This invention discloses a
machine learning-based method and
system for predicting low
oil pressure faults, relating to the field of engine oil maintenance. The method includes the following steps: acquiring
oil pressure samples within a prediction period, with each sample corresponding to a vehicle; training a
machine learning model on all
oil pressure samples to obtain a fault prediction model; and calculating the fault prediction result using the oil
pressure data of the vehicle under test. This invention can obtain a fault prediction model through
machine learning training based on relevant oil
pressure data. This model can calculate and push the probability of an oil pressure fault occurring in the future in real time, thereby providing timely warnings to users, reminding them of potential faults, and guiding them to change the oil in advance to avoid
driving safety issues caused by oil pressure-related faults.