Surface roughness monitoring by singular spectrum analysis of vibration signals
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- 作者：E. Garcí ; a Plaza ; eustaquio.garcia@uclm.es" class="auth_mail" title="E-mail the corresponding author ; P.J. Nú ; ñ ; ez Ló ; pez pedro.nunez@uclm.es" class="auth_mail" title="E-mail the corresponding author
- 关键词：Singular spectrum analysis (SSA) ; Vibrations signals ; Surface roughness monitoring ; CNC turning
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：1 February 2017
- 年：2017
- 卷：84
- 期：part_PA
- 页码：516-530
- 全文大小：1214 K
文摘
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Optimum prediction results were obtained for a window length L=10 (effective L=5).
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Feed acceleration ay was the primary data source in the monitoring of roughness.
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I-SSA and G-SSA methodologies provided excellent reliability and predictive power.
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G-SSA method is the most efficient method for monitoring surface roughness (Ra).
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SSA method permitted the grouping of effective principal components in monitoring.