514 / 2019-01-02 22:07:46

Research on Condenser Fault Diagnosis Based on EMD and SVD

steam turbine; condenser; empirical mode decomposition; singular value decomposition; fault diagnosis

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The working process and failure mechanism of the condenser are analyzed, and the set of typical fault set, symptom set and typical fault feature vector set are established. EMD (Mode Decomposition Empirical) and singular value decomposition using empirical mode decomposition (SVD)(Value Decomposition Singular) a fault diagnosis model is established, and the validity of the model is proved by an example. At the same time, compared with the neural network method, it is found that, in the case of small samples, the EMD and SVD methods are better than the neural network, and the generalization ability is stronger, and the efficiency is higher than that of the neural network. This method provides a new way for the establishment of intelligent equipment condition monitoring and fault diagnosis, and it has a wide range of practical value for the establishment of intelligent equipment condition monitoring and fault diagnosis.