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作 者:FENG Fei QIN Li 冯飞;秦丽(中北大学仪器科学与动态测试教育部重点实验室,山西太原030051;中北大学电子测试技术重点实验室,山西太原030051)
机构地区:[1]Key Laboratory of Instrumentation Science and Dynamic Measurement(North University of China),Ministry of Education, Taiyuan 030051, China [2]Science and Technology on Electronic Test & Measurement Laboratory, North University of China, Taiyuan 030051, China
出 处:《Journal of Measurement Science and Instrumentation》2021年第1期61-67,共7页测试科学与仪器(英文版)
基 金:National Natural Science Foundation of China(No.51467009);Natural Science Foundation of Shanxi Province(No.51400000)。
摘 要:An improved denoising method and its application in pulse beat signal denoising are studied.The proposed denoising algorithm takes the advantages of local mean decomposition(LMD)and time-frequency peak filtering(TFPF),called L-T algorithm.As a classical time-frequency filtering method,TFPF can effectively suppress random noise with signal amplitude retained when selecting a longer window length,while the signal amplitude will be seriously attenuated when selecting a shorter window length.In order to maintain effective signal amplitude and suppress random noise,LMD and TFPF are improved.Firstly,the original signal is decomposed into progression-free survival(PFS)by LMD,and then the standard error of mean(SEM)of each product function is calculated to classify many PFSs into useful component,mixed component and noise component.Secondly,by using the shorter window TFPF for useful component and the longer window TFPF for mixed component,noise component is removed and the final signal is obtained after reconstruction.Finally,the proposed algorithm is used for noise reduction of an Fabry-Perot(F-P)pressure sensor.Experimental results show that compared with traditional wavelet,L-T algorithm has better denoising effect on sampled data.
关 键 词:local mean decomposition(LMD) time-frequency peak filtering(TFPT) noise reduction Fabry-Perot(F-P)sensor
分 类 号:TN9[电子电信—信息与通信工程]
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