Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection
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- 作者：Gang Lia ; gl2@ualberta.ca" class="auth_mail" title="E-mail the corresponding author ; Geoff L. McDonaldb ; glmcdona@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Qing Zhaoa ; qingz@ualberta.ca" class="auth_mail" title="E-mail the corresponding author
- 关键词：Sinusoidal synthesis ; Time series modeling ; Adaptive ; Vibration signal ; Fault detection
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：15 January 2017
- 年：2017
- 卷：83
- 期：Complete
- 页码：356-370
- 全文大小：1583 K
文摘
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This proposed SSBAT model can predict and trend vibration signals.
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It is a dynamic adaptive model incorporating sinusoidal constraints.
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The rotating speed is assumed to be unknown, leading to unknown model parameters.
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The unknown model parameters are estimated using a modified least-squares algorithm.
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It is suitable for on-line rotating machinery impact fault detection.