Abstract

A novel laser self-mixing interferometry vibration measurement algorithm based on the local maximum detection technique is proposed, that can reconstruct micro vibrations rapidly and easily. In this article, the principles of the local maximum detection algorithm are analyzed in detail, and the process of solving the window function is emphasized. The major advantage of the method is that it does not involve any complicated calculations and removes the need for optical/electromechanical components. The validity of the presented method is confirmed by means of simulated signals and demonstrated via several experiments for harmonic and aleatory motion.

Highlights

  • Laser self-mixing interferometry (SMI), which is called the laser optical feedback interference effect, is an emerging and promising nondestructive optical measurement technique [1], [2]

  • An effective micro vibration measurement algorithm based on local maximum detection (LMD) for self-mixing signals is proposed in this work

  • This study presents a new algorithm that is based on the LMD technique to unwrap the correct external phase φF (t) and reconstruct micro vibrations

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Summary

INTRODUCTION

Laser self-mixing interferometry (SMI), which is called the laser optical feedback interference effect, is an emerging and promising nondestructive optical measurement technique [1], [2]. An effective micro vibration measurement algorithm based on local maximum detection (LMD) for self-mixing signals is proposed in this work. A window function that is based on adopting the median of the derivative of the SMI signal is proposed to determine the correct direction of the LMPs. Third, we use the cubic spline interpolation method to fit the micro vibration curve. This study presents a new algorithm that is based on the LMD technique to unwrap the correct external phase φF (t) and reconstruct micro vibrations. The findings verify that the algorithm is only slightly influenced by the optical feedback level under the weak feedback regime

EXPERIMENTAL VALIDATIONS
Findings
CONCLUSION
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