Detection of Outliers in Sensor Data Based on Adaptive Moving Average Fitting

被引:6
|
作者
Xiong, Jianbin [1 ]
Wang, Qinruo [2 ]
Wan, Jiafu [3 ]
Ye, Baoyu [2 ]
Xu, Weichao [2 ]
Liu, Jianqi [4 ]
机构
[1] Guangdong Univ Petrochem Technol, Sch Comp & Elect Informat, Maoming 525000, Peoples R China
[2] Guangdong Univ Technol, Guangzhou 510006, Guangdong, Peoples R China
[3] S China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510006, Guangdong, Peoples R China
[4] Guangdong Jidian Polytech, Coll Informat Engn, Guangzhou 510515, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Moving Average Fitting; Ship Dynamic Positioning; Outlier Detection; Sensor; Adaptive Moving Average Fitting;
D O I
10.1166/sl.2013.2657
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In the sensor data of the dynamic positioning reference system for voyaging ships, there are often some abnormal deflection values which are called outliers. Discarding or replacing the outliers in real time is very important for the improvement of accuracy. In this paper an adaptive moving average fitting method is proposed to detect the outliers to be discarded or replaced in the sensor data of the reference system. This method defines an outlier detection criterion, adjusts the real-time outliers and judges the bandwidth through the adjustment to standards of parameters. The experimental results showed that our method can quickly and effectively solve the problem of real-time elimination of outliers.
引用
收藏
页码:877 / 882
页数:6
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