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المؤلفHemmati, Farzad
المؤلفAlqaradawi, Mohammed
المؤلفGadala, Mohamed S.
تاريخ الإتاحة2021-09-05T05:40:21Z
تاريخ النشر2016
اسم المنشورProceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology
المصدرScopus
الرقم المعياري الدولي للكتاب13506501
معرّف المصادر الموحدhttp://dx.doi.org/10.1177/1350650115591233
معرّف المصادر الموحدhttp://hdl.handle.net/10576/22738
الملخصAcoustic emission (AE) signal generated from defects in rolling element bearings are investigated using simulated defects and experimental measurements in this paper. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings comprises four main stages, which are, statistical analysis, faults diagnostics, defect size calculation, and prognostics. A modified and effective signal processing algorithm is designed to diagnose localized defects on rolling element bearing components under different operating speeds, loadings, and defect sizes. The algorithm is based on optimizing the ratio of Kurtosis and Shannon entropy to obtain the optimal band pass filter utilizing wavelet packet transform (WPT) and envelope detection. Results show the superiority of the developed algorithm and its effectiveness in extracting bearing characteristic frequencies from the raw acoustic emission signals masked by the background noise under different operating conditions. 2015 Institution of Mechanical Engineers.
راعي المشروعThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the Qatar National Research Fund (QNRF), Doha, Qatar.
اللغةen
الناشرSAGE Publications Ltd
الموضوعacoustic emission
de-noising
Signal processing
wavelet packet transform
العنوانRolling element bearing fault diagnostics using acoustic emission technique and advanced signal processing
النوعArticle
الصفحات64-77
رقم العدد1
رقم المجلد230
dc.accessType Abstract Only


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