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- W2365338557 abstract "To avoid problems brought about by fitting length and straight-line fitting means in the conventional method of Hurst Exponent estimated,refinements based on improving scale length and sub-fitting method were proposed.Scale length was selected using the index of two,and curves of rescaled range sequence were divided into four sections.Then the appropriate curves were selected to fit,and linear slope got from the result is the estimated Hurst exponent value.By numerical simulation researchers verify that the method is of estimated accuracy than conventional Hurst Exponent estimation methods.This paper analyzes the effectiveness of Hurst exponent and approximate entropy from acoustic emission signals as characteristic parameters of the occurrence and intensity of rubbing.The experiment uses the Hurst exponent and approximate entropy extracted from the rub impact acoustic emission(AE) signals under different conditions obtained from a rotating test stand in a separate and combined form as the input of BP neural network to identify the different status of rubbing.The results of the experiment show that the method combining Hurst Exponent and Approximate Entropy is of higher recognizable accuracy.This paper provides a new approach for the identification of rotating machinery rubbing fault." @default.
- W2365338557 created "2016-06-24" @default.
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- W2365338557 date "2010-01-01" @default.
- W2365338557 modified "2023-09-23" @default.
- W2365338557 title "Identification of Rotating Machinery Rub and Impact Fault Using Hurst Exponent and Approximate Entropy as Characteristic Parameters of Acoustic Emission" @default.
- W2365338557 hasPublicationYear "2010" @default.
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