典型文献
                High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning
            文献摘要:
                    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.
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                    作者姓名:
                    
                        BING DUAN;HANYING ZOU;JIN-HUI CHEN;CHUN HUI MA;XINGYUN ZHAO;XIAOLONG ZHENG;CHUAN WANG;LIANG LIU;DAQUAN YANG
                    
                作者机构:
                    State Key Laboratory of Information Photonics and Optical Communications,School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China;Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia,Beijing University of Posts and Telecommunications,Beijing 100876,China;Institute of Electromagnetics and Acoustics and Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection Technology,Xiamen University,Xiamen 361005,China;Shenzhen Research Institute of Xiamen University,Shenzhen 518000,China;School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China
                文献出处:
                    
                引用格式:
                    
                        [1]BING DUAN;HANYING ZOU;JIN-HUI CHEN;CHUN HUI MA;XINGYUN ZHAO;XIAOLONG ZHENG;CHUAN WANG;LIANG LIU;DAQUAN YANG-.High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning)[J].光子学研究(英文),2022(10):2343-2348
                    
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                    High,precision,whispering,gallery,microsensors,ergodic,spectra,empowered,by,machine,learning,Whispering,WGM,microcavities,provide,increasing,opportunities,measurement,due,their,ultrahigh,sensitivity,compact,size,fast,response,However,conventional,rely,monitoring,changes,single,abundant,sensing,information,transmission,has,not,been,fully,utilized,Here,ML,propose,demonstrate,method,optofluidic,microcavity,pressure,developed,realizes,analysis,features,optical,prediction,accuracy,obtained,average,error,low,kPa,range,via,training,testing,stages,We,further,achieve,readout,arbitrary,unknown,within,Moreover,that,higher,than,simply,extracting,resonating,modes,wavelength,With,this,work,opens,up,new,avenue,integrated,intelligent
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