Title :
Missing sensor data restoration for vibration sensors on a jet aircraft engine
Author :
Narayanan, Sreeram ; Vian, J.L. ; Choi, J.J. ; Mark, R.J. ; El-Sharkaw, M.A. ; Thompson, Benjamin B.
Author_Institution :
Boeing Phantom Works, Boeing Co., Seattle, WA, USA
Abstract :
Using array historical data, the readings from a sensor array may be shown to contain sufficient redundancy such that the readings from one or more lost sensors may be able to be accurately estimated from those remaining. This interdependency can be established by an neural network encoder. The encoder is also used in the restoration process. In this paper, we give some examples of sensor restoration for vibration sensors on jet engine and computer traffic data.
Keywords :
aircraft computers; encoding; jet engines; neural nets; vibration measurement; auto-associative regression machine; computer traffic data; jet aircraft engine; missing sensor data restoration; neural network encoder; vibration sensors; Aircraft propulsion; Computational intelligence; Frequency response; Imaging phantoms; Intelligent sensors; Jet engines; Neural networks; Sensor arrays; Testing; Vibration measurement;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1224050
