  In-flight sensor fault diagnosis and recursive combination of residual
signals via the Dempster-Shafer (DS) theory have been considered in this study.
In particular, a novel evidence-based combination rule of residual errors as a
function of a reliability measure derived from streaming data is proposed for
the purpose of online robust sensors fault diagnosis. The proposed information
fusion mechanism is divided into three steps. In the first step, the classic DS
probability mass combination rule is applied; then, the difference between the
previous posterior mass and the current prior mass associated with fault events
is computed. Finally, the increment of the posterior mass of a fault event is
weighted as a function of a reliability coefficient that depends on the norm of
control activity. A Sensor Fault Isolation scheme based on the proposed
combination rule has been worked out and compared with well-known
state-of-the-art recursive combination rules. A quantitative analysis has been
performed exploiting multi-flight data of a P92 Tecnam aircraft. The proposed
approach showed to be effective, particularly in reducing the false alarms
rate.
