基于One-Class SVM的凝泵入口滤网堵塞预警模型开发与应用

Development and application of an early warning model for condensate pump inlet filter clogging based on One-Class SVM

电厂凝结水泵入口滤网在机组长周期运行时,由于凝结水水质变差,凝结水中杂质增多,易导致凝结泵入口滤网堵塞现象的发生。该研究采用基于单类支持向量机(One-Class SVM)算法,建立了凝结水泵入口滤网堵塞智能诊断与预警模型。通过提取与凝结水泵入口滤网堵塞具有因果联系的主要参数的历史数据,对智能预警模型进行训练优化,并完成了相关测试。研究结果表明,该模型可以有效对凝结水泵入口滤网发生堵塞现象进行识别,准确率达到99.96%,误报率低,召回率达到90.20%,准确率达到93.18%,满足工业生产需求,可有效指导机组操作人员及时采取相应措施,避免机组因非正常停机而造成经济损失。

During the long-term operation of the condensate pump inlet filter in the power plant,due to the deterioration of the condensate water quality and the increase of impurities in the condensate water,it is easy to cause the blockage of the condensate pump inlet filter.An intelligent diagnosis and early warning model of condensate pump inlet filter blockage is established based on One-Class SVM algorithm.By extracting the historical data of the main parameters with causal relationship with the inlet filter plugging of the condensate pump,the intelligent early warning model is trained and optimized,and the related tests are completed.The results show that this model can effectively identify the clogging phenomenon of the inlet filter of the condensate pump,and the accuracy rate reaches 99.96%,with low false alarm rate,the recall rate of the model reaches 90.20%and the accuracy rate reaches 93.18%,which meets the needs of industrial production.It can effectively guide the operator of the unit to take corresponding measures in time to avoid economic losses caused by abnormal shutdown of the unit.