Design of MEMS Frog shape Microphone with High Sensitivity and low voltage using PSO Algorithm

Abstract

In this paper, the geometry of a frog- shape MEMS microphone is optimized using a particle swarm optimization technique to reduce bias voltage and to increase sensitivity. The PSO algorithm is a population based stochastic optimization technique that inspired by social behavior of bird flocking, which is used to solve complicated design spaces and multi physical problems. The proposed method in this paper can be adapted to a variety of MEMS device designs. This approach shows improvements over previous designs that were generated from the conventional design approach (approximate methods based on trial and error). Considering that the performance of the microphone is studied in different directions, and various design parameters are in a trade off with each other, the definition of a multi-purpose target function is very important. In this work, we define the target function such that all three factors of resonance frequency, mechanical sensitivity and pull-in voltage should be considered, simultaneously. The results show that the designed microphone has a good performance. Actually, only by choosing optimal dimensions for length and width of frog-shape diaphragm arms, the mechanical sensitivity and open circuit sensitivity of the microphone increased approximately 4 and 2 times respectively, and the pull-in voltage decreased to half approximately.

Keywords

• frog-shape capacitive microphone
• micro electro mechanical system (mems)
• spring constant
• particle swarm optimization algorithm(pso)