http://davidegironi.blogspot.it/2017/05/mq-gas-sensor-correlation-function.html
In the post linked above I've discuss a method to correlate the sensor resistance to a gas ppm using the datasheet curve named "sensitivity characteristics of the MQ-135" and the formula:
ppm=a*(Rs/Ro)^b.
Someone ask me about sensor and correlation coefficients of various gasses, so here I will post some correlation coefficient for the a few MQ sensor and gasses.
| sensor | gas | a | b | min Rs/Ro | max Rs/Ro |
| MQ2 | LPG | 591.283 | -2.076502 | 0.256166 | 1.68543 |
| MQ3 | alcohol | 0.3923202 | -1.493249 | 0.1143375 | 2.497754 |
| MQ4 | CH4 | 1041.333 | -2.729007 | 0.4365277 | 1.830508 |
| MQ5 | CH4 | 217.4972 | -2.422111 | 0.2058715 | 1.035233 |
| MQ6 | LPG | 940.2178 | -2.521573 | 0.3915661 | 1.847477 |
| MQ7 | H2 | 64.86522 | -1.405261 | 0.05323301 | 1.203488 |
| MQ8 | H2 | 1079.683 | -0.6416874 | 0.03115283 | 13.84067 |
| MQ135 | CO2 | 110.3794 | -2.721706 | 0.8038119 | 2.416431 |
Those values have been found using the method proposed in the above post, and the figures posted below.
In order to use the correlation function, you now need to compute the Ro value. You can find this value reading the sensor resistance at a know amount of ppm, compy in the gases ppm limits of the datasheet, and then use this formula:
Ro=Rs*(a/ppm)^(1/b).
Those are the
- collected points: https://bitbucket.org/snippets/davidegironi/z9AMEr/mq-gas-sensor-correlation-coefficients
that has been processes using the following
- R script: https://gist.github.com/davidegironi/b7be6b7cace6b475dd42c48c3e62fcf4
Notes
- read risk disclaimer
- excuse my bad english