How can I use two different datasets as a training model for svm
From a proper methodological standpoint, you should do the scaling you're proposing after the two sets are merged.

Either way, the model is not going to be able to differentiate between, say, an anomalous reading from one generating process that falls into the range generated by the other generating process unless you also make a variable indicating the source system that the observation came from (assuming all else is equal).

You need to make sure that both sets of observations actually represent the same population of possible observations in order to make this modeling decision.