Oleksandr Fomin

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The paper presents an informational technology for improving the reliability of nonlinear dynamic objects fault diagnosing using model-based diagnostics method of nonparametric identification. Diagnostic models build on the base of Volterra kernels moments. The efficiency of the proposed diagnostic models analyzes on an nonlinear dynamic objects simulation(More)
The paper presents an informational technology for improving the reliability of nonlinear dynamic objects fault diagnosing using model-based diagnostics method of nonparametric identification. Diagnostic models build on the base of Volterra kernels moments. The efficiency of the proposed diagnostic models analyzes on an nonlinear dynamic objects simulation(More)
In this paper the problem of improving the reliability of nonlinear dynamic objects fault diagnosing is presented. Model-based diagnostics nonparametric identification method is used. Diagnostic models are constructed on the base of Volterra kernels wavelet transforms. The effectiveness of the suggested diagnostic models based on Volterra kernels wavelet(More)
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