Under the cutting operation of low-pressure cylinder of heating unit,the L-1 temperature of low-pressure cylinder has a strong nonlinear problem to the actual object of low-pressure cylinder inlet flow,and its gain varies with the size and positive and negative of inlet flow.The intake flow gain was classified according to the L-1 temperature of the low-pressure cylinder,and the method which can solve the object strong nonlinear problem was transformed into the mature multi-model control method.We proposed a method to identify the gain of inlet steam flow of low pressure cylin-der penultimate order temperature:the L-1 temperature and steam flow as characteristic variables,we used the fuzzy c-means clustering algorithm to divide the actual object gain into four types.Then,the two characteristic variables of the data to be discriminated were fused by D-S evidence theory,and the category corresponding to the maximum affilia-tion was the discriminant result.Taking the actual object of a power plant as an example,the D-S evidence theory can be used to discriminate the data to be discriminated based on the cluster center,and the discriminant result is more ac-curate and reliable than the ordinary Euclidean distance discriminant.
关键词
切缸运行/强非线性/模糊C均值聚类算法/D-S证据理论
Key words
cutting cylinder operation/strong nonlinearity/fuzzy c-means algorithm/D-S evidence theory
维普
万方数据