The paper describes the application of artificial nervous network models with self organizing characteristic reflection in fault diagnosis of power plant systems. By comparison with conventional BP networks used for fault diagnosis of steam turbines, the following conclusion is drawn: self organizing models possess self studying capability, are quick in performing calculations and are strong in type discrimination. They have prospects of general application.
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