TY - GEN
T1 - Application challenges
T2 - 15 Workshops Held in Conjunction with the IEEE International Parallel and Distributed Processing Symposium, IPDPS 2000
AU - Hadden, George D.
AU - Bergstrom, Peter
AU - Samad, Tariq
AU - Bennett, Bonnie Holte
AU - Vachtsevanos, George J.
AU - Van Dyke, Joe
PY - 2000
Y1 - 2000
N2 - System Health Management (SHM) is an example of the types of challenging applications facing embedding high-performance computing environments. SHM systems monitor real-time sensors to determine system health and performance. Performance, economics, and safety are all at stake in SHM, and the emphasis on health management technology is motivated by all these considerations. This paper describes a project focusing on condition-based maintenance (CBM) for naval ships. Condition-based maintenance refers to the identification of maintenance needs based on current operational conditions. In this project, system architectures and diagnostic and prognostic algorithms are being developed that can efficiently undertake real-time data analysis from appropriately instrumented machinery aboard naval ships and, based on the analysis, provide feedback to human users regarding the state of the machinery - such as its expected time to failure, the criticality of the equipment for current operation.
AB - System Health Management (SHM) is an example of the types of challenging applications facing embedding high-performance computing environments. SHM systems monitor real-time sensors to determine system health and performance. Performance, economics, and safety are all at stake in SHM, and the emphasis on health management technology is motivated by all these considerations. This paper describes a project focusing on condition-based maintenance (CBM) for naval ships. Condition-based maintenance refers to the identification of maintenance needs based on current operational conditions. In this project, system architectures and diagnostic and prognostic algorithms are being developed that can efficiently undertake real-time data analysis from appropriately instrumented machinery aboard naval ships and, based on the analysis, provide feedback to human users regarding the state of the machinery - such as its expected time to failure, the criticality of the equipment for current operation.
UR - http://www.scopus.com/inward/record.url?scp=0007927971&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0007927971&partnerID=8YFLogxK
U2 - 10.1007/3-540-45591-4_108
DO - 10.1007/3-540-45591-4_108
M3 - Conference contribution
AN - SCOPUS:0007927971
SN - 354067442X
SN - 9783540674429
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 784
EP - 791
BT - Parallel and Distributed Processing - 15 IPDPS 2000 Workshops, Proceedings
A2 - Rolim, Jose
PB - Springer Verlag
Y2 - 1 May 2000 through 5 May 2000
ER -