基于CVA的换流阀冷却系统故障诊断技术研究

Study on Fault Diagnosis Technology of Converter Valve Cooling System Based on CVA

针对换流站阀冷系统运行过程中监测变量的复杂性,缺乏全面的故障诊断手段,基于规范变量分析(CVA)实现了阀冷系统故障诊断,并根据贡献图准确定位故障原因。首先,建立了阀冷系统数据驱动的故障诊断模型,提取了阀冷系统运行参数,确定了CVA算法的参量。其次,基于该算法,通过对阀冷系统典型故障案例分析验证了模型的准确性,结果表明算法可以快速判断系统异常并优于主元分析算法,实现故障预警。最后,基于贡献图分析,计算了不同参数的贡献率,精确定位故障数据位置。通过对换流站运行数据进行试验诊断,发现CVA算法能够有效地提取故障特征并诊断故障,研究结果可为现场阀冷系统运维提供有效支撑。

In view of the complexity of monitoring variables during the operation of valve cooling system in converter station and the lack of comprehensive fault diagnosis means,the fault diagnosis of the valve cooling system is achieved based on the canonical variable analysis(CVA),and the fault cause is accurately located in accordance with the contribution diagram.Firstly,the data-driven fault diagnosis model of the valve cooling system is set up,the operating parameters of the valve cooling system are extracted,and the parameters of the CVA algorithm are determined.Then,based on this algorithm,the accuracy of the model is verified by analyzing typical fault cases of the valve cooling system.The results show that the algorithm can quickly judge system abnormalities,is superior to the principal component analysis algorithm and can achieve early warning of fault.Finally,based on the contribution graph analysis,the contribution rates of different parameters are calculated to accurately locate the fault data location.It is found through the test diagnosis of the operation data of converter station that the CVA algorithm can effectively extract the fault features and diagnose the fault,and the research results can provide effective support for the operation and maintenance of valve cooling system at site.