Title :
Working Condition Recognition of Cement Decomposition Furnace Based on ART-2 Neural Network
Author :
Song Qiuyun ; Yuan Zhugang
Author_Institution :
Univ. of Jinan, Jinan, China
Abstract :
This paper advances a two-stage ART-2 neural network method on working condition recognition of cement decomposition furnace. The process parameters describing cement decomposition furnace conditions are determined based on the process design requirements and the analysis of field operation experience. The field operating datas through mean filtering are determined as the first-class ART-2 network inputs, and the trend recognitions of the parameters are finished based on the trend recognition function. The results are determined as the second-class ART-2 network inputs,and the real time recognitions of decomposition furnace conditions are completed using the pattern recognition function. The simulation and practical operation show the effectiveness of the method.
Keywords :
ART neural nets; cement industry; filtering theory; furnaces; pattern recognition; process design; production engineering computing; cement decomposition furnace conditions; field operation experience analysis; first-class ART-2 network inputs; mean filtering; pattern recognition function; process design requirements; process parameters; second-class ART-2 network inputs; trend recognition function; two-stage ART-2 neural network method; working condition recognition; Coal; Employee welfare; Furnaces; Market research; Neural networks; Neurons; Pattern recognition; ART-2 Neural Network; Cement Decomposition Furnace; Pattern Recognition; Trend Recognition; Working Condition Recognition;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-3434-8
DOI :
10.1109/ICMTMA.2014.203