If the training data is all gas turbines that you own, why do you care about having the ML model at all? You already have complete knowledge of the state of all your gas turbines.

There's no point to having an ML model unless you are applying it to something outside of the training data.

If you plan on applying the model to different turbines, then there is potential for sample bias in which turbines you selected. If you apply it to the same turbines at some point in the future, then you sampled points in time so there is a potential for sample bias based on which points in time you selected.

There is no way of completely avoiding the potential for sample bias unless you completely abandon ML as a useful concept.