High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning  

作　　者：BING DUAN HANYING ZOU JIN-HUI CHEN CHUN HUI MA XINGYUN ZHAO XIAOLONG ZHENG CHUAN WANG LIANG LIU DAQUAN YANG 

机构地区：[1]State Key Laboratory of Information Photonics and Optical Communications,School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China [2]Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia,Beijing University of Posts and Telecommunications,Beijing 100876,China [3]Institute of Electromagnetics and Acoustics and Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection Technology,Xiamen University,Xiamen 361005,China [4]Shenzhen Research Institute of Xiamen University,Shenzhen 518000,China [5]School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China

出　　处：《Photonics Research》2022年第10期2343-2348,共6页光子学研究（英文版）

基　　金：National Natural Science Foundation of China(11974058,62005231,62131002);A3 Foresight Program of NSFC(62061146002);Beijing Nova Program from Beijing Municipal Science and Technology Commission(Z201100006820125);Beijing Municipal Natural Science Foundation(Z210004);State Key Laboratory of Information Photonics and Optical Communications,BUPT,China(IPOC2021ZT01);BUPT Excellent Ph.D.Students Foundation(CX2022114).

摘　　要：Whispering gallery mode(WGM)microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity,compact size,and fast response.However,the conventional WGM sensors rely on monitoring the changes of a single mode,and the abundant sensing information in WGM transmission spectra has not been fully utilized.Here,empowered by machine learning(ML),we propose and demonstrate an ergodic spectra sensing method in an optofluidic microcavity for high-precision pressure measurement.The developed ML method realizes the analysis of the full features of optical spectra.The prediction accuracy of 99.97%is obtained with the average error as low as 0.32 kPa in the pressure range of 100 kPa via the training and testing stages.We further achieve the real-time readout of arbitrary unknown pressure within the range of measurement,and a prediction accuracy of 99.51%is obtained.Moreover,we demonstrate that the ergodic spectra sensing accuracy is∼11.5%higher than that of simply extracting resonating modes’wavelength.With the high sensitivity and prediction accuracy,this work opens up a new avenue for integrated intelligent optical sensing.

关 键 词：measurement SPECTRA PREDICTION 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TP212[自动化与计算机技术—控制科学与工程]