Reference : Analysis versus synthesis for trending of gas-path measurement time series
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/170131
Analysis versus synthesis for trending of gas-path measurement time series
English
Borguet, Sébastien mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]
Léonard, Olivier mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]
Dewallef, Pierre mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Systèmes de conversion d'énergie pour un dévelop.durable >]
Jun-2014
Proceedings of ASME Turbo Expo 2014
GT2014-26029
Yes
No
International
ASME Turbo Expo 2014
16-20 juin 2014
American Society of Mechanical Engineers
Düsseldorf
Germany
[en] time series filtering ; quadratic programming ; gas-path analysis
[en] Gas-path measurements used to assess the health condition of an engine are corrupted by noise.
Generally, a data cleaning step occurs before proceeding with fault detection and isolation.
Classical linear filters such as the exponentially weighted moving average filter are traditionally
used for noise removal. Unfortunately, these low-pass filters distort trend shifts indicative
of faults, which increases the detection delay.

The present paper investigates two new approaches to non-linear filtering of time series. On one hand, the synthesis approach reconstructs the signal as a combination of elementary signals chosen from a pre-defined library. On the other hand, the analysis approach imposes a constraint on the shape of the signal (e.g., piecewise constant). Both approaches incorporate prior information about the signal in a different way, but they lead to trend filters that are very capable at noise removal while preserving at the same time sharp edges in the signal. This is highlighted through the comparison with a classical linear filter on a batch of synthetic data representative of typical engine fault profiles.
Researchers ; Professionals
http://hdl.handle.net/2268/170131
Copyright 2014 by ASME

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