基于数据融合的压力传感器静态特性研究

Study on static characteristic of pressure sensor based on BP data fusion

通常传感器的输出值不仅决定于目标参量,还会受到非目标参量的影响。为此,采用BP神经网络技术对其进行数据融合处理,以消除非目标参量对传感器输出值的影响。试验结果表明:该方法很好地抑制了传感器的交叉灵敏度,提高了其测量准确度。

Usually,the output of pressure sensor not only depends on objection parameter,but also is affected by non-objection parameter. In order to eliminate affection caused by non-objection parameter, BP neural network data fusion is adopted. Experiment results show that the method can well restrain cross-sensitivity of sensor and improve measuring precision.