Open Access
December 2015 The latent state hazard model, with application to wind turbine reliability
Ramin Moghaddass, Cynthia Rudin
Ann. Appl. Stat. 9(4): 1823-1863 (December 2015). DOI: 10.1214/15-AOAS859


We present a new model for reliability analysis that is able to distinguish the latent internal vulnerability state of the equipment from the vulnerability caused by temporary external sources. Consider a wind farm where each turbine is running under the external effects of temperature, wind speed and direction, etc. The turbine might fail because of the external effects of a spike in temperature. If it does not fail during the temperature spike, it could still fail due to internal degradation, and the spike could cause (or be an indication of) this degradation. The ability to identify the underlying latent state can help better understand the effects of external sources and thus lead to more robust decision-making. We present an experimental study using SCADA sensor measurements from wind turbines in Italy.


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Ramin Moghaddass. Cynthia Rudin. "The latent state hazard model, with application to wind turbine reliability." Ann. Appl. Stat. 9 (4) 1823 - 1863, December 2015.


Received: 1 September 2014; Revised: 1 July 2015; Published: December 2015
First available in Project Euclid: 28 January 2016

zbMATH: 06560811
MathSciNet: MR3456355
Digital Object Identifier: 10.1214/15-AOAS859

Keywords: big data , decision-making , maintenance , Performance monitoring , reliability

Rights: Copyright © 2015 Institute of Mathematical Statistics

Vol.9 • No. 4 • December 2015
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