Case studies for selective agglomeration detection in fluidized beds: Application of a new screening methodology

被引:20
作者
Bartels, Malte [1 ]
Nijenhuis, John [1 ]
Kapteijn, Freek [1 ]
van Ommen, J. Ruud [1 ]
机构
[1] Delft Univ Technol, Dept Chem Engn, Delft Res Ctr Sustainable Energy, NL-2628 BL Delft, Netherlands
关键词
Fluidized beds; Selective agglomeration detection; Signal analysis; Screening methodology; Data filtering; Monitoring;
D O I
10.1016/j.powtec.2010.05.003
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
We have recently presented a new methodology for screening different signal analysis methods in combination with signal pre-treatment methods with the goal to effectively identify those combinations that are highly selective towards a specific process change (Bartels et al., Ind. Chem. Eng. Res. 48 (2009) 3158-3166). The main outcome of the methodology is visually represented in an overall result matrix with coloured tiles illustrating a measure for the suitability of each combination of analysis method and signal pre-treatment. Suitable methods can be visually identified very quickly. For the early detection of agglomeration in fluidized beds we illustrate this methodology by four different cases: two cases from a pilot-scale bubbling bed, one from an industrial scale bubbling bed and one case from a lab-scale circulating bed. With the result matrix for each case several suitable methods are identified. The data are also evaluated to identify methods that are more generally applicable for a range of different cases. The suitability of a positively identified method is subsequently analyzed for its temporal response to both agglomeration and other effects. The influence of the different data pre-treatment methods is also addressed. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:148 / 166
页数:19
相关论文
共 20 条
[1]  
[Anonymous], 2001, Applied Multivariate Data Analysis
[2]   Methodology for the Screening of Signal Analysis Methods for Selective Detection of Hydrodynamic Changes in Fluidized Bed Systems [J].
Bartels, Malte ;
Vermeer, Bart ;
Verheijen, Peter J. T. ;
Nijenhuis, John ;
Kapteijn, Freek ;
van Ommen, J. Ruud .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2009, 48 (06) :3158-3166
[3]   On-line detection of bed fluidity in a fluidized bed coker [J].
Briens, C ;
McDougall, S ;
Chan, E .
POWDER TECHNOLOGY, 2003, 138 (2-3) :160-168
[4]  
Carlson G., 1998, Signal and Linear System Analysis, V2nd
[5]   The S-statistic as an early warning of entrainment in a fluidized bed dryer containing pharmaceutical granule [J].
Chaplin, G ;
Pugsley, T ;
Winters, C .
POWDER TECHNOLOGY, 2005, 149 (2-3) :148-156
[6]   Mechanism and prediction of bed agglomeration during fluidized bed combustion of a biomass fuel: Effect of the reactor scale [J].
Chirone, Riccardo ;
Miccio, Francesco ;
Scala, Fabrizio .
CHEMICAL ENGINEERING JOURNAL, 2006, 123 (03) :71-80
[7]   Detecting differences between delay vector distributions [J].
Diks, C ;
vanZwet, WR ;
Takens, F ;
DeGoede, J .
PHYSICAL REVIEW E, 1996, 53 (03) :2169-2176
[8]   THE APPLICATION OF DIFFUSIONAL TECHNIQUES IN TIME-SERIES ANALYSIS TO IDENTIFY COMPLEX FLUID DYNAMIC REGIMES [J].
Giona, Massimiliano ;
Paglianti, Alessandro ;
Soldati, Alfredo .
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, 1994, 2 (04) :503-520
[9]  
Kantz H., 2000, Nonlinear Time Series Analysis, V2nd
[10]  
KORBEE R, 2004, ECNC04052