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Fault diagnosis of bladed disc using wavelet transform and ensemble empirical mode decomposition
Blade faults are considered as the most common cause of failure in turbomachines. Any fault occurs in impeller's blades gives the breakdown in these machines and creates undesired vibration. This paper presents a new method which combines wavelet transform (WT) with ensemble empirical mode deco...
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Published in: | Australian journal of mechanical engineering 2020-07, Vol.18 (sup1), p.S165-S175 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Blade faults are considered as the most common cause of failure in turbomachines. Any fault occurs in impeller's blades gives the breakdown in these machines and creates undesired vibration. This paper presents a new method which combines wavelet transform (WT) with ensemble empirical mode decomposition (EEMD) method for early identification of blade state. The vibration signals measured from a blade rotor are filtered using the WT, and then the obtained signals are decomposed into intrinsic mode functions (IMFs) by EEMD method to obtain multichannel signals. The correlation coefficient is used as an index to select the effective IMFs. The selected IMFs are then reconstituted and its spectrum is generated. Experimental results validate the usefulness of the proposed method for detecting the blade faults. |
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ISSN: | 1448-4846 2204-2253 |
DOI: | 10.1080/14484846.2018.1499471 |