Load Cell Calibration Calculator

Work out load cell calibration instantly with clear inputs, formula shown and shareable results.

About Load Cell Calibration Calculator

Full scale output is sensitivity in mV/V times excitation voltage, so a 2 mV/V cell at 10 V gives 20 mV at rated load. Output is linear with load, giving 40 microvolts per kilogram on a 500 kg cell — a signal small enough that excitation stability directly limits accuracy.

Formula

Load cell output

full scale mV = sensitivity (mV/V) x excitation (V); output = full scale x load / rating

Worked example

With the default values below, Load Cell Calibration Calculator returns Output at this load of 12.80000. Change any input above and every figure here is recalculated in your browser.

Inputs used

Load cell rating: 500 kg
Rated output: 2 mV/V
Excitation voltage: 10 V
Applied load: 320 kg

Results

Output at this load: 12.80000 mV
Full scale output: 20.00 mV
Output per kilogram: 0.040000 mV/kg
Percentage of rated capacity: 64.00% %

Step by step

1Values used
2Load cell output
3Output at this load= 12.80000 mV
4Full scale output= 20.00 mV
5Output per kilogram= 0.040000 mV/kg
6Percentage of rated capacity= 64.00 %

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax or compounding frequency into account.
Figures are rounded for display to 6 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Why does excitation voltage matter?

Output is proportional to it, so any drift appears directly as a weight error. Ratiometric measurement, using the excitation as the ADC reference, cancels this.

Should I use the full capacity?

Aim for 50-80% of rating at maximum load. Too little uses only part of the signal range; too much risks overload and non-linearity.