When sensors malfunction, control systems become unreliable. Even with the most
sophisticated instruments and control algorithms, a control decision based on faulty data will …

Periodic manual calibrations ensure that an instrument will operate correctly for a given
period of time, but they do not assure that a faulty instrument will remain calibrated for other …

The new approach for sensor diagnostics is presented. The approach, Enhanced
Autoassociative Neural Networks (E-AANN), adds enhancement to Autoassociative Neural …

We address the problem of sensor fault diagnosis in complex systems. The motivation for
this work is the common problem encountered in industrial setting, ie sensor shift, drift and …

The topology and property of Autoassociative Neural Networks (AANN) and the AANN's
application to sensor fault diagnosis and reconstruction of engine control system are …

Sensor validation is an essential task in the operation of an aircraft engine. Faulty sensor
readings can lead to undesirable situations, such as dispatch delays, degraded engine …

Continuous operations can result in performance degradation of industrial systems, which
naturally increases complexity in fault detection (FD). In this study, a transfer learning …

This paper considers the problem of inhibiting smearing effects for multiple sensor fault
isolation. Although the reconstruction-based approach has received considerable attention …

An unappealing characteristic of all real-world systems is the fact that they are vulnerable to
faults, malfunctions and, more generally, unexpected modes of-haviour. This explains why …

This work is aimed towards the development of an artificially intelligent search algorithm
used in conjunction with an Auto Associative Neural Network (AANN) to help locate and …