The ownership cost, availability, and safety of Air Force systems is significantly influenced by the practice of periodic nondestructive inspections (NDI) and maintenance. Department of Defense studies [ODUSD (S&T) white paper, Jan ‘01] indicate “unnecessary or inappropriate maintenance contributes to inflated ownership costs and generally reduced readiness for deployable assets, …” On the other hand, reducing periodic NDI and maintenance may decrease safety margins and lead to expensive, disruptive, unscheduled down time. This presentation will address the application of principles of dynamical systems theory to issues involving vehicle health monitoring. The motivation for this approach is its broad applicability to very wide array of engineering design and analysis problems. It has been proven to be successful in aeronautical and aerospace engineering, the chemical process industry, electric power systems design and management, automotive systems design, and materials and manufacturing process design. The common thread that allows this approach to be so widely applicable is the uniform and systematic methods available for addressing issues such as how to formulate efficient mathematical models of physical processes, how to incorporate uncertainty into mathematical models, how to best select and place sensors and actuators, and how to optimize and efficiently trade-off performance measures such as cost, safety, throughput, availability, etc. In particular, this presentation will focus on experimental validation of a sensor placement algorithm and associated signal processing.