基于支持向量回归的多参数融合的蒸汽发生器水位信号预测

Prediction for Water Level of Steam Generator Based on Multi-signal Fusion by Support Vector Regression

舰船核动力装置负荷变化过程中,蒸汽发生器水位经常出现大幅波动甚至假水位现象。同时,水位测量通道故障时有发生。这些问题严重影响着给水流量的自动调节和操纵员对系统运行状态的准确判断。为此提出一种基于多信号重构的方法,对蒸汽发生器水位信号进行预测,该方法增加影响水位变化的相关信号作为预测输入信息。与单纯分析历史水位变化规律而进行的预测方法相比,提高了预测的准确性、稳定性、可靠性,并能进行较长期的预测。

During change of marine nuclear power plant load ,the water level of steam generator often waved heavily and even more false water level occurred .In the mean-time ,water level measurement channels failed once in a while .All problems affected heavily self-regulation of water level and operator ’s correct judgment on the operation states .Therefore ,a water level predicting method based on multi-signal reconstruction was brought forward .This method added relevant signals which may affect water level change as input information for prediction .Comparing with predicting method based on analyzing the history of water level change only ,this method improves accuracy ,stabili-ty and reliability of prediction ,and supports predicting in longer term .