期刊
JOURNAL OF HYDRAULIC ENGINEERING
卷 139, 期 7, 页码 785-793出版社
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)HY.1943-7900.0000734
关键词
Acoustic techniques; Data analysis; Algorithms; Hydraulics; Acoustic doppler velocimeter (ADV); Despiking; Kernel density; Outlier; Jet
资金
- NSERC postgraduate scholarship
- Alberta Ingenuity scholarship
Acoustic doppler velocimeter (ADV) data can be contaminated by spikes from various sources. Available despiking methods were found to encounter difficulties in despiking ADV data from a turbulent jet flow. An iteration-free despiking algorithm was developed for highly contaminated ADV data by applying a bivariate kernel density function and its gradient to separate the data cluster from the spike clusters. It is shown that the new method overcomes some of the deficiencies of the existing despiking methods. (C) 2013 American Society of Civil Engineers.
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