Detection and Location of Structural Degradation in Mechanical Systems
Abstract
The investigation of a diagnostic method for detecting and locating the source of structural degradation in a mechanical system is described in this paper. The diagnostic method uses a mathematical model of the mechanical system to determine relationships between system parameters and measurable spectral features. These relationships are incorporated into a neural network, which associates measured spectral features with system parameters. Condition diagnosis is performed by presenting the neural network with measured spectral features and comparing the system parameters estimated by the neural network to previously estimated values. Changes in the estimated system parameters indicate the location and severity of degradation in the mechanical system.
- Authors:
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 7635
- Report Number(s):
- ORNL/CP-103230
ON: DE00007635
- DOE Contract Number:
- AC05-96OR22464
- Resource Type:
- Conference
- Resource Relation:
- Conference: GLOBAL 99, International Conference on Future Nuclear Systems, Jackson Hole, WY, August 30-September 2, 1999
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 22 NUCLEAR REACTOR TECHNOLOGY; Mechanical Structures; Damage; Mathematical Models; Neural Networks; Spectra
Citation Formats
Blakeman, E D, Damiano, B, and Phillips, L D. Detection and Location of Structural Degradation in Mechanical Systems. United States: N. p., 1999.
Web.
Blakeman, E D, Damiano, B, & Phillips, L D. Detection and Location of Structural Degradation in Mechanical Systems. United States.
Blakeman, E D, Damiano, B, and Phillips, L D. 1999.
"Detection and Location of Structural Degradation in Mechanical Systems". United States. https://www.osti.gov/servlets/purl/7635.
@article{osti_7635,
title = {Detection and Location of Structural Degradation in Mechanical Systems},
author = {Blakeman, E D and Damiano, B and Phillips, L D},
abstractNote = {The investigation of a diagnostic method for detecting and locating the source of structural degradation in a mechanical system is described in this paper. The diagnostic method uses a mathematical model of the mechanical system to determine relationships between system parameters and measurable spectral features. These relationships are incorporated into a neural network, which associates measured spectral features with system parameters. Condition diagnosis is performed by presenting the neural network with measured spectral features and comparing the system parameters estimated by the neural network to previously estimated values. Changes in the estimated system parameters indicate the location and severity of degradation in the mechanical system.},
doi = {},
url = {https://www.osti.gov/biblio/7635},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Aug 30 00:00:00 EDT 1999},
month = {Mon Aug 30 00:00:00 EDT 1999}
}