Application of Discrete Wavelet Transform for Detection of Long- and Short-Term Components in Real-Time TOC Data

실시간 TOC 자료의 장.단기 성분의 검출을 위한 이산형 웨이블렛 변환의 적용

  • Published : 2006.09.30


Recently, Total Organic Carbon (TOC) which can be measured instantly can be used as an organic pollutant index instead of BOD or COD due to the diversity of pollutants and non-degradable problem. The primary purpose of the present study is to reveal the properties of time series data for TOC which have been measured by real-time monitoring in Juam Lake and, in particularly, to understand the long- and short-term characteristics with the extraction of the respective components based on the different return periods. For the purpose, we proposed Discrete Wavelet Transform (DWT) as the methodology. The results from the DWT showed that the different components according to the respective periodicities could be extracted from the time series data for TOC and the variation of each component with respect to time could emerge from the return periods and the respective energy ratios of the decomposed components against the raw data.


TOC(Total Organic Carbon);DWT(Discrete Wavelet Transform);Periodicity;Return period


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