The invention relates to a correction method for on-line monitoring noisy data of oil chromatography. The method includes the following steps: step 1, collecting data of off-line tests and on-line monitoring of the oil chromatography; step 2, obtaining an optimal combination of significant parameters in a regression model of a support vector machine through a firefly algorithm; step 3, training the support vector machine with the small amount of accurate off-line test data of the oil chromatography obtained, and obtaining the regression model of the support vector machine; step 4, initializing a permissible deviation radius h of the on-line monitoring data, calculating a piecewise function between the off-line tests, and judging whether the on-line monitoring data of the oil chromatography is in a permissible error range of the model; step 5, correcting the on-line data; and step 6, according to the result of correction feedback of the on-site data, adjusting the parameters in the model. When the method is used for correction of the on-line data of the oil chromatography, the effect is stable, the result is accurate, the time is short, and the real-time performance is good, and the method is very suitable for correction of the one-site on-line data of the oil chromatography.