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噪声作为 MEMS 质量和可靠性的诊断工具。

Noise as Diagnostic Tool for Quality and Reliability of MEMS.

机构信息

Queensland Micro- and Nanotechnology Centre, Griffith University, Nathan, QLD 4111, Australia.

Department of ECE, The George Washington University, Washington, DC 20052, USA.

出版信息

Sensors (Basel). 2021 Feb 22;21(4):1510. doi: 10.3390/s21041510.

Abstract

This perspective explores future research approaches on the use of noise characteristics of microelectromechanical systems (MEMS) devices as a diagnostic tool to assess their quality and reliability. Such a technique has been applied to electronic devices. In comparison to these, however, MEMS have much more diverse materials, structures, and transduction mechanisms. Correspondingly, we must deal with various types of noise sources and a means to separate their contributions. In this paper, we first provide an overview of reliability and noise in MEMS and then suggest a framework to link noise data of specific devices to their quality or reliability. After this, we analyze 13 classes of MEMS and recommend four that are most amenable to this approach. Finally, we propose a noise measurement system to separate the contribution of electrical and mechanical noise sources. Through this perspective, our hope is for current and future designers of MEMS to see the potential benefits of noise in their devices.

摘要

本文探讨了将微机电系统(MEMS)器件噪声特性用作评估其质量和可靠性的诊断工具的未来研究方法。这种技术已经应用于电子设备。然而,与这些设备相比,MEMS 具有更多样化的材料、结构和转换机制。因此,我们必须处理各种类型的噪声源,并找到分离它们贡献的方法。在本文中,我们首先提供了 MEMS 可靠性和噪声的概述,然后提出了一个将特定器件的噪声数据与其质量或可靠性联系起来的框架。之后,我们分析了 13 类 MEMS,并推荐了最适合这种方法的 4 类。最后,我们提出了一种噪声测量系统,以分离电气和机械噪声源的贡献。通过本文,我们希望当前和未来的 MEMS 设计者能够看到其设备中噪声的潜在好处。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/861e/7926468/b42ba5a41872/sensors-21-01510-g001.jpg

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