基于多传感器信息融合的涡街信号处理方法  

Vortex signal processing method based on multi-sensor information fusion

作　　者：宋开臣[1] 曾瑶[1] 叶凌云[1] 

机构地区：[1]浙江大学生物医学工程与仪器科学学院,浙江杭州310027

出　　处：《浙江大学学报（工学版）》2016年第7期1307-1312,1352,共7页Journal of Zhejiang University：Engineering Science

摘　　要：针对压电式涡街流量计抗干扰性能差的缺点,提出基于多传感器信息融合的涡街信号检测方法.在该测量系统中,差压传感器测得钝体前、后的平均差压,压电传感器检测钝体下游涡街信号的频率,通过无迹卡尔曼滤波(UKF)算法将以上两种信息进行数据融合,有效提高了数字带通滤波器的锁定精度.在搭建的振动实验平台上验证了该方法的可行性,对比分析了本文方法和传统方法的测量结果.实验表明:采用该处理方法能够有效抑制外界的强振动噪声干扰对流速测量的影响,当最大振动噪声干扰的强度为涡街信号的4倍时,测量精度可以达到1%,增强了压电式涡街流量计的抗振能力,提高了流量测量精度.A vortex signal detection method based on multi-sensor information fusion was proposed in view of the poor anti-jamming performance of piezoelectric vortex flowmeter. In the measuring system, the average differential pressure before and after bluff body was measured by differential pressure pickup while the frequency of downstream vortex signal of bluff body by piezoelectric sensor. The two data above were fused by means of unscented Kalman filter (UKF), which effectively improved the locking precision of the digital band-pass filter. The feasibility of the method was verified through related experiments. The results of the method and the traditional method were comparatively analyzed. Experimental results show that the processing method can effectively restrain the impact of strong vibration noise interference from the outside on flow velocity measurement, which enhances the anti-vibration ability of piezoelectric vortex flowmeter and improves the flow measurement accuracy. When the vibration noise's maximum intensity was four times stronger than the vortex signal, the measurement accuracy could achieve 1%. © 2016, Zhejiang University Press. All right reserved.

关 键 词：压电式涡街流量计 多传感器信息融合 无迹卡尔曼滤波 抗振能力 

分 类 号：TH814[机械工程—仪器科学与技术] TP274[机械工程—精密仪器及机械]