A Prediction Method of Gearbox Wear Volume Based on Ferrography Analysis and Grey System Theory

The gearbox is one of the key transmission parts of the special vehicle, and its wear volume relates directly to the service life of the vehicle. Aiming at accurately obtaining the trend of wear volume of gearboxes, a prediction model based on the grey system theory that introducing a correction factor is developed in this study. This model takes the ferrography analysis data of oil samples from gearboxes as the input characteristic variables and takes into account the factors, such as an unequal interval of prediction data, the interference of oil change, etc. A prediction method for the wearing volume of gearboxes is proposed. Research indicates that the prediction method reached the “first-class” precision by the posterior variance examination. Moreover, when λ=0.992, the modified model can achieve three-step accurate prediction, while the original GM (1,1) model can only achieve one-step accurate prediction.