Engine health monitoring has been an area of intensive research for many years. Numerous methods have been developed with the goal of determining a faithful picture of the engine condition. On the other hand, the issue of sensor selection allowing an efficient diagnosis has received less attention from the community. The present contribution revisits the problem of sensor selection for engine performance monitoring within the scope of information theory. To this end, a metric that integrates the essential elements of the sensor selection problem is defined from the Fisher information matrix. The FIM quantifies the amount of information that an observation carries about an unknown parameter. Mathematically, the FIM is defined as the variance of the score function associated to the estimation problem. An example application consisting in a commercial turbofan engine illustrates the enhancement that can be expected from a wise selection of the sensor set.
The Fisher information matrix as a relevant tool for sensor selection in engine health monitoring
Fisher-Informationsmatrix als relevante Sensorauswahlhilfe zur Motorzustandsüberwachung
2008
10 Seiten, 4 Bilder, 9 Tabellen, 22 Quellen
Aufsatz (Zeitschrift)
Englisch
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