中文摘要：

根据Gelormino管网LTI离散模型,结合实际推导出可行的广义数据模型,提出了系统辨识方法：（1）通过数据挖掘技术实现模型结构聚类;（2）采用相关性分析技术确定模型结构;（3）采用最小二乘法及渐消记忆递推最小二乘法实现模型参数辨识及在线辨识。实例计算结果表明,该方法建立的数据模型可以很好地模拟并预测泵站的污水流入量、污水总量以及水位变化情况,可用于指导城市污水泵站的运行管理。

英文摘要：

Based on the Gelormino sewer LTI discrete model,the paper deduced a feasible generalized data model with the practical requirements,and proposed system identification method：（1）utilizing data mining technology to achieve clustering model structure,（2）applying correlation analysis to determine model structure,and（3）using least squares method and the fading memory recursive least squares method to achieve model parameter identification and on-line identification.The actual calculation result shows that the data model established by the above method can simulate and predict the inflow,the sewage and the water level changes,it can be used to guide the operation and management of urban sewage pumping system.