In the case of fitting a curve to the typical thermistor, it is not easy.

Here is a link with a lot of info re these devices:

http://www.betatherm.com/beta_value_b.html

Radio Shaft sells one with a 10k resistance at 25%C - they put a table on
the package. I loaded the table into a regression analysis program I have.

Over the full range, it is impossible to fit a polynomial of any reasonable
degree with any accuracy whatsoever. And if you are going to do this on a
PIC with integer arithmetic (as opposed to using a floating point
package),  you need to use a polynomial fit.

Over a narrower range, you can linearize the thermistor by putting a
resistor in series with it.

Larry

At 11:37 PM 11/15/2002 +0000, you wrote:
>Lawrence Lile wrote...
>
> >That's one way to deal with it.
> >
> >A typical problem for me is interpolating thermistor data.  The thermistor
> >curve comes in chart form from the manufacturer, in very un-handy
> >increments.  It's quite a complex curve, and I think curve fitting it
> >would be a long involved task (unless Excel does this automatically
> >somehow? )  Linear curve fitting would be a cinch.   The only way I know
> >how to curve fit a nonlinear is, guess at the type of equation to use,
> >plot it next to your data, sum the squares of the differences,  then run a
> >linear regression on the results and use a Tools:GoalSeek on the results
> >to approach the minimum, then guess again at the type of equation to use
> >until you like the fit..  It is a time-consuming process, usually.
> >
> >Is there a more efficient way?
>
>Least-squares curve fitting will give you a set of coefficients
>for an interpolation polynomial and is especially useful where
>you can take a lot of data points, but the data are noisy.
>
>Another technique for generating interpolating polynomial
>coefficients is Newton's Method of Divided Differences.  This
>method will take (N) data points and give you the coefficients
>for a (N-1)th-order polynomial that passes precisely through the
>points.  The computations for this technique are easy, and it
>works very well when you have a limited amount of data but the
>data are largely noise-free.
>
>One writeup of Newton's Method that looks like a good summary of
>the technique is at:
>
>http://classes.cecs.ucf.edu/egn3420/klee/Notes/Interpolation/Interp_NDD.pdf
>
>but you can probably get more from Google.
>
>Dave D.
>
>--
>http://www.piclist.com hint: The PICList is archived three different
>ways.  See http://www.piclist.com/#archives for details.

Larry Bradley
Orleans (Ottawa), Ontario, CANADA

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