数据协调方法在传感器故障监测中的应用

Data reconciliation for sensor fault monitoring

以某电厂1 000MW机组高压给水加热器及抽汽管道系统为对象,研究数据协调方法在传感器故障检测、识别和数据重构中的应用。数据协调过程中,采用主导因素法建立设备特性参数模型,构建参数间的特性约束关系。仿真案例研究结果表明:该方法能够有效检测和识别传感器故障,故障数据重构平均相对误差2.42%,具有较高精度。

Data reconciliation method is used to improve sensor fault detection,identification and data rebuilding for a high pressure feedwater heater and extraction steam pipe system in a 1 000MW coal-fired power generation unit.The dominant factor modeling method is used to build the characteristic constraint relationships between the parameters.A case study shows that this method can efficiently detect,identify and rebuild data after sensor faults with an average relative error in the rebuilt data of 2.42%.