TY - GEN
T1 - PROGNOSTIC TOOLS FOR SMALL CRACKS IN STRUCTURES
AU - McDowell, D. L.
AU - Neu, R. W.
AU - Qu, J.
AU - Saxena, A.
N1 - Publisher Copyright:
© 1997 American Society of Mechanical Engineers (ASME). All rights reserved.
PY - 1997
Y1 - 1997
N2 - An integrated system for diagnosis of the “health” of a structural component subjected to high cycle fatigue (HCF) consists of sets of embedded or emplaced sensors at various locations, extracting information related to generation of material defects, presence of crack-like discontinuities and their progression, and changes of system dynamics which may relate to this progression. Conceptually, signals from these sensors are fed into a processing environment that can ascertain deleterious conditions related to the onset of loss of function or propagation of cracks to critical dimensions. Since the idea is to monitor the gradual changes of component performance and various local related indices before catastrophic failure to enable the operator to respond with a maintenance hold, it is essential to couple the diagnostics with prognostic capability; this facilitates a prediction of how much time remains within the window of viable servicing or repair. In the HCF regime, the dominant fraction of total fatigue life may be spent at crack lengths on the order of 20 to 500 pm. The detection of longer cracks near the end of component life is critical since component failure may lead to failure of the overall structure. This necessitates the identification of (i) finite-element algorithms for identifying component “hot spots” where failure is likely to occur, (ii) development of appropriate crack growth laws for cracks of different length scales, ranging from on the order of grain size to on the order of component dimensions, including consideration of contacting components (fretting ratigue) and environmental effects, and (iii) development of algorithms for identifying the progression of component degradation based on multiple sensor inputs at different time and length scales, providing feedback to support cause for maintenance shutdown. This paper discusses related work underway in the Structural Fatigue Task within a Department of Defense University Research Initiative (M-URI) on Integrated Diagnostics at Georgia Tech, monitored by the Office of Naval Research.
AB - An integrated system for diagnosis of the “health” of a structural component subjected to high cycle fatigue (HCF) consists of sets of embedded or emplaced sensors at various locations, extracting information related to generation of material defects, presence of crack-like discontinuities and their progression, and changes of system dynamics which may relate to this progression. Conceptually, signals from these sensors are fed into a processing environment that can ascertain deleterious conditions related to the onset of loss of function or propagation of cracks to critical dimensions. Since the idea is to monitor the gradual changes of component performance and various local related indices before catastrophic failure to enable the operator to respond with a maintenance hold, it is essential to couple the diagnostics with prognostic capability; this facilitates a prediction of how much time remains within the window of viable servicing or repair. In the HCF regime, the dominant fraction of total fatigue life may be spent at crack lengths on the order of 20 to 500 pm. The detection of longer cracks near the end of component life is critical since component failure may lead to failure of the overall structure. This necessitates the identification of (i) finite-element algorithms for identifying component “hot spots” where failure is likely to occur, (ii) development of appropriate crack growth laws for cracks of different length scales, ranging from on the order of grain size to on the order of component dimensions, including consideration of contacting components (fretting ratigue) and environmental effects, and (iii) development of algorithms for identifying the progression of component degradation based on multiple sensor inputs at different time and length scales, providing feedback to support cause for maintenance shutdown. This paper discusses related work underway in the Structural Fatigue Task within a Department of Defense University Research Initiative (M-URI) on Integrated Diagnostics at Georgia Tech, monitored by the Office of Naval Research.
UR - http://www.scopus.com/inward/record.url?scp=85210846329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85210846329&partnerID=8YFLogxK
U2 - 10.1115/IMECE1997-1264
DO - 10.1115/IMECE1997-1264
M3 - Conference contribution
AN - SCOPUS:85210846329
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
SP - 1
EP - 12
BT - Emerging Technologies for Machinery Health Monitoring and Prognosis
T2 - ASME 1997 International Mechanical Engineering Congress and Exposition, IMECE 1997
Y2 - 16 November 1997 through 21 November 1997
ER -