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5 Oct 2021
On October 5, 2021, a business meeting was held between representatives of the EPAM Systems IT Company Denis Grinev and Sergey Garashchuk with the Rector of the State University “Odessa Polytechnic” Gennadii Alexandrovich Oborskiy
17 Sept 2021
International Summer School
15 July 2021
Until November 1, 2021, enrollment in the double degree program of Slovakia 2ouble Degree is carried out.
CONSTRUCTION OF THE DIAGNOSTIC MODEL BASED ON COMBINING SPECTRAL CHARACTERISTICS OF NONLINEAR DYNAMIC OBJECTS
The task of constructing diagnostic models for nonlinear dynamics objects solved in this work. The reasons for increasing the dimension of the modern diagnostics objects description and related problems of using existing diagnostics methods are considered. The purpose of this work is to increase the accuracy and reliability of nonlinear dynamic objects diagnosing by forming diagnostic models in the conditions of increasing the dimension of the objects description for creating effective tools for automated systems of technical diagnostics. It is offered a broad overview and classification of methods for reducing the dimension space of diagnostic features including nonlinear dynamic objects with continuous characteristics and unknown structure, which can be considered as a “black box”. The forming diagnostic models method of nonlinear dynamic objects based on the combination of spectral characteristics obtained as the result of continuous models transformations: wavelet transformations coefficients and models moments of different orders is proposed. The family of diagnostic models is proposed as combinations of dynamic objects spectral characteristics with weak nonlinearity. The hybrid method of forming diagnostic models based on the combination of spectral characteristics suggested. The method consist of sequential application of feature filtering for forming primary feature space, construction of secondary feature space using the spectral transformations and diagnostic model construction by complete bust of secondary features. It is developed a detailed algorithm for constructing diagnostic models using the proposed hybrid method. The suggested method has been tested on real-life task of diagnosing a non-linear dynamic object – a electric motor. Primary diagnostic model of the electric motor taken on the base of indirect measurements of the air gap between the rotor and the stator of the motor. Diagnostic models constructed by combining the spectral characteristics of continuous models. The diagnostic models family of the switched reluctance motor is offered. The method is demonstrate more independence of the accessibility indicator then existing methods of the diagnostic feature space biulding: the samples, the moment and the coefficients of wavelet transformations of the primary diagnostic models.
Hanna M. Fedorova
( firstname.lastname@example.org )
Oleksandr A. Fomin
, Dr. of Tech. Sciences, Associate Professor
( email@example.com )
Oleksandr D. Ruban
( firstname.lastname@example.org )
Vitaliy D. Pavlenko
, Dr. of Tech. Sciences, Professor
( email@example.com )
nonlinear dynamic objects; diagnostic models; model reduction; spectral transformations
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Received after revision 17.02.2020
Vol. 3 № 1, 2020
22 Oct 2021
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