Combustion Quality Estimation in Power Station Boilers using Median Threshold Clustering Algorithms
Combustion Quality Estimation in Power Station Boilers using Median Threshold Clustering Algorithms
复制标题
使用中值阈值聚类算法估计电站锅炉的燃烧质量
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
K. Sujatha
中科院分区：
文献类型：
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作者：
K. Sujatha;DR. N. Pappa;A. Kalaivani;K. Sujatha
电站锅炉燃烧品质的评价对控制大气污染具有重要意义。从烟囱中排出的NOx和CO等有害气体会造成空气污染。通过分析火焰颜色，可以将烟气中的NOx和CO浓度保持在允许的范围内。火焰的颜色受燃烧质量的影响。当完全燃烧发生时，出口处的这些气体的量在公差范围内。因此，如果使用图像处理技术从火焰中估计燃烧质量，则可以最小化空气污染。这种新的策略开发使用中值阈值的特征约简和各种聚类算法来估计燃烧质量。
The estimation of combustion quality in power station boilers is of great importance in the present scenario as it plays an important role in controlling the air pollution. The harmful gases like NOx and CO from the chimney causes air pollution. The amount of NOx and CO concentration in flue gas can be maintained within admissible limits by analyzing the flame colour. The colour of the flame is affected by combustion quality. When complete combustion takes place the amount these gases at the exit are within tolerance. Hence if the quality of combustion was estimated from the flame using image processing technique, it is possible to minimize the air pollution. This new strategy developed uses median threshold for feature reduction and various clustering algorithms to estimate the quality of combustion.