Sensor Calibration Process
Compare raw sensor readings with trusted references, fit a correction model, and verify the error that remains.
Sensor Calibration Process
Watch a sensor compare itself with trusted reference points, fit a correction equation, and prove whether the remaining error is small enough for deployment.
Calibration starts with known values from a trusted standard, not with the sensor under test.
Offset shifts the line; gain changes the slope; non-linearity bends the response.
A useful calibration checks points that were not used to create the equation.
A calibration record should state method, references, residual error, tolerance, and next check date.
Known Reference
Stable physical value is prepared.
Raw Sensor
The device reports its uncorrected value.
Fit Equation
Reference and raw values produce a correction model.
Apply Correction
New readings are translated through the model.
Verify Result
Remaining error is compared with tolerance.
Fit raw and calibrated response
displayed value vs true valueSingle-Point Rule
Single-point calibration only shifts readings by one offset.
calibrated = raw + offsetTwo-Point Rule
Two-point calibration fits a straight line through low and high references.
gain = (ref2 - ref1) / (raw2 - raw1)Multi-Point Rule
This animation uses quadratic least-squares for a curved sensor response.
true = a raw^2 + b raw + cCalibration Quick Reference
Calibration is a comparison process. The reference instrument or reference condition is treated as the trusted value; the sensor under test is adjusted mathematically.
- Offset error means the whole response is shifted.
- Gain error means the slope is too steep or too shallow.
- Non-linearity means one straight line cannot fit the whole range well.
- Noise and repeatability limit how much precision the correction can prove.
Method Selection
Choose the method to match the error pattern and the risk of the application.
- Use single-point only for quick field checks near one operating value.
- Use two-point for most linear sensors across a known range.
- Use multi-point when the residual plot still bends after a straight-line fit.
- Verify with points that were not used to fit the model.
Technical Accuracy Notes
The plotted sensor model is a teaching model, not a datasheet model. Raw readings are generated with offset, gain, curvature, drift, and deterministic repeatability noise so learners can see why different calibration methods behave differently.
- Single-point: corrected = raw + offset, using one reference point.
- Two-point: corrected = gain * raw + offset, fitted through two reference points.
- Multi-point: corrected = a * raw^2 + b * raw + c, fitted by least-squares to five reference points.
- RMSE and maximum error are calculated over the displayed operating range, in the scenario units.
- A real traceable calibration also needs uncertainty budget, standards traceability, environmental conditions, and controlled procedures.
Calibration Record Checklist
A useful calibration record should let another person understand what was calibrated, how it was checked, and when it must be checked again.
- Sensor ID, date, operator, and firmware or hardware revision.
- Reference standard ID, certificate date, and stated uncertainty.
- Reference points, raw readings, correction equation, tolerance, and pass/fail result.
- Environmental conditions and next calibration interval.
Compare Methods
Select the pressure scenario, increase drift, and compare single-point against two-point. Notice where the error grows.
Find Curvature
Select the CO2 room scenario and switch to the residual view. A curved residual pattern explains why multi-point calibration helps.
Set Tolerance
Tighten the tolerance until a method fails. The same sensor can be acceptable for one job and unacceptable for another.