Research On The Robust Design Principle And Methodology Of Micro Sensor

The MEMS sensors mainly use silicon Semiconductor as the material. By using the manufacturing process of integrated circuits and micro mechanical processing technology, the sensor structure becomes integrated and miniaturized. The MEMS sensors has been widely used in the important fields of aerospace, military, automotive electronics, telecommunications, agriculture, environmental monitoring, bio-medical. With the development and progress of modern design theory and methods, people fully realize the importance of quality design in the product design. The robust design method is adjusting the design variables and control its tolerance at the same time, in order to make sure the quality of product can be guaranteed when the actual value of the controllable and uncontrollable factors is different from the design value.This paper describes the working principle of piezoresistive, capacitive and piezoelectric sensor. The paper simply analysis their design principle, mainly including the pizoresistive effect of the piezoresistive pressure sensor, the sensitivity and the nonlinear error of capacitance sensor, and the piezoelectric effect of the piezoelectric sensor. In this thesis, the robust design method is introduced into the design of micro sensor. Though researching the general principles and methods of the robust design, the performance of the sensor is improved and the manufacturing cost is reduced.According to the goal of robust design, the basic principles of robust design of micro sensor are put forward:feasibility robustness, quality characteristics robustness and the fluctuation robustness. This paper discusses the basic principle and modeling method of micro sensor robust design based on the tolerance model, stochastic model and the fuzzy model. This paper set up three kinds of application models of robust design of micro sensor. With the examples of piezoresistive pressure sensors and capacitive sensors,three methods of calculating are set up. In considering the impact of design variables tolerance and noise factor, the robust design results are given.A procedures is written to calculate the robust design tolerance based on tolerance model, stochastic models and fuzzy models. The calculations show that the algorithm is stable and reliable. It is convenient for application and strong practicability.