Gross-error Detection for Observation Data Series
Huang Hongn · Hydropower Automation and Dam Monitoring · 2006
Based on the theories of wavelet analysis and unascertained filtering, the methods for detecting and eliminating gross-error in observation data series are studied. The analysis and comparison of two methods show that the detecting results are basically consistent, and they both have the value of application. Furthermore, the advantages and limitations of these two methods are analyzed, which provides reference for the practical application. Based on the characteristics of these two methods, an integrated method is proposed to detect gross-errors.