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The method of a black-box diagnostics, founded on nonparametric identification of objects using integro-power Volterra series is offered. It provides a set of diagnostic features formed on base of multidimensional Volterra kernels: discrete values of Volterra kernels, heuristic features, moments and wavelet transform coefficients. It is researched a self-descriptiveness of provided features using classifier on base of neural nets. The diagnostic spaces are formed by method of all features combination selection.