A kind of multi-dot ensemble regression AI detector for lubricating oil additive content based on lambert-beer law.

In this work, we propose a Multi-dot Ensemble Regression AI detector (MER) based on the Lambert-Beer law. We pre-trained a model using the infrared spectral data of target additives collected in advance to detect the target additives in unknown oil samples. The algorithm's feasibility was validated by assessing the content of additives in a series of simulated commercial oil samples that were not part of the training set.