I am measuring the temperature from an RTD to produce a heating (or cooling) curve. The response is roughly sigmoidal, however it is noisy, and thus differentiating the data in real time does not give me a 'heating rate' of any sensible appearance.
Does anyone know how i could do this in real time rather than resorting to post processing?
One option I tried was to watch the data for the correct type of change, then only use that. I.e. when recording a heating process, the code watches for a rise in temperature. When this happens the new temperature and the current time is stored in an array. This is then compared to the previously recorded value, and the gradient of the increase is calculated and displayed. Of course when r
ecording a cooling process, a decrease is stored instead. This still gives me a very fuzzy differential, however it appears to show a 'real' response (has a maxima/minima and finally settles to 0).
Is there a 'better' method for doing this in real time?
Many thanks
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