I'm using a MAX31865 RTD measurement IC, and a standard PT100 RTD to measure maple syrup temperature as it's boiling (219 degF). At ambient, the temperature measurement is reasonably stable. But, when boiling, I get a substantial amount of drift. I need stability preferably in the range of ±0.1 degF. In my data below, I'm already applying a pretty heavy rolling average. And, the data you see was taken in seconds, so it's fair to say I don't have an electrical noise issue (and there's really no frequency component). This looks like random drift. Do I have a measurement problem, or is this a physics problem? Does boiling liquid drift like this?
I took the suggestion of @sstobbe and replaced the RTD with a resistor of similar resistance that would give me a 219 degF reading. The reading is solid as a rock. The stability is actually within the precision of the device. I see a very infrequent change of around 0.016 degF (I should mention that I'm using an oversampling routine to increase the resolution). So, I am convinced that this is a physics problem.
Next, I think I will use use the suggestion of @10ppb and try to increase the thermal mass by using a metal block of some sort. Unfortunately, agitating the syrup, or giving it some sort of recirculation, is not an option. Any other mechanical suggestions on how to overcome the measurement volatility induced by the boiling?
UPDATE 2: I tried a couple things last night with a boiling pot of water. I wrapped the end of the RTD with about a half inch of aluminum foil. There was perhaps a 10-20% improvement. Then I put a test tube upright in the water bath, added a little bit of vegetable oil in the bottom of the test tube, then put the tip of the RTD in the oil. The thought being, the oil wouldn't boil (and cause measurement fluctuations), but would be a good conductor of heat. While the water was at 212 degF, I couldn't get the oil past 204 degF. I waited at least 20 minutes. I'm sure it would have reached equilibrium at some point, but it was clear this isn't going to work for my application.
Also, someone had mentioned that they were surpised that my data wasn't more erratic. It actually is quite erratic. The data shown has a heavy rolling average applied.