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Research on Furnace Flame Detection Based on MSIF
Author: LiZhiXin
Tutor: MaYongGuang
School: North China Electric Power University (Hebei)
Course: Control Theory and Control Engineering
Keywords: Flame detection Information Fusion Neural Networks D - S evidence theory
CLC: TM621.2
Type: Master's thesis
Year: 2009
Downloads: 23
Quote: 0
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Abstract
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For large thermal power plants in terms of coal-fired boilers , pulverized coal combustion process is a very complex suspension combustion and very unstable conditions . Therefore, the monitoring of the combustion state in the furnace is very important to the reliability, safety and economy of the boiler . First, based on the analysis of the traditional the flame detection methods and characteristics of the CCD image acquisition equipment acquisition burner flame image as a measurement tool . Secondly, detailed analysis of the characteristics of the BP neural network , the judgment based on BP neural network flame burning state , the results show that the neural network fusion is an effective method . Finally , for the uncertainty in the flame detection BP neural network and DS evidence theory is a combination of the two fusion constructs . The experimental results show that the two fusion constructs can effectively improve the accuracy of the flame detector and the boiler combustion security .
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CLC: > Industrial Technology > Electrotechnical > Power generation, power plants > Power plant > Thermal power plants, thermal power stations > Boilers and combustion systems
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