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      The latent state hazard model, with application to wind turbine reliability

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          Abstract

          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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          Journal
          2016-01-29
          Article
          10.1214/15-AOAS859
          1601.08034
          f1f6fb85-78e8-45c2-8fda-fad95ae1f2ac

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          IMS-AOAS-AOAS859
          Annals of Applied Statistics 2015, Vol. 9, No. 4, 1823-1863
          Published at http://dx.doi.org/10.1214/15-AOAS859 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
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