MATEC Web Conf.
Volume 148, 2018International Conference on Engineering Vibration (ICoEV 2017)
|Number of page(s)||5|
|Section||Vibration-Based Structural Health Monitoring Data Analysis and Time Series Methods|
|Published online||02 February 2018|
- A. Sharma, M. Amarnath, and P. Kankar, “Feature extraction and fault severity classification in ball bearings,” Journal of Vibration and Control, vol. 22, pp. 176-192, (2016). [CrossRef] [Google Scholar]
- B. Nayana and P. Geethanjali, “Analysis of Statistical Time Domain Features Effectiveness in Identification of Bearing Faults from Vibration Signal,” IEEE Sensors Journal, (2017). [Google Scholar]
- H. Hassani, “Singular spectrum analysis: methodology and comparison,” (2007). [Google Scholar]
- H. Al-Bugharbee and I. Trendafilova, “A fault diagnosis methodology for rolling element bearings based on advanced signal pretreatment and autoregressive modelling,” Journal of Sound and Vibration, vol. 369, pp. 246-265, (2016). [CrossRef] [Google Scholar]
- H. R. Al-Bugharbee, “Data-driven methodologies for bearing vibration analysis and vibration based fault diagnosis,” PhD thesis, University of Strathclyde, 2016. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.