摘要
在石油平台注水压力监测系统设计中 ,采用LabVIEW虚拟仪器平台 ,嵌入逼近能力强和收敛速度快的RBF神经网络 ,以人工环境实验数据为样本进行训练 ,实现了压力传感器的智能网络温度补偿。结果显示 ,此方法能够在压力、温度变化较大的恶劣环境下 ,获得很高的补偿精度。
Based on the research of design platform of virtual instrument(LabVIEW) and connected with neural network technology, in this paper, the intelligent temperature compensation for a pressure transducer is achieved. It is canbe applied to the design the injection supervisory and control system of the seawater on the oil platform. In the method of temperature compensation a RBF neural network is used. It is more accurate and converges quicker and the sample data can be acquired from an experiment with a artificial environment. The application of the result shows that this design can attain effective intelligent temperature compensation for a pressure transducer at atrocious environment of different pressure and temperature, and obtain excellent compensation precision.
出处
《中国海洋大学学报（自然科学版）》
CAS
CSCD
北大核心
2004年第6期1041-1044,共4页
Periodical of Ocean University of China
