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- W2390202229 abstract "A method of the fault detection and diagnosis by combining correlation filter and Shannon information entropy was proposed. The method was called wavelet correlation feature scale entropy-fault.At first,the weak fault information features were picked up from roller bearings fault vibration signals by the way of transform correlation filter,in order to get high signal to noise scales coefficients.Then,the defining and computing way of correlation feature scale entropy was presented, based on the integration of shannon information entropy theory.Wavelet correlation feature scale entropy can quantitatively describe energy distributing of different scales which reflects difference of roller bearings running state,the work states and fault types were estimated by magnitude of the selected correlation feature scale entropy which can mostly embody fault features.Results and analysis of the diagnosing example reveal that the proposed method can effectively estimate roller bearings fault feature and offer one new way for diagnosing roller bearings." @default.
- W2390202229 created "2016-06-24" @default.
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- W2390202229 date "2007-01-01" @default.
- W2390202229 modified "2023-09-23" @default.
- W2390202229 title "Application of Wavelet Correlation Feature Scale Entropy to Fault Diagnosis of Roller Bearings" @default.
- W2390202229 hasPublicationYear "2007" @default.
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