Enhanced performance of self-mixing interferometry for piezoelectric material displacement measurement using the data fusion method

IF 5.6 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Measurement Pub Date : 2025-06-30 Epub Date: 2025-03-11 DOI:10.1016/j.measurement.2025.117261
Weilin Ma , Xingye Tong , Shengping Du , Yuntao Cheng
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Abstract

Piezoelectric materials play a pivotal role in enabling nano-positioning. However, their precision control is hindered by hysteresis, creating a need for a low-cost, non-contact displacement sensor capable of achieving high-precision control. While hysteresis models and self-mixing interferometry (SMI) with phase unwrapping methods offer cost-effective solutions for monitoring the displacement of piezoelectric materials, their versatility is often limited in complex scenarios. This study proposes a fusion method that combines the piezoelectric material drive voltage with SMI displacement measurements using the fringe counting method. This approach provides a balanced trade-off among cost, accuracy, and versatility for displacement monitoring. Compared to SMI alone, the proposed method reduces the root mean square error (RMSE) by 30.1 % and the maximum error by 45.5 %, achieving an accuracy of 120.7 nm and an RMSE of 45 nm. These improvements make the method particularly well-suited for cost-sensitive applications requiring high precision.

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利用数据融合方法提高压电材料位移测量自混合干涉测量性能
压电材料在实现纳米定位方面发挥着举足轻重的作用。然而,它们的精确控制受到磁滞的阻碍,因此需要一种能够实现高精度控制的低成本、非接触式位移传感器。虽然磁滞模型和自混合干涉测量(SMI)与相位解包方法为监测压电材料的位移提供了具有成本效益的解决方案,但其多功能性在复杂情况下往往受到限制。本研究提出了一种融合方法,利用条纹计数法将压电材料驱动电压与 SMI 位移测量相结合。这种方法在成本、精度和位移监测的多功能性之间实现了平衡。与单独的 SMI 相比,所提出的方法将均方根误差 (RMSE) 降低了 30.1%,最大误差降低了 45.5%,实现了 120.7 nm 的精度和 45 nm 的 RMSE。这些改进使该方法特别适用于要求高精度的成本敏感型应用。
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来源期刊
Measurement
Measurement 工程技术-工程:综合
CiteScore
10.20
自引率
12.50%
发文量
1589
审稿时长
12.1 months
期刊介绍: Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.
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