Los Alamos Na tiona l Labor ato ry, an a ffirm ative action/equal o pportunity e mployer, is opera ted by the Uni ve rsity of Californ ia for t he U . S . Depa rtment of Ene rgy u nde r con tra ct W-740 5-ENG-36. By acceptance of th is article, the pu b lisher recogn izes that the U.S. Government re tai n s a nonexcl usive , royalty-f ree licen se to p u blish or reproduce the pub lis hed form of th is contribution , or to a llow ot hers to do so, for U . S. Government purposes. Los Al amos National Laboratory requests that the pu b lish er iden t ify thi s article as work performed under the aus p ices o f t he U . S . De p artment of Ene rgy. Los A lamos N ational La boratory st rongly s upports a cad em ic freedom and a researcher's rig h t to pub lis h ; as an i n stitu tion, however, the La borato ry d oes not endors e th e viewp oint of a pu blica ti on or gua rantee its technica l corre ctne ss . Recently, a new approach in vibration-based structural health monitoring has been developed utilizing features extracted from concepts in nonlinear dynamics systems theory . The structure is excited with a low-dimensional chaotic input, and the steady-state structural response attractor is reconstructed using a false nearest neighbors algorithm . Certain features have been computed from the attractor such as average local "neighborhood" variance, and these features have been shown in previous works to exceed the damage resolving capability of traditional modal-based features in several computational and experimental studies . In this work, we adopt a similar attractor approach, but we present° a feature based on nonlinear predictive models of evolving attractor geometry. This feature has an advantage, over previous attractor-based features in that the input excitation need not be monitored . We apply this overall approach to a steel frame model of a multi-story building, where damage is incurred by the loosening of bolted connections between model members
