Vol. 6 No. 4 (2015): IJPHM Special Issue on Uncertainty in PHM

The International Journal of Prognostics and Health Management (IJPHM) is the premier online open access journal related to multidisciplinary research on Prognostics, Diagnostics, and System Health Management. This special issue focuses on computational methods and practical applications dealing with the representation, interpretation, quantification, and management of uncertainty in prognostics and health management.

Prognostics, the science of prediction, is inherently affected by several sources of uncertainty (natural variability, data uncertainty, and model uncertainty). It is important to rigorously account for these sources of uncertainty while predicting the behavior of engineering systems, and compute the overall uncertainty in the remaining useful life prediction. Uncertainties that exhibit complex, non-linear interactions need to be aggregated using computational methods. If there is a large uncertainty associated with the remaining useful life prediction, then such information may not be useful for meaningful decision-making. Therefore, recent research efforts have focused on developing methods to characterize, interpret, incorporate, and quantify uncertainty in prognostics, quantify the risk associated with system operation decisions, and eventually facilitate risk-informed decision-making activities such as fault mitigation, mission re-planning, etc.

Published: 2015-12-02

Technical Papers

Uncertainty in PHM

Shankar Sankararaman, Sankaran Mahadevan, Marcos E. Orchard
Abstract 75 | PDF Downloads 89 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2289

Probabilistic Prognosis with Dynamic Bayesian Networks

Gregory Bartram, Sankaran Mahadevan
Abstract 60 | PDF Downloads 90 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2290

Uncertainty in Prognostics and Systems Health Management

Shankar Sankararaman, Kai Goebel
Abstract 117 | PDF Downloads 140 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2319

Impact of Prognostic Uncertainty in System Health Monitoring

Robert M. Vandawaker, David R. Jacques, Jason K. Freels
Abstract 180 | PDF Downloads 10076 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2320

Hybrid Particle Petri Nets for Systems Health Monitoring under Uncertainty

Quentin Gaudel, Elodie Chanthery, Pauline Ribot
Abstract 73 | PDF Downloads 72 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2323