Nonlinear characteristics analyses of particle motion for predicting flow regimes

查看全文 作　　者：Panxing [1]Kang;Yujian [1]Lu;Lei [1]Yang;Libin [1]Liu;Xiayi(Eric)[1]Hu;Xiao [2]Luo;Hongbo [1]Chen;Yefeng [1]Zhou;Rui [1]Zhang

机构地区：[1]National and Local United Engineering Research Centre for Chemical Process Simulation and Intensification,Chemical Process Simulation and Optimization Engineering Research Center of the Ministry of Education,Xiangtan University,Xiangtan 411105,China;[2]College of Chemistry and Chemical Engineering,Hunan University,Changsha 410082,China

出　　处：《Particuology》索引2020年第18卷第6期,共8页

基　　金：National Natural Science Foundation of China(21506181,21506179,51608464);Natural Science Foundation of Hunan Province(2019JJ40281,2019SK2112,2018SK2027,2018RS3088,2020JJ3033);Research Foundation of Education Bureau of Hunan Province(18B088);China Scholarship Council(201707230001);Hunan Key Laboratory of Environment Friendly Chemical Process Integration,and Hunan 2011 Collaborative Innovation Center of Chemical Engineering&Technology with Environmental Benignity and Effective Resource Utilization. 摘　　要：Gas-solid flow regimes have a significant impact on particle transport and separation in a fluidized bed reactor.In this study,to determine flow regime transitions in gas-solid fluidized beds,an acoustic technique was used to detect and analyze the behavior of gas and solids.Algorithm complexity,fluctuation complexity,and Shannon entropy analyses of acoustic emission signals were performed to examine non linear system characteristics,and to determine the flow regime transiti on velocities uc,uk,and ufd-Moreover,using the standard deviation of pressure signals,pressure measurements and acoustic measurements were compared.The relative deviations(RDs)between the experimental and empirical values of uk were 8.8%,13.7%,8.8%,and 30.4%for the algorithm complexity,fluctuation complexity,Shannon entropy,and pressure signal standard deviation,respectively,while the respective RDs for Ufd were 15.7%,23.9%,15.7%,and 97.8%.The RDs between the experimental and empirical values of uc were all 6.4%.The experimental values obtained from acoustic signal measurements were therefore closer to the empirical values.In summary,the integration of non-intrusive acoustic measurements,complexity analysis,and Shannon entropy analysis is suitable for identifying flow regime transitions. 关键词：Acoustic emission Nonlinear characteristics Complexity analysis Shannon entropy Flow regime transition

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Nonlinear characteristics analyses of particle motion for predicting flow regimes

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