Abstract

In this work, the problem of diagnostic models constructing under conditions of description dimension increase in the modern diagnostic objectssolves. As a diagnostic objects considers the nonlinear dynamics objects with continuous characteristicsand an unknown structure, which can be considered as a “black box”. The purposeof the work is to increase the reliability of the diagnosis of nonlinear dynamic objects by forming diagnostic models under conditionsof the objects description dimensionality increasing. A review of methods for reducing the dimensionality of the diagnostic features space is given. A method for the constructionof diagnostic models of nonlinear dynamic objects with weak nonlinearity on the basis of univariate and multivariate analysis of variance as a filtering stage of signs is proposed. A step-by-step algorithm for the constructionof diagnostic models using the proposed method is presented. On the example of the task of technical diagnosis a jet engine, diagnostic models are constructed on the basis of univariateand multivariate analysis of variance of continuous models. A family of diagnostic models of a jet engine is proposed.

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