Fault detection for aircraft piston engine using self-organizing map

Aircraft piston engine can be monitored using an advanced graphic engine monitor. Such engine monitor can supply a large amount of data containing evolution of engine parameters through the time. Analysis of a vast amount of multidimensional temporal data by a self-organizing map may aid in data visualization, but also in detection of engine parameter deviations from normality indicating potential problems in operation of aircraft piston engine. For determination of engine parameter space that corresponds to normal engine operation quantization error of the self-organizing map is used.

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