Curve fit for sensor data

[Vindhyachal.Takniki]

1. Have a thermistor, data whose dataset is available not anything else from company except B value. Attached is data.   Resistance is "x" & temperature is "y"

Need to fit y =F(x)

2. Trying to make a equation for it and implement for 8 bit MCU, usin IAR IDE.

3. First I made this code, steinhart thermistor equation. calculated values of A,B,C from this site:  https://www.thinksrs.com/downloa...  . Put three values at -20C, 25C & 100C and get A,B,C

Its involves natural log and can fit data points, but I have to implement it on 8 bit MCU so it takes lots of space on it.

4. Then I used labview tool, to make equation , I have to break it down dataset into multiple sets for fitting 2nd order equation.

Here are coefficients for resistance values I got, for 2nd order

    if( (resistance <= 956040.0f) &&  (resistance >= 482170.0f) )
    {
        c0 = 14.5029518320319131f;
        c1 = -0.000057344817030149406f;
        c2 = 0.000000000021788855747503695f;
    }    
    else if(resistance >= 250140.0f)
    {
        c0 = 29.3136847463533279f;
        c1 = -0.000119496884518122221f;
        c2 = 0.0000000000876747221220605721f;    
    }    
    else if(resistance >= 130230.0f)
    {
        c0 = 45.3985586636038647f;
        c1 = -0.000249401966454676711f;
        c2 = 0.000000000352768556658954028f;    
    }    
    else if(resistance >= 71230.0f)
    {
        c0 = 62.1448935476119572f;
        c1 = -0.000506560472110208432f;
        c2 = 0.00000000135019658772898851f;    
    } 
    else if(resistance >= 39200.0f)
    {
        c0 = 79.7753263268828902f;
        c1 = -0.00100556530593662709f;
        c2 = 0.00000000491385322365418885f;    
    } 
    else if(resistance >= 21830.0f)
    {
        c0 = 98.8979251125107339f;
        c1 = -0.00198872984475097995f;
        c2 = 0.0000000176669521860767602f;    
    } 
    else if(resistance >= 12750.0f)
    {
        c0 = 118.809289117525665f;
        c1 = -0.00381338043851388829f;
        c2 = 0.0000000598289053823529209f;    
    } 
    else if(resistance >= 7327.0f)
    {
        c0 = 140.313484336487619f;
        c1 = -0.00722784306211046376f;
        c2 = 0.000000196440993753396293f;    
    } 
    else if(resistance >= 6683.0f)
    {
        c0 = 133.215333415477943f;
        c1 = -0.00480709971651089099f;
        c2 = 0.0f;    
    } 

Any other method, where I get better fit equation or lesser sub datasets I have to break to?

[GerdW]

Hi Vindhyachal,

with sensors like thermistors (NTC or PTC type) you often use additional resistors to form voltage dividers with the thermistor and also to linearize the voltage=f(temperature) behaviour, as described in this AppNote.

This Appnote also shows methods to convert the voltage signal back to a temperature:

• apply a polynomial on the linearized voltage signal
• using a LUT in the linearized voltage signal

For the NTCs I work with I choose the linearization resistor based on (mainly) two considerations:

• current through NTC to prevent self-heating
• best linearization behaviour depending on the expected typical temperature range to be measured

[Vindhyachal.Takniki]

Here is VI I made

It keep on decreasing dataset values unless error is less than defined error. This way i can divide equation into multiple parts.

[GerdW]

Hi Vindhyachal,

use the data to create a LUT, then interpolate linearly between two neighboring data points (should be accurate enough for a NTC sensor):

To improve code performance you need to create the LUT only once: all the code until Reverse1DArray should only be called once. You can even create a constant of the data after Reverse1DArray…

[Vindhyachal.Takniki]

@gerdw can u share the VI.

Dont have much exp in coding in labview. Could nt find the image icons some of them

[GerdW]

Hi Vindhyachal,

---

@Vindhyachal.Takniki wrote:

can u share the VI.

Dont have much exp in coding in labview. Could nt find the image icons some of them

---

It's a snippet. Read the LabVIEW help on "snippets"…

There are only 5 simple functions:

• SpreadsheetStringToArray
• IndexArray
• Index&BundleClusterArray
• Reverse1DArray
• Interpolate1DArray