基于粗糙集和遗传算法的水轮发电

针对水轮发电机组故障监测中的大量数据，为了提高故障诊断效率,考虑将粗糙集理论和遗传算法引入水轮发电机组故障诊断中。利用粗糙集获取水轮发电机组故障信息决策表，再用遗传算法的全局搜索技术，对决策表进行约简，找出对故障分类起主要作用的特征，并提取诊断规则。通过对具体诊断实例研究表明：该方法在水轮发电机组故障诊断中具有较高的可行性和有效性。

Hydroelectric Units Fault Diagnosis Based on Genetic Algorithm and Reduction Rough Set Theory

Aiming at the plentiful data of fault monitoring of hydroelectric units, the rough set theory and genetic algorithms are introduced into the hydroelectric units fault diagnosis in order to improve the fault diagnosis efficiency. The fault information table of hy droelectric units is obtained based on rough set theory, and is simplified based on the global searching technique of the genetic algorithm. The main features which are important to the fault classification are searched, and the diagnosis rules are obtained. Case study shows that this method is feasible and effective to be used in the hydroelectric units fault diagnosis.