摘要
针对在细颗粒物采样监测装置中称重部分数据采集易受外部环境的影响,产生测量误差和干扰,导致称重部分的精度达不到要求,进而影响整个监测装置的测量精度和性能。通过经典的卡尔曼滤波算法,对传感器读取的数据进行处理,去除了极端数据,提高了称重部分的检测精度。通过MATLAB编写程序,对称重数据进行处理并图形化显示,满足称重部件精度要求±2mg的要求,验证了卡尔曼滤波算法在此应用的有效性。该方法可应用于相关领域的数据处理。
Part in fine particulate matter sampling monitoring device for weighing data acquisition is vulnerable to the influence of external environment, measurement error and interference, cause the weighing precision of the part can not meet the requirements, thus influence the measuring accuracy of the monitoring devices, and performance. By the classical kalman filter algorithm, the sensors read data processing, in addition to the extreme data, improves the detection precision of the weighing part. Through MATLAB program, the weighing data processing and graphical display, to meet the requirements of the weighing accuracy of parts plus or minus 2 mg, verified the effectiveness of kalman filtering algorithm in the application. This method can be applied to in the field of data processing.
出处
《电子测量技术》
2017年第2期105-108,共4页
Electronic Measurement Technology
