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基于法布里-珀罗微腔结构的光纤声传感系统研究 被引量:4

Study of a Optical Fiber Acoustic Sensing System Based on F-P Microcavity Structure
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摘要 对基于法布里-珀罗(F-P)微腔结构的光纤声传感系统进行研究。传感头由具有高熔点、低热膨胀系数的氧化锆(ZrO 2)管贴合氧化石墨烯(GO)薄膜制作而成。测试结果显示,F-P微腔的腔长为92.943μm,反射谱的干涉对比度达25 dB。对传感头的声音传感性能进行测试,结合多帧比较法,实现了语音前导无话帧的自动识别。运用基于小波包变换的维纳滤波方法对采集到的信号进行去噪,相比单纯运用维纳滤波的方法,信噪比提高了1.5 dB,从而提高了语音质量。整个系统结构简单、成本低、实用性高,应用场景广泛。 In this paper,a optical fiber acoustic sensing system based on the Fabry-Perot(F-P)microcavity structure is studied.The sensor head composed of a zirconia(ZrO 2)tube with a high melting point and low thermal expansion coefficient bonded to graphene oxide(GO)diaphragm.Test results show that the cavity length of the F-P microcavity is 92.943μm.Further,the interference contrast of the reflection spectrum is 25 dB.Additionally,the sound sensing performance of the sensor head is tested.Combined with the multiframe comparison method,the automatic recognition of speech leading to silent frames is realized.The Wiener filtering method based on wavelet packet transform is used to denoise the collected signals.Moreover,the signal-to-noise ratio of this method improves by 1.5 dB compared with that of the Wiener filtering method only,thus improving the quality of the speech.The attributes of the entire system include a simple structure,low cost,high practicability,and wide application scenarios.
作者 尹玺 万生鹏 熊新中 董德壮 刘恒 肖登 雷盈 Yin Xi;Wan Shengpeng;Xiong Xinzhong;Dong Dezhuang;Liu Heng;Xiao Deng;Lei Ying(Jiangxi Engineering Laboratory for Optoelectronics Testing Technology,Nanchang Hangkong University,Nanchang,Jiangxi 330063,China;National Engineering Laboratory for Nondestructive Testing and Optoelectric Sensing Technology and Application,Nanchang Hangkong University,Nanchang,Jiangxi 330063,China)
出处 《激光与光电子学进展》 CSCD 北大核心 2021年第3期172-178,共7页 Laser & Optoelectronics Progress
基金 国家自然科学基金(61465009) 江西省主要学科学术和技术带头人资助计划(20172BCB22012) 江西省自然科学基金重点项目(20202ACBL202002)。
关键词 测量 光纤声传感 法布里-珀罗 氧化锆 氧化石墨烯 小波包变换 维纳滤波 measurement fiber optic acoustic sensing Fabry-Perot ZrO 2 GO wavelet packet transformation Wiener filtering
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