The plasma generation and evolution processes are susceptible to matrix effects, environmental noise, pulse energy jitter, etc., resulting in the instability of the spectral data, which makes it difficult to ensure the validity of the monitoring criterion established based on a single spectral line. The monitoring criterion established by continuous multiple LIBS spectra combined with statistical methods can effectively improve the monitoring accuracy of paint removal based on LIBS technology. Based on a high-frequency nanosecond infrared pulsed laser paint removal LIBS online monitoring platform, the paper collected continuous multiple LIBS spectra of the paint removal process in real-time. After the spectral data were pre-processed by baseline correction and normalization, the spectral peaks of Ba Ⅰ (712.55 nm), Cr Ⅰ (357.48 nm), Cr Ⅰ (425.43 nm), Ti Ⅰ (427.45 nm), Cu Ⅱ (309.76 nm), Cu Ⅰ (484.22 nm) were used as the characteristic spectral lines and the paint removal effect was monitored. The intensity variation of the six characteristic spectral lines in different paint removal effects was studied, and the mapping relationship between different paint removal effects and the intensity variation of the selected characteristic spectral lines was established. The intensity of the above 6 spectral lines for each spectrum is extracted as data units. The data units of 10 consecutive spectral lines are used as data sets, and the data sets of each 10 iterations of the paint removal process are called data flow disks. The data cells and data sets in the data flow disk are analyzed. The confidence intervals are combined to determine the paint removal effect in the paint removal area in real-time. The monitoring criterion based on the data flow disk is obtained. The results show that this criterion can effectively monitor the paint removal effect in five categories: still on the top coat, completely removed top coat, still on the bottom coat, completely removed bottom coat, and substrate damage. The three-dimensional micro-pattern analysis showed that the accuracy of complete topcoat removal reached 1.2 μm, which effectively verified the applicability and stability of the LIBS-based data flow disc monitoring criterion.