I reprocessed some old data to add some software temperature compensation for the Rev. P wind sensor. The sensor itself has hardware temperature calibration built in, but the hardware compensation isn’t perfect.
You can see by these trend lines in this ADCunit vs static pressure graph that the curves diverge slightly at the upper end of the graph. I used the static pressure data from a pitot tube along with humidity and temp data, to convert the pitot tube data to wind velocities. I then set up a regression and derived an equation that matched the curve of the sensor.
I did the regression, solving for the output voltage instead of the wind speed, as I probably should have done. When the regression was done I had to factor the final equation, solving for the wind speed (in MPH) instead of for the volts, which is what the sensor outputs. This resulted in slightly less clear math, than it might have been, had I done the regression the other way around. I’m far from an expert Excel jockey, but knowing how to use the “Solver” in Excel makes me feel like at least I could play one on TV, after maybe a clean up and a shave.
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