A Generic Software Architecture for Prognostics

Christopher Teubert, Matthew Daigle, Shankar Sankararaman, Kai Goebel, and Jason Watkins
Publication Target: 
IJPHM
Publication Issue: 
2
Submission Type: 
Full Paper
AttachmentSizeTimestamp
ijphm_17_013.pdf4.2 MBSeptember 25, 2017 - 11:39am

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.

Publication Year: 
2017
Publication Volume: 
8
Publication Control Number: 
013
Page Count: 
26
Submission Keywords: 
architecture
software
Generic prognostics methodology
software architecture
Battery discharge prognostics
Submission Topic Areas: 
Health management system design and engineering
Model-based methods for fault detection, diagnostics, and prognosis
Technology maturation
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