在线监测冷凝器污脏程度的新方法

A Novel Method for On-line Measurement of Fouling in Condenser

针对现有测量冷凝器换热管污脏方法的不足,提出了一种在线监测污脏程度的新方法。该方法选取传热端差作为研究 对象,综合考虑各因素对端差的影响,运用模糊建模技术成功实现冷凝器污脏、工况参数变化对端差影响的分离,可准确地在 线监测冷凝器污脏。在模糊建模中,采用T-S模型描述变工况端差,研究了一种基于相似性判别的模糊聚类算法自动确定合 适的聚类组数目,并用实数编码的遗传算法优化全局参数,从而获得了规则简化的、具有较高精度的模糊模型。根据此方法, 进行了现场试验。试验结果表明该方法能准确、有效地监测冷凝器污脏,并在冷凝器出现堵管时,取得比热阻法更好的测量效 果。

Aiming at overcoming the deficiency of available methods for measuring fouling in condenser,a novel method is proposed.In the method,terminal temperature difference is chosen to reflect the fouling state,fuzzy modeling is applied to separate the influences of both the fouling and off-design condition on terminal temperature difference.During fuzzy modeling,T-S model is employed to depict off-design condition terminal temperature difference,a fuzzy clustering algorithm based on similarity is proposed to determine the optimum number of clusters and a real-coded genetic algorithm is adopted to optimize model parameters.All these techniques make the fuzzy model simple and accurate.Based on it,various experiments on an actual condenser are conducted.The results prove the method to be effective.