Non-destructive testing of aerospace structures: granularity and data mining approach

Author

Osegueda, R. ; Kreinovich, Vladik ; Potluri, Lakshmi ; Aló, Richard

Author_Institution

FAST Center, Texas Univ., El Paso, TX, USA

Volume

1

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

685

Lastpage

689

Abstract

For large aerospace structures, it is extremely important to detect faults, and nondestructive testing is the only practical way to do it. Based on measurements of ultrasonic waves, Eddy currents, magnetic resonance, etc., we reconstruct the locations of the faults. The best (most efficient) known statistical methods for fault reconstruction are not perfect. We show that the use of expert knowledge-based granulation improves the quality of fault reconstruction

Keywords

aerospace testing; computational complexity; data mining; eddy current testing; expert systems; fault diagnosis; nondestructive testing; probability; statistical analysis; ultrasonic materials testing; Eddy currents; data mining; expert knowledge-based granulation; fault reconstruction; faults detection; granularity; large aerospace structures; magnetic resonance; nondestructive testing; ultrasonic waves; Aerospace testing; Current measurement; Data mining; Eddy currents; Fault detection; Magnetic resonance; Measurement standards; Nondestructive testing; Statistical analysis; Ultrasonic variables measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7280-8

Type

conf

DOI

10.1109/FUZZ.2002.1005075

Filename

1005075