Fault Diagnosis of Hydroelectric Units Based on a Novel Multiscale Fractional-Order Weighted Permutation Entropy

Abstract

To improve the noise immunity, stability and sensitivity to different signal types in the hydroelectric unit fault diagnosis model, a hydroelectric unit fault diagnosis model based on improved multiscale fractional-order weighted permutation entropy (IMFWPE) is proposed. Firstly, the fractional order and weighting theory is introduced into the permutation entropy (PE) to improve the sensitivity to different fault signals while improving the defect of ignoring the signal amplitude information. Additionally, considering the problem that a single scale cannot fully reflect the timing characteristics and that the traditional coarse-grained method will shorten the timing length, a new tool for measuring the complexity of timing signals, IMFWPE, is proposed by introducing an improved multiscale method. Finally, the IMFWPE values of signals are extracted as features and input to the classifier for fault identification of hydroelectric units. The experimental results show that the proposed method has the best diagnostic effect when compared with other methods, has good noise immunity and stability, and has good diagnostic capability in the actual unit environment.