Application of Neural Networks in Fault Diagnosis of Rotating Machinery

The fault diagnosis method based on artificial neural networks is summarized. An object-oriented paradigm is introduced to fault diagnosis for large scale rotating machinery, for example, turbine-generator. A fault diagnosis method based on object-oriented artificial neural networks for more symptom domains is presented. The training patterns are constructed. A treatment for incomplete symptom domains and/or concurrent faults in diagnosing is given. Verification is carried out for the actual turbine-generator data with incomplete symptom domains.