FIELD: computer engineering.
SUBSTANCE: method for diagnosing a system of on-board equipment of aircraft based on machine learning, comprising steps of collecting and preparing initial data, transmitted information data are determined, a developed neural network filter based on multilayer perceptrons is applied, a method of reducing marked data samples is applied, K-means, SOM and DBSCAN machine learning models are created, model training parameters are assigned, models are trained on the data according to the criteria for obtaining one cluster, which characterizes the sound state of each information conversion channel, based on the obtained DTA-10 values and the input and obtained output signals from the IM-47 of the electronic engine controller of the ERD-3VM series are fixed.
EFFECT: higher accuracy of diagnostics of aircraft on-board equipment data conversion elements (DCE) based on machine learning.
1 cl, 10 dwg
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