Open AccessA peak recognition algorithm designed for chromatographic peaks of transformer oil
Author(s) -
Linjun Ou,
Jian Cao
Publication year - 2014
Publication title -
sepu/chinese journal of chromatography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.171
H-Index - 19
eISSN - 1872-2059
pISSN - 1000-8713
DOI - 10.3724/sp.j.1123.2014.05008
Subject(s) - transformer oil , transformer , algorithm , square wave , logarithm , derivative (finance) , analytical chemistry (journal) , mathematics , chromatography , voltage , chemistry , engineering , mathematical analysis , electrical engineering , financial economics , economics
In the field of the chromatographic peak identification of the transformer oil, the traditional first-order derivative requires slope threshold to achieve peak identification. In terms of its shortcomings of low automation and easy distortion, the first-order derivative method was improved by applying the moving average iterative method and the normalized analysis techniques to identify the peaks. Accurate identification of the chromatographic peaks was realized through using multiple iterations of the moving average of signal curves and square wave curves to determine the optimal value of the normalized peak identification parameters, combined with the absolute peak retention times and peak window. The experimental results show that this algorithm can accurately identify the peaks and is not sensitive to the noise, the chromatographic peak width or the peak shape changes. It has strong adaptability to meet the on-site requirements of online monitoring devices of dissolved gases in transformer oil.