Micro displacement reconstruction of laser self mixing interference based on wavelet threshold filtering and S-G filtering

You Yaqiang; Li Xintao; Liu Hui; He Dan

doi:10.11884/HPLPB202436.240125

Volume 36 Issue 8

Jul. 2024

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Article Navigation > High Power Laser and Particle Beams > 2024 > 36(8): 081002

You Yaqiang, Li Xintao, Liu Hui, et al. Micro displacement reconstruction of laser self mixing interference based on wavelet threshold filtering and S-G filtering[J]. High Power Laser and Particle Beams, 2024, 36: 081002. doi: 10.11884/HPLPB202436.240125

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You Yaqiang, Li Xintao, Liu Hui, et al. Micro displacement reconstruction of laser self mixing interference based on wavelet threshold filtering and S-G filtering[J]. High Power Laser and Particle Beams, 2024, 36: 081002. doi: 10.11884/HPLPB202436.240125

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Micro displacement reconstruction of laser self mixing interference based on wavelet threshold filtering and S-G filtering

doi: 10.11884/HPLPB202436.240125

School of Mechanical and Electrical Engineering, Xi’an Polytechnic University, Xi’an 710048, China

Received Date: 2024-04-12
Accepted Date: 2024-06-12
Rev Recd Date: 2024-06-12

Available Online: 2024-06-20

Publish Date: 2024-07-04

Abstract

Abstract

In semiconductor laser self-mixing interferometry (SMI) for micro-displacement measurement, the precise extraction of phase information is essential for high-accuracy displacement reconstruction. However, measurement noise induces phase errors in the SMI signal, leading to suboptimal displacement reconstruction accuracy. To tackle the challenge of signal denoising, wavelet thresholding denoising algorithms can effectively filter out most of the noise. However, they suffer from local oscillation issues when applied to SMI signal denoising. This results in the appearance of new interference peaks in the denoised self-mixing interference signal, thereby causing erroneous displacement reconstruction. This paper proposes an SMI signal processing algorithm that synergistically combines wavelet thresholding and Savitzky-Golay (S-G) filtering. By incorporating the S-G filtering algorithm, the algorithm smooths out noise at phase jump points on a global scale, thus mitigating the local oscillation issues inherent in wavelet-only denoising. Experimental results of displacement reconstruction indicate that the proposed method successfully eliminates high-frequency noise at both amplitude and phase jump points. Consequently, the reconstructed displacement curve retains the original waveform characteristics of the vibrating object.
- self mixing interference,
- phase unwrapping,
- displacement reconstruction,
- wavelet threshold filter,
- Savitzky-Golay filter

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References(24)

