Phase-unwrapping algorithm combined with wavelet transform and Hilbert transform in self-mixing interference for individual microscale particle detection  

作　　者：赵宇 李嘉玮 张梦雷 赵洋洋 邹江林 陈涛 Yu Zhao;Jiawei Li;Menglei Zhang;Yangyang Zhao;Jianglin Zou;Tao Chen(Institute of Advanced Photonic Technology,Faculty of Materials and Manufacturing,Beijing University of Technology,Beijing 100124,China;Key Laboratory of Trans-scale Laser Manufacturing Technology(Beijing University of Technology),Ministry of Education,Beijing 100124,China)

机构地区：[1]Institute of Advanced Photonic Technology,Faculty of Materials and Manufacturing,Beijing University of Technology,Beijing 100124,China [2]Key Laboratory of Trans-scale Laser Manufacturing Technology(Beijing University of Technology),Ministry of Education,Beijing 100124,China

出　　处：《Chinese Optics Letters》2023年第4期31-36,共6页中国光学快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.61905005 and 52175375);the General Program of Science and Technology Development Project of Beijing Municipal Education Commission(No.KM202110005004)。

摘　　要：The self-mixing interferometry(SMI)technique is an emerging sensing technology in microscale particle classification.However,due to the nature of the SMI effect raised by a microscattering particle,the signal analysis suffers from many problems compared with a macro target,such as lower signal-to-noise ratio(SNR),short transit time,and time-varying modulation strength.Therefore,the particle sizing measurement resolution is much lower than the one in typical displacement measurements.To solve these problems,in this paper,first,a theoretical model of the phase variation of a singleparticle SMI signal burst is demonstrated in detail.The relationship between the phase variation and the particle size is investigated,which predicts that phase observation could be another alternative for particle detection.Second,combined with continuous wavelet transform and Hilbert transform,a novel phase-unwrapping algorithm is proposed.This algorithm can implement not only efficient individual burst extraction from the noisy raw signal,but also precise phase calculation for particle sizing.The measurement shows good accuracy over a range from 100 nm to 6μm with our algorithm,proving that our algorithm enables a simple and reliable quantitative particle characteristics retrieval and analysis methodology for microscale particle detection in biomedical or laser manufacturing fields.

关 键 词：self-mixing interferometry particle detection continuous wavelet transform laser processing Hilbert transform 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]