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Monitoring Scheme of a Ship Synchronous Generator Excitation System Based on Gaussian Process Latent Variables

Electricity related system has strong nonlinearity and periodicity and therefore is difficult to build data-driven models. Under the frame of Bayesian theory, Gaussian Process Latent Variable (GPLV) model is a suitable tool to model systems with such properties. With internal kernels and probabilistic features, complex data relationships can be preserved and explored. This paper attempts to construct a statistical model for a ship synchronous generator excitation system. With the proposed approach, normal load and three phase short circuit situations can be detected and differentiated successfully.