References

[1]	Taimre T, Nikolić M, Bertling K, et al. Laser feedback interferometry: a tutorial on the self-mixing effect for coherent sensing[J]. Advances in Optics and Photonics, 2015, 7(3): 570-631. doi: 10.1364/AOP.7.000570
[2]	Brambilla M, Columbo L L, Dabbicco M, et al. Versatile multimodality imaging system based on detectorless and scanless optical feedback interferometry-a retrospective overview for a prospective vision[J]. Sensors, 2020, 20: 5930. doi: 10.3390/s20205930
[3]	Bhardwaj V K, Maini S. Compact and self-aligned fluid refractometer based on the Doppler-induced self-mixing effect[J]. Applied Optics, 2020, 59(10): 3064-3072. doi: 10.1364/AO.388078
[4]	Donati S, Norgia M. Overview of self-mixing interferometer applications to mechanical engineering[J]. Optical Engineering, 2018, 57: 051506.
[5]	Kou Ke, Li Xingfei, Li Li, et al. Absolute distance estimation with improved genetic algorithm in laser self-mixing scheme[J]. Optics & Laser Technology, 2015, 68: 113-119.
[6]	郭冬冬, 叶会英. 光反馈自混合干涉位移实时跟踪测量算法[J]. 激光杂志, 2017, 38(1):55-59 Guo Dongdong, Ye Huiying. Optical feedback self-mixing interference displacement real-time tracking and measurement algorithm[J]. Laser Journal, 2017, 38(1): 55-59
[7]	Liu Hui, Li Sijia, You Yaqiang, et al. Model of multiple mode gain competition in self-mixing laser diode[J]. Optik, 2023, 281: 170853. doi: 10.1016/j.ijleo.2023.170853
[8]	Wei Zheng, Huang Wencai, Zhang Jie, et al. Obtaining scalable fringe precision in self-mixing interference using an even-power fast algorithm[J]. IEEE Photonics Journal, 2017, 9: 6803211.
[9]	宋观平, 齐攀, 李莹, 等. 基于双光反馈的双偏振差分自混合干涉降噪技术[J]. 激光与光电子学进展, 2022, 59:1126001 Song Guanping, Qi Pan, Li Ying, et al. Dual-polarization differential noise reduction technology in dual-beam feedback self-mixing interferometer[J]. Laser & Optoelectronics Progress, 2022, 59: 1126001
[10]	张玉燕, 周航, 闫美素. 基于经验模态分解的自混合干涉相位提取方法研究[J]. 物理学报, 2015, 64:054203 doi: 10.7498/aps.64.054203 Zhang Yuyan, Zhou Hang, Yan Meisu. Study on the phase-extracting method of self-mixing signal based on empirical mode decomposition[J]. Acta Physica Sinica, 2015, 64: 054203 doi: 10.7498/aps.64.054203
[11]	宦海, 郭克伦, 张雨, 等. 两路反馈外腔自混合干涉信号的相位提取方法[J]. 激光与光电子学进展, 2016, 53:061203 Huan Hai, Guo Kelun, Zhang Yu, et al. Phase-extracting method of laser self-mixing interference signal with two feedback external cavity[J]. Laser & Optoelectronics Progress, 2016, 53: 061203
[12]	姜春雷, 周旭明. 基于激光自混合干涉技术和小波变换的齿轮箱故障诊断[J]. 光学技术, 2017, 43(1):83-86 Jiang Chunlei, Zhou Xuming. Application of laser self-mixing interference technology and wavelet transform in gearbox fault diagnosis[J]. Optical Technique, 2017, 43(1): 83-86
[13]	郭晴, 叶会英. 基于奇异值分解的自混合干涉信号降噪方法[J]. 现代电子技术, 2019, 42(9):26-30 Guo Qing, Ye Huiying. Singular value decomposition based denoising method of self-mixing interference signal[J]. Modern Electronics Technique, 2019, 42(9): 26-30
[14]	Liu Hui, You Yaqiang, Li Sijia, et al. Denoising of laser self-mixing interference by improved wavelet threshold for high performance of displacement reconstruction[J]. Photonics, 2023, 10: 943. doi: 10.3390/photonics10080943
[15]	邢挺, 范增盛, 马君梁, 等. 基于小波变换改进阈值函数的故障行波去噪方法[J]. 电工技术, 2023(17):37-43 Xing Ting, Fan Zengsheng, Ma Junliang, et al. Denoising method of fault traveling wave based on wavelet transform and improved threshold function[J]. Electric Engineering, 2023(17): 37-43
[16]	张宝峰, 左铭, 朱均超, 等. 基于VMD与小波阈值的激光自混合干涉位移信号滤波方法[J]. 激光杂志, 2021, 42(2):77-82 Zhang Baofeng, Zuo Ming, Zhu Junchao, et al. Research on laser self-mixing interference displacement signal filtering method based on VMD and wavelet threshold[J]. Laser Journal, 2021, 42(2): 77-82
[17]	郝军, 李福生, 杨婉琪, 等. Russian roulette优化小波算法在X射线荧光光谱去噪中的应用[J]. 激光与光电子学进展, 2023, 60:0930006 Hao Jun, Li Fusheng, Yang Wanqi, et al. X-ray fluorescence spectral denoising analysis based on the Russian roulette optimized wavelet algorithm[J]. Laser & Optoelectronics Progress, 2023, 60: 0930006
[18]	罗会甫, 王扬红, 朱炜, 等. 基于激光自混合干涉法的微振动测量[J]. 北京理工大学学报, 2017, 37(6):584-589 Luo Huifu, Wang Yanghong, Zhu Wei, et al. Measurement of micro-vibration based on laser self-mixing interference[J]. Transactions of Beijing Institute of Technology, 2017, 37(6): 584-589
[19]	张震川, 曹保锋, 李鹏, 等. 小波包分形在远区核爆电磁脉冲识别中的应用[J]. 强激光与粒子束, 2022, 34:066002 doi: 10.11884/HPLPB202234.210375 Zhang Zhenchuan, Cao Baofeng, Li Peng, et al. Recognition of far-region nuclear electromagnetic pulse based on wavelet fractal technique[J]. High Power Laser and Particle Beams, 2022, 34: 066002 doi: 10.11884/HPLPB202234.210375
[20]	李思嘉, 刘晖, 熊玲玲, 等. 基于S-G滤波与包络提取算法的半导体激光器自混合干涉微位移测量[J]. 机械与电子, 2022, 40(4):13-19 Li Sijia, Liu Hui, Xiong Lingling, et al. Micro-displacement measurement of semiconductor laser self-mixing interference based on S-G Filter and envelope extraction algorithm[J]. Machinery & Electronics, 2022, 40(4): 13-19
[21]	王婧瑶, 王红军. 基于Mask R-CNN与SG滤波的手势识别关键点特征提取方法[J]. 电子测量与仪器学报, 2021, 35(9):41-48 Wang Jingyao, Wang Hongjun. Gesture key point extraction method based on Mask R-CNN and SG filter[J]. Journal of Electronic Measurement and Instrumentation, 2021, 35(9): 41-48
[22]	Wang Xiufang, Yuan Ye, Chen Peng, et al. Laser self-mixing based on peak–valley point detection algorithm for displacement reconstruction[J]. Optical and Quantum Electronics, 2020, 52: 34. doi: 10.1007/s11082-019-2153-9
[23]	Zhao Yu, Li Jiawei, Zhang Menglei, et al. Phase-unwrapping algorithm combined with wavelet transform and Hilbert transform in self-mixing interference for individual microscale particle detection[J]. Chinese Optics Letters, 2023, 21: 041204. doi: 10.3788/COL202321.041204
[24]	王华英, 于梦杰, 刘飞飞, 等. 基于快速傅里叶变换的四种相位解包裹算法[J]. 强激光与粒子束, 2013, 25(5):1129-1133 doi: 10.3788/HPLPB20132505.1129 Wang Huaying, Yu Mengjie, Liu Feifei, et al. Four phase unwrapping algorithms based on fast Fourier transform[J]. High Power Laser and Particle Beams, 2013, 25(5): 1129-1133 doi: 10.3788/HPLPB20132505.1129