KY-026 Flame Detection Module Tutorial: Infrared Flame Sensing, Threshold Tuning, and Arduino Examples

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This tutorial is a comprehensive, practical guide to the <strong>IR Receiver &amp; Flame Detection Module (KY-026) (Leobot Product #215). It explains how infrared flame sensing works, how the KY-026 module is built, how to tune sensitivity correctly, and how to use both the analog and digital outputs reliably with Arduino for flame presence detection, alarms, and safety projects.

KY-026 Flame Detection Module Tutorial: Infrared Flame Sensing, Threshold Tuning, and Arduino Examples

This tutorial is a comprehensive, practical guide to the IR Receiver & Flame Detection Module (KY-026) (Leobot Product #215). It explains how infrared flame sensing works, how the KY-026 module is built, how to tune sensitivity correctly, and how to use both the analog and digital outputs reliably with Arduino for flame presence detection, alarms, and safety projects.

Tutorial Beginner ? Intermediate Flame Detection Infrared LM393 Safety Arduino
What this module is: A flame detection sensor that uses an infrared-sensitive photodiode tuned to the wavelength range emitted strongly by open flames. An onboard LM393 comparator provides a clean digital output, while the analog pin exposes raw signal intensity.
Important limitation: The KY-026 detects infrared light, not β€œfire” itself. Hot objects, sunlight, incandescent bulbs, or IR heaters can trigger false positives if not handled carefully.

1) What the KY-026 does (and does not do)

The KY-026 module detects the presence of a flame by sensing infrared radiation typically emitted by burning materials (around 760–1100 nm).

Good use cases

  • Flame presence detection
  • Fire alarm triggers (with validation)
  • Educational demonstrations
  • Robotics flame-finding projects

Not suitable for

  • Precise temperature measurement
  • Smoke detection (use smoke sensors instead)
  • Outdoor detection without shielding and filtering

2) How infrared flame detection works

Flames emit strong infrared radiation due to excited molecules and hot particles. The KY-026’s IR photodiode converts this radiation into a small electrical signal.

  • Stronger flame ? stronger IR signal
  • Distance and angle strongly affect response
  • Flickering flames produce fluctuating signals
Key insight: The characteristic flicker of a flame (roughly 1–20 Hz) can be used in software to distinguish flames from constant IR sources.

3) Module overview and internal circuitry

The KY-026 typically includes:

  • Infrared photodiode or phototransistor
  • LM393 comparator
  • Potentiometer for threshold adjustment
  • Status LED (digital output indicator)

The analog signal feeds the comparator, which produces a digital HIGH/LOW output depending on the set threshold.


4) Pinout and electrical characteristics

Pin Label Description
1 AO Analog output (IR intensity)
2 GND Ground
3 VCC Supply voltage (3.3V–5V)
4 DO Digital output (threshold-based)
  • Compatible with 3.3V and 5V microcontrollers
  • Digital output is TTL-level

5) Analog vs digital output behavior

Analog Output (AO)

  • Represents raw IR intensity
  • Higher value ? stronger IR detected
  • Used for calibration and advanced logic

Digital Output (DO)

  • Comparator-based ON/OFF signal
  • Threshold adjustable via potentiometer
  • Often active LOW when flame is detected (verify)

6) Sensitivity and threshold adjustment

  1. Power the module and connect DO to a digital input.
  2. Open Serial Monitor to observe DO state.
  3. Introduce a flame at the desired detection distance.
  4. Turn the potentiometer slowly until DO switches reliably.
  5. Verify stability by removing and reintroducing the flame.
Do not overtune: Excessive sensitivity causes false triggers from ambient IR. Tune for reliable detection, not maximum range.

7) Wiring to Arduino


KY-026 VCC ? Arduino 5V (or 3.3V)
KY-026 GND ? Arduino GND
KY-026 AO  ? Arduino A0
KY-026 DO  ? Arduino D2
    

8) Arduino Example 1: Analog flame intensity


/*
  KY-026 Flame Sensor - Analog Read
  Product #215
*/

const int FLAME_AO = A0;

void setup() {
  Serial.begin(9600);
}

void loop() {
  int value = analogRead(FLAME_AO); // 0–1023
  Serial.print("IR Intensity: ");
  Serial.println(value);
  delay(200);
}
    

9) Arduino Example 2: Digital flame detection


/*
  KY-026 Flame Sensor - Digital Detection
*/

const int FLAME_DO = 2;

void setup() {
  pinMode(FLAME_DO, INPUT);
  Serial.begin(9600);
}

void loop() {
  if (digitalRead(FLAME_DO) == LOW) {
    Serial.println("Flame detected");
  } else {
    Serial.println("No flame");
  }
  delay(200);
}
    

10) Arduino Example 3: Flame alarm logic


/*
  Simple Flame Alarm Logic
*/

const int FLAME_DO = 2;
const int BUZZER  = 8;

void setup() {
  pinMode(FLAME_DO, INPUT);
  pinMode(BUZZER, OUTPUT);
}

void loop() {
  bool flame = (digitalRead(FLAME_DO) == LOW);

  if (flame) {
    digitalWrite(BUZZER, HIGH);
  } else {
    digitalWrite(BUZZER, LOW);
  }
}
    

11) Detection angle and distance

  • Typical detection range: up to ~50–80 cm for small flames
  • Detection angle: roughly 60Β° (module-dependent)
  • Best detection when flame is centered in field of view

12) Sunlight and false triggers

  • Sunlight contains strong IR ? shield sensor if possible
  • Incandescent bulbs emit IR ? may trigger detection
  • Use flicker detection or multiple samples for validation
  • Combine with temperature or smoke sensors for safety systems

13) Typical applications

  • Fire detection alarms
  • Flame-following robots
  • Industrial safety monitoring
  • Educational sensor experiments

14) Troubleshooting

Always triggered

  • Sensitivity set too high
  • Direct sunlight or IR source nearby
  • Incorrect wiring

Never triggered

  • Sensitivity too low
  • Flame too far or off-axis
  • Wrong assumption about DO polarity

15) Quick checklist


KY-026 Flame Detection Module (#215) Checklist
---------------------------------------------
? Power with 3.3V–5V
? Use AO for calibration and advanced logic
? Use DO for simple flame detection
? Adjust potentiometer under real conditions
? Expect IR-based false triggers; validate in software
? Shield from sunlight when possible
? Combine with other sensors for safety-critical systems
    

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