SOM-Based Method for Process State Monitoring and Optimization in Fluidized Bed Energy Plant

Author(s):  
Mikko Heikkinen ◽  
Ari Kettunen ◽  
Eero Niemitalo ◽  
Reijo Kuivalainen ◽  
Yrjö Hiltunen

2018 ◽  
Vol 73 ◽  
pp. 271-286 ◽  
Author(s):  
Sabino De Gisi ◽  
Agnese Chiarelli ◽  
Luca Tagliente ◽  
Michele Notarnicola


2013 ◽  
Vol 850-851 ◽  
pp. 851-855
Author(s):  
Lei Chen ◽  
Wei Guo Lin ◽  
Zhong Zhao ◽  
Hao Tong Hou

Agglomeration reduces the productivity and the quality of polyethylene fluidized bed. The mathematical model cant characterize the nonlinearity of two-phase flow in the fluidized bed exactly, which make state monitoring and failure diagnosis to inner state of fluidized bed lacking assessment criterion. Acoustic emission sensor could monitor the signals from polyethylene granules impacting on the wall of fluidized beds. Use wavelet packet analysis to process the acoustic emission signals and extract voiceprint feature by MFCC. The feature vector is combined with the MFCC of all sensors. Reduce the dimensionality of vector by PCA and test the feature vector by BP neural network.



Author(s):  
Marco Badami ◽  
Antonio Mittica ◽  
Alberto Poggio

This paper assesses the incineration capacity requirement of the Province of Turin through a detailed analysis of the mass streams and the properties of residual Municipal Solid Waste (MSW). Historical data series were elaborated to study the trend evolution of household generation and separate collection. Residual MSW material compositions were calculated for each year over an observed period and for planned scenarios. A waste properties model was applied to calculate the residual MSW chemical composition and the LHV. The analysis allows conclusions to be drawn about the design of the planned waste-to-energy plant and to estimate the required size and technology to be used. The results show that the use of grate furnace combustor appears to be more suitable than fluidized bed.



2019 ◽  
Vol 343 ◽  
pp. 683-692 ◽  
Author(s):  
Lei Guo ◽  
Zhe Wang ◽  
Shengping Zhong ◽  
Qipeng Bao ◽  
Zhancheng Guo






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