感应式油屑检测混叠误差的分析评价

W. Hong, Honggang Li, D. Tan, H. Yin, Li Liu, Yanzheng Bai
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引用次数: 0

摘要

油屑监测是机械故障诊断和寿命预测的重要技术。然而,多个碎片一起通过电感式碎片传感器产生的混叠误差是难以避免的。针对这一问题,本文采用分段函数描述碎片混叠行为,并讨论了不同碎片大小和间隔下的最大混叠误差。在此基础上,提出了一种优化的检测策略,以减小混叠误差。最后,基于正弦波形的仿真验证了所提方法的有效性。结果表明,该方法可以在不同情况下进行策略切换,并具有最佳的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytical Evaluating for Aliasing Error of Inductive Oil Debris Detection
Oil debris monitoring is an important technique for mechanical fault diagnosis and life prediction. However, the aliasing error which comes from multiple debris through an inductive debris sensor together is difficult to be avoided. Aiming to this problem, this paper uses a segmented function to describe the behavior of debris aliasing and discusses maximum aliasing error under different debris sizes and spacings. On this basis, an optimized detection strategy is developed to reduce aliasing error. Finally, the simulation based Sine waveform is performed to validate the proposed method. The result indicates the proposed method can switch between the several strategies in different situations that it has the best performance among them.
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