节点文献
基于滑窗式模型预估的超声波堰式流量测试研究
Research of Ultrasonic Barrier Flow Volume Measure Based on the Algorithm of Sliding Window Model Prediction
【摘要】 结合超声波堰式流量测试方法的研究 ,在信号处理领域首次引进了“滑动窗口”的概念 ,提出了一种滑窗式模型预估的算法 ,给出了RBF神经网络实现模型实时预估的方法 ,解决了液面不平引起流量测试故障实时恢复的问题 ,提高了堰式流量测试的精度。滑窗式模型预估的算法对其他物理量的测试同样有一定的指导作用。
【Abstract】 In accordance with the research of ultrasonic barrier flow volume measure. the conception of sliding window is applied to the signal measured. The algorithm of model prediction with RBF neural network is described. The fault caused by the fluctuation of the liquid surface is diagnosed and recovered. The precision of barrier flow volume measurement is improved. The algorithm of sliding window model prediction will be helpful to the research of other similar measurements.
【关键词】 滑动窗口;
模型预估;
超声波;
流量测试;
神经网络;
【Key words】 Sliding window Model prediction Ultrasonic wave Flow volume measure Neural network;
【Key words】 Sliding window Model prediction Ultrasonic wave Flow volume measure Neural network;
【基金】 江苏省软科学研究计划资助项目 (BJ98315 )
- 【文献出处】 电工技术学报 ,Transactions of China Electrotechnical Society , 编辑部邮箱 ,2001年05期
- 【分类号】TP274.5
- 【被引频次】2
- 【下载频次】56