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pro vyhledávání: '"Matthew J. Daigle"'
Publikováno v:
International Journal of Prognostics and Health Management, Vol 8, Iss 2 (2017)
Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a
Externí odkaz:
https://doaj.org/article/29ec7f69e2564ea1a4c74079b9ca3184
Publikováno v:
International Journal of Prognostics and Health Management, Vol 8, Iss 1 (2017)
Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack
Externí odkaz:
https://doaj.org/article/7cbb8faba79441c5ae6c52beab140301
Autor:
Jose R. Celaya, Christopher Bond, Adam Sweet, Indranil Roychoudhury, Matthew J. Daigle, Sriram Narasimhan, Edward Balaban, George Gorospe
Publikováno v:
International Journal of Prognostics and Health Management, Vol 4, Iss 1, Pp 39-58 (2013)
As fault diagnosis and prognosis systems in aerospace applications become more capable, the ability to utilize information supplied by them becomes increasingly important. While certain types of vehicle health data can be effectively processed and ac
Externí odkaz:
https://doaj.org/article/856dc98372694f60ac62298397c87029
Autor:
Matthew J. Daigle, Kai Goebel
Publikováno v:
International Journal of Prognostics and Health Management, Vol 2, Iss 2, Pp 1-16 (2011)
Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physic
Externí odkaz:
https://doaj.org/article/1f70b976209447eda1fc7a0dd4c15059