反渗透海水淡化系统\

为了提高案例推理方法在反渗透膜故障诊断中的性能，首先，采用模糊自适应谐振理论（fuzzy adaptive resonance theory，Fuzzy ART）网络将源案例划分为多个聚类簇；然后，删除每一个聚类簇内的噪声案例和冗余案例，并保留离群案例，从而实现案例库的维护；最后，将这种维护策略和案例推理方法应用于反渗透膜故障诊断，并使用某冶炼厂反渗透膜故障的历史数据进行对比实验，验证了改进的案例推理方法在诊断准确性能方面的优势.

Research advances in organic fouling of reverse osmosis membrane

To improve the performance of case-based reasoning in reverse osmosis membrane fault diagnosis, the Fuzzy ART network was first used to divide the source case into multiple clusters. Then, the noise cases and the redundancy cases in each cluster were deleted and the outliers were reserved to realize the maintenance of the case base. Finally, this maintenance strategy and case-based reasoning method were applied to the fault diagnosis of the reverse osmosis membrane, and the comparative experiment was carried out by using the historical data of the reverse osmosis membrane fault in a smelter, which verified the advantages of the improved CBR method in the diagnosis accuracy, and the research has certain practical application value.