International Journal of Prognostics and Health Management (Jun 2017)

A Generic Software Architecture for Prognostics (GSAP)

  • Christopher Teubert,
  • Matthew J. Daigle,
  • Shankar Sankararaman,
  • Kai Goebel,
  • Jason Watkins

DOI
https://doi.org/10.36001/ijphm.2017.v8i2.2618
Journal volume & issue
Vol. 8, no. 2

Abstract

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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 large hurdle in developing the models, algorithms, architecture, and integration pieces. Similarly, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use.

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