  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.
