDT for steel cables and tendons. In...