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2019 | OriginalPaper | Buchkapitel

The Time-Frequency Filtering (TFF) Method Used in Early Detection of Gear Faults in Variable Load and Dimensions Defect

verfasst von : Hafida Mahgoun, Fakher Chaari, Ahmed Felkaoui, Mohamed Haddar

Erschienen in: Rotating Machinery and Signal Processing

Verlag: Springer International Publishing

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Abstract

In stationary condition, a local gear fault is presented by periodic impulses. However, under variable load, the vibration signal is non-stationary and the periodic impulses are masked by the noise and the part of the signal due to the load. The use directly of the time-frequency methods doesn’t allow detecting these impulses. In this study, we propose to use two different time-frequency methods, ensemble empirical mode decomposition (EEMD) and time-frequency filtering (TFF) to analyze the vibration signal. First, the EEMD method is used to decompose the vibration signals in many modes. Then each mode is filtered and denoised by using the TFF method. In this paper, we propose to compare the results given by using the two methods separately and the results when we combine the two methods.

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Vorheriges Kapitel Bearing Diagnostics Using Time-Frequency Filtering and EEMD

Nächstes Kapitel Comparison Between Hidden Markov Models and Artificial Neural Networks in the Classification of Bearing Defects

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Titel: The Time-Frequency Filtering (TFF) Method Used in Early Detection of Gear Faults in Variable Load and Dimensions Defect
verfasst von: Hafida Mahgoun
Fakher Chaari
Ahmed Felkaoui
Mohamed Haddar
Verlag: Springer International Publishing
Buch: Rotating Machinery and Signal Processing
Print ISBN: 978-3-319-96180-4

Electronic ISBN: 978-3-319-96181-1

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-319-96181-1_5

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