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The fault harmonic series are synthesized to enhance fault features.
This is suitable for extracting the fault features.
Both simulation and experiments verify that the method could extract the fault features effectively.
This paper reports a new blind component separation (BCS) method for extracting different mechanical fault features.
The experimental results show remarkable improvements and enhance gear fault features.
Three feature extraction methods were utilized to seek for sensitive fault features.
Meanwhile, the enhanced empirical wavelet transform (EEWT) algorithm is applied to extract the bearing fault features.
The fewer, yet more sensitively detected, fault features significantly improves the accuracy of fault diagnosis.
Lastly, several different fault features are fused to illustrate the operating state of the machinery.
The results show that this method can effectively extract bearing fault features.
Section 2 analyzes and summarizes wind farm fault features and the research status on protection configuration.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com