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Published 2009 | Accepted Version
Book Section - Chapter Open

A time-reversed reciprocal method for detecting high-frequency events in civil structures with accelerometer arrays

  • 1. ROR icon California Institute of Technology

Abstract

A high-frequency experimental method of detecting a failure event in engineered structures is presented that uses the property of wave propagation reciprocity and time-reversed reciprocal Green's functions. The premise is that if a numerical database of pre-event, source-receiver Green's functions can be compiled for multiple locations of potential damage in a structure, that database can subsequently be used to identify the location and time of occurrence of a real failure event in the structure. Once a fracture source emits a wavefield that is recorded on a distributed set of accelerometers in the structure, time-reversed waves can be obtained by convolving the displacements with the database of time-reversed Green's functions and stacking the results. The correct location and time of the fracture source can be inferred from the subset of Green's functions that exhibits the best focus in the form of a delta function. The 17-story, steel moment-frame UCLA Factor building contains a cutting-edge, continuously recording, 72-channel, seismic array. The accelerometers' 500 sample-per-second recordings have been used to verify the ability to observe impulse-like sources in a full-scale structure. Application of an impulse-like source on the 3rd and 15th floors of the Factor building shows that the associated displacements serve as useful approximations to the building's Green's functions in the far field, and can be used in investigations of scenario fracture location and timing.

Additional Information

©2010 Techno-Press. We appreciate support from the U.S. Geological Survey for Factor array operation and maintenance, and the NSF Center for Embedded Networked Sensing at UCLA for basic research. We are grateful to Prof. C-M. Uang for access to the moment-frame testing facility at UCSD, and to S. Irvine, M. Lukac, and I. Stubailo for processing the fracture data.

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