A data acquisition system based on outlier detection method for weighing lysimeters

Abstract

The weighing lysimeters provide scientist the basic information for research related to the evapotranspiration, high quality of the collected data from lysimeters is of great significance. However there are many factors that can affect the measurement accuracy of the weighing lysimeter. In this paper, a data acquisition system was developed to collect the data from 24 weighing lysimeters. The calibration process of the load cell was described. An outlier detection method based on the 3-sigma rule and the median filter was proposed to improve the measurement accuracy of the weighing lysimeters. The performance of the proposed method was compared with the method based on Savitzky-Golay filter. Results show that the standard deviations of the 15-point median filter and the 15-point Savitzky-Golay filter applied to the 283 data points were 0.413Kg and 0.422Kg respectively, which means that the performance of the median filter was better than the Savitzky-Golay filter. Moreover the outliers were successfully eliminated using the median filter and were not removed by the Savitzky-Golay filter. © 2012 IFIP International Federation for Information Processing.