Temperature and chemical sensing via intrinsic noise analysis of MEMS microphones

Micromachined microphones are sophisticated, optimized sound transducers that are employed on a massive scale in consumer electronics, including mobile phones. The optimization of the design of the transducing element’s acoustic frequency spectrum has been aimed at providing a near-constant sensitivity for the human audible frequency range and multiple techniques for reducing external acoustic background noise have been developed in order to improve performance of systems employing microphones. This work models and investigates the influence of environmental conditions on the intrinsic noise behaviour of MEMS microphones. The results show that the intrinsic noise spectrum of MEMS microphones may be employed to gauge the ambient temperature as well as serve as a chemical sensor. To this end, a model that takes into account environmental conditions and the gas composition is used to simulate the microphones’ behaviour and experimental results demonstrate how environmental parameters may be determined from the intrinsic noise spectrum. ● Intrinsic noise analysis of MEMS microphones for temperature and gas sensing ● Additional sensing capabilities of MEMS microphones without added components ● Noise spectrum behaviour as transducing mechanism