Sensors & Measurement · Study deck

Sensor Calibration: Measurement Foundations

A sensor can be precise and still report the wrong value.

Physics Phoebe is your guide for this deck.

sensorcalibration

Physics Phoebe, the module guide, in a scene from this chapter.

After studying this chapter

Learning objectives

You will be able to:

Explain calibration fundamentals: Describe why sensors need calibration and how raw readings differ from true values
Implement two-point calibration: Calculate offset and gain correction using low and high reference points
Apply signal conditioning: Configure moving average filtering to reduce noise in sensor readings
Evaluate raw vs calibrated data: Measure the impact of calibration on measurement accuracy

Major section

Most Valuable Understanding (MVU)

Every real sensor has manufacturing variations that cause its readings to deviate from the true value.

Two-point calibration uses two known reference points to calculate correction coefficients that map inaccurate raw readings to accurate calibrated values.

Calibration transforms inaccurate raw sensor readings into precise, reliable measurements

Major section

Introduction

In this hands-on lab, you will build a complete sensor calibration system using an ESP32 microcontroller in the Wokwi browser-based simulator.

You will wire a potentiometer to simulate a sensor with offset and gain errors, implement two-point calibration to correct those errors, and apply a moving average filter for noise reduction.

Major section

Calibration Matters

Think of calibration like adjusting a musical instrument.: Even a brand-new guitar needs to be tuned before it plays the right notes.

Sensors are similar - they need to be "tuned" to give accurate readings.
Manufacturing variations: No two sensors are exactly identical, just like no two guitars are perfectly tuned from the factory.

Major section

Calibration Matters (continued)

Environmental factors: Temperature, humidity, and age can cause sensors to drift over time.

Component tolerances: The electronic parts inside sensors have slight variations.
The mathematical approach:: Instead of just "subtract 2", calibration gives us a formula: corrected = raw × gain + offset.
Offset fixes constant errors (like always being 2 degrees off).

Major section

Teaching Sensors Truth

Sammy always reads too high - that is an offset error (always adding a constant).

But notice something: at 10 degrees Sammy is off by 3, and at 25 degrees Sammy is off by 3 too.
That constant +3 shift is a pure offset error.
You could fix it by subtracting 3 from every reading.

Major section

Teaching Sensors Truth (continued)

Sammy says "It's 3 degrees!" Oops - that is Sammy's offset error! (0 + 3 = 3).

Sammy says "It's 103 degrees!" Still 3 degrees too high - the offset is consistent! (100 + 3 = 103).
Lila the Light explains: "It's like being a translator!
Max the Motor adds: "I need calibration too!

Major section

Folded Error And Quality Metrics Notes

Offset shifts the whole response by a constant amount, so a zero reference can be wrong even when the slope is usable.

Gain changes the slope, so error grows as the true value moves away from the reference point.
These metrics are evidence for the tested range only.

Deck summary

Key takeaways

Every real sensor has manufacturing variations that cause its readings to deviate from the true value.

In this hands-on lab, you will build a complete sensor calibration system using an ESP32 microcontroller in the Wokwi browser-based simulator.
Think of calibration like adjusting a musical instrument.: Even a brand-new guitar needs to be tuned before it plays the right notes.
Environmental factors: Temperature, humidity, and age can cause sensors to drift over time.
Sammy always reads too high - that is an offset error (always adding a constant).

Retrieval practice

Recall check

Physics Phoebe says: answer from memory, then check your reasoning.

Q1The calibration lab has both systematic error and noisy readings. Which operation specifically targets the random variation?

ATreating a reference point as a filter window

BReplacing the simulated sensor with a dashboard label

CThe moving average filter

DChanging the calibration offset for each noisy sample

Show answer

Answer: C The introduction assigns noise reduction to averaging and offset/gain correction to calibration.

Q2A thermometer reads a constant amount too hot across the tested range. Which calibration term addresses that pattern?

AThe display refresh interval

BThe offset correction

CThe gain correction for proportional error

DThe reference count without a correction formula

Show answer

Answer: B The chapter distinguishes a constant error from a gain or scaling error.

Print reference

Answers

Answer key.

C · The introduction assigns noise reduction to averaging and offset/gain correction to calibration.
B · The chapter distinguishes a constant error from a gain or scaling error.