首页|Investigations into the flow dynamics of mixed biomass particles in a fluidized bed through Hilbert-Huang transformation and data-driven modelling
Investigations into the flow dynamics of mixed biomass particles in a fluidized bed through Hilbert-Huang transformation and data-driven modelling
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Flow dynamics of binary particles are investigated to realize the monitoring and optimization of fluidized beds.It is a challenge to accurately classify the mass fraction of mixed biomass,considering the limi-tations of existing techniques.The data collected from an electrostatic sensor array is analyzed.Cross correlation,empirical mode decomposition(EMD),Hilbert-Huang transform(HHT)are applied to pro-cess the signals.Under a higher mass fraction of the wood sawdust,the segregation behavior occurs,and the high energy region of HHT spectrum increases.Furthermore,two data-driven models are trained based on a hybrid wavelet scattering transform and bidirectional long short-term memory(ST-BiLSTM)network and a EMD and BiLSTM(EMD-BiLSTM)network to identify the mass fractions of the mixed biomass,with accuracies of 92％and 99％.The electrostatic sensing combined with the EMD-BiLSTM model is effective to classify the mass fraction of the mixed biomass.
Fluidized bedsBiomassHilbert-Huang transformationBidirectional long short-term memorynetworkElectrostatic sensors
Bojian Qi、Yong Yan、Wenbiao Zhang
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School of Computer and Artificial Intelligence,Beijing Technology and Business University,Beijing,100048,China
International Research Center for Carbon Neutralization,Hangzhou Beihang International Innovation Institute,Beihang University,Hangzhou,311115,China
School of Control and Computer Engineering,North China Electric Power University,Beijing,102206,China
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