Real-time health monitoring of a thin composite beam using a passive Structural Neural System

被引：0

作者：

Kirikera, G. R. ^{[1
]}

Shinde, V. ^{[1
]}

Schulz, M. J. ^{[1
]}

Ghoshal, A. ^{[1
]}

Sundaresan, M. J. ^{[1
]}

Lee, J. W. ^{[1
]}

机构：

[1] Univ Cincinnati, Dept Mech Engn, Smart Mat Nanotechnol Lab, Cincinnati, OH 45221 USA

来源：

HEALTH MONITORING AND SMART NONDESTRUCTIVE EVALUATION OF STRUCTURAL AND BIOLOGICAL SYSTEMS V | 2006年 / 6177卷

关键词：

Structural Neural System (SNS); acoustic emission (AE); structural health monitoring (SHM);

D O I：

10.1117/12.658674

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A small size prototype of a Structural Neural System (SNS) was tested in real time for damage detection in a laboratory setting and the results are presented in this paper. The SNS is a passive online structural health monitoring (SHM) system that can detect small propagating damages in real time before the overall failure of the structure is realized. The passive SHM method is based on the concept of detecting acoustic emissions (AE) due to damage propagating. Propagating cracks were identified near the vicinity of a sensor in a composite specimen during fatigue testing. In the composite specimen, in additions to a propagating crack, fretting occurred because of slipping contact between the load points and the composite specimen. The SNS was able to predict the location of damage due to crack propagation and also detect signals from fretting simultaneously in real time.

引用

页数：12

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