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2009 International Joint Conference on Artificial Intelligence
Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis
Hainan Island, China
April 25-April 26
ISBN: 978-0-7695-3615-6
| ASCII Text | x | ||
| Shufeng Ai, Hui Li, Lihui Fu, "Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis," Artificial Intelligence, International Joint Conference on, pp. 659-662, 2009 International Joint Conference on Artificial Intelligence, 2009. | |||
| BibTex | x | ||
| @article{ 10.1109/JCAI.2009.10, author = {Shufeng Ai and Hui Li and Lihui Fu}, title = {Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis}, journal ={Artificial Intelligence, International Joint Conference on}, volume = {0}, year = {2009}, isbn = {978-0-7695-3615-6}, pages = {659-662}, doi = {http://doi.ieeecomputersociety.org/10.1109/JCAI.2009.10}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Artificial Intelligence, International Joint Conference on TI - Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis SN - 978-0-7695-3615-6 SP659 EP662 A1 - Shufeng Ai, A1 - Hui Li, A1 - Lihui Fu, PY - 2009 KW - fault diagnosis;gear; vibration; angle domain average; autoregressive spectrum VL - 0 JA - Artificial Intelligence, International Joint Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/JCAI.2009.10
In order to process the non-stationary vibration signals during run-up of gearbox, the method based on angle domain average and autoregressive spectrum analysis is presented. This new method combines angle domain average with angle domain average technique. Firstly, the vibration signal is sampled at constant time increments and then uses software to resample the data at constant angle increments.Secondly, the angle domain signal is preprocessed using angle domain average technique in order to eliminate the unrelated noise. In the end, the averaged signals are processed by autoregressive spectrum analysis. The experimental results show that the proposed method can effectively detect the gear crack faults.
Index Terms:
fault diagnosis;gear; vibration; angle domain average; autoregressive spectrum
Citation:
Shufeng Ai, Hui Li, Lihui Fu, "Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis," jcai, pp.659-662, 2009 International Joint Conference on Artificial Intelligence, 2009
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