A Survey of Data-Driven Prognostics

*Integrated Systems Health Management includes fault detection, fault diagnosis (or fault isolation), and fault prognosis. We define prognosis to be detecting the precursors of a failure, and predicting how much time remains before a likely failure. Algorithms that use the data -driven approach to prognosis learn models directly from the data, rather than u sing a hand -built model based o n human experti se. This paper surveys past work in the data driven approach to prognosis. It also includes related work in data -driven fault detection and diagnosis, and in model -based diagnosis and prognosis, particularly as applied to space systems.