摘要
为了更好地进行水轮机调速器的故障诊断,利用D-S证据推理对不同的神经网络技术得出的结果进行数据融合。仿真结果证实,利用D-S证据推理所得出的结论比单纯利用神经网络得出的结果要理想,它减小了误诊率,提高了水轮机故障诊断的准确率。
In order to better estimate the fault diagnosis of the hydraulic turbine governing system, the D - S evidential reasoning is used for data fusion with the result of different neural networks. By simulation, it can be clearly found that the result of the data fusion is much better than that of the neural networks. It decreases the fault ratio, and increases veracity of the fault diagnosis of hydraulic turbines.
出处
《计算机与数字工程》
2006年第8期87-89,163,共4页
Computer & Digital Engineering
关键词
水轮机调速器
故障诊断
神经网络
D—S证据推理
hydraulic turbine goveming system, fault diagnosis, artificial neural, D- S evidential reasoning
