|
 Department
of Materials Science and Engineering
Learn more about
Materials Science
| |
 |
Professor Kanji Ono
tel.
(310) 825-5233
fax (310)
206-7353
|
 | Professor; B.Engr.
Tokyo Institute of Technology; Ph.D. Northwestern University;
Postdoctoral research, Northwestern University; Visiting Professor,
International Christian University; Director, Tokyo Study Center,
University of California Education Abroad Program; Henry M. Howe
Medal, American Society for Metals; Achievement Award, American
Society for Nondestructive Testing; Achievement Award and Gold Medal
Award, Acoustic Emission Working Group; Editor, Journal of Acoustic
Emission. |
Research Description
| Our research is about the
mechanical behavior and nondestructive evaluation (NDE) of structural
materials. |
| Of late, we concentrate on
composite materials and aluminum alloys, using acoustic emission and
related ultrasonic methods. In particular, we examine techniques to
predict incipient fracture with advanced acoustic emission analysis,
relying on digital signal acquisition and pattern recognition
processing. |
| Acoustic emission (AE) has
demonstrated capabilities for monitoring structural integrity and for
dynamically characterizing materials behavior. Fatigue fracture in
aluminum alloys and micro-fracture processes in fiber reinforced
composites generate numerous acoustic emission (AE) signals that can
be detected. With proper analysis, these AE signals can dynamically
identify failure processes. However, conventional AE methods with the
use of event counts, event energy, signal amplitude, duration and rise
time, etc. have severe limitation in the characterization of AE
sources. For fatigue detection and for failure mechanism study in
composite materials, advanced characterization methods are needed. By
using sensor output waveforms, identifying unknown signals and
evaluating their significance, and correlating identified signals to
the failure modes, the advanced methods permit quantitative
interpretations based on signal feature analysis and identify the
nature of emission sources. The techniques of pattern recognition are
used to classify unknown signals into groups, which are related to
specific signal characteristics. |
Key Words
|
acoustic emission; mechanical
behavior; nondestructive evaluation; NDE; structural materials; fiber
reinforced composites; pattern recognition analysis.
|
|
|