Comb-drive transducers are made of interdigitized fingers formed by the stationary part known as stator and the moving part known as rotor, and based on the transduction principle of capacitance change. They can be designed as area-change or gap-change mechanism to convert the mechanical signal at in-plane direction into electrical output. The comb-drive transducers can be utilized to differentiate the wave motion in orthogonal directions when they are utilized with the outof- plane transducers. However, their sensitivity is weak to detect the wave motion released by newly formed damage surfaces. In this study, Micro-Electro-Mechanical System (MEMS) comb-drive Acoustic Emission (AE) transducer designs with two different mechanisms are designed, characterized and compared for sensing high frequency wave propagation. The MEMS AE transducers are manufactured using MetalMUMPs (Metal Multi-User MEMS Processes), which use electroplating technique for highly elevated microstructure geometries. Each type of the transducers is numerically modeled using COMSOL Multiphysics program in order to determine the sensitivity based on the applied load. The transducers are experimentally characterized and compared to the numerical models. The experiments include laser excitation to control the direction of the wave generation, and actual crack growth monitoring of aluminum 7075 specimens loaded under fatigue. Behavior and responses of the transducers are compared based on the parameters such as waveform signature, peak frequency, damping, sensitivity, and signal to noise ratio. The comparisons between the measured parameters are scaled according to the respective capacitance of each sensor in order to determine the most sensitive design geometry.
In this paper, new MEMS strain sensors are introduced. The transduction principle of the sensors is the resistance change due to piezoresistive property of polysilicon. Five different sensors are designed on the same device and tuned to resistance values of 350 Ω and 120 Ω. The sensors are aligned in horizontal, vertical and 45° directions in order to extract the principle strains. The geometry of the sensing element is a rectangular bar anchored at two ends and suspended above silicon substrate. The sensors are numerically modeled using COMSOL Multiphysics software. The model consists of all the micromachining layers, including silicon substrate, 0.7 μm thick polysilicon layer (sensing element) sandwiched between two layers of 0.35 μm thick silicon nitride layers and trenching under polysilicon layer, in order to estimate the strain that piezoresistive element is exposed to. The MEMS strain sensors are manufactured using MetalMUMPs process. The sensors are attached to aluminum and steel plates, and their gauge factors are compared with conventional foil gauges under uniaxial and biaxial loading. It is demonstrated that the MEMS strain sensors can detect both static and dynamic strains with the gauge factor reaching significantly high values. High gauge factor occurs because of unique geometry design and trenching, which amplify the strain that the polysilicon layer senses. The MEMS strain sensor can be fused with other sensing elements on the same device such as accelerometer, acoustic emission in order to have redundant measurement from a single point.
In this paper, new MEMS Acoustic Emission (AE) sensors are introduced. The transduction principle of the sensors is capacitance due to gap change. The sensors are numerically modeled using COMSOL Multiphysics software in order to estimate the resonant frequencies and capacitance values, and manufactured using MetalMUMPS process. The process includes thick metal layer (20 μm) made of nickel for freely vibration layer and polysilicon layer as the stationary layer. The metal layer provides a relatively heavy mass so that the spring constant can be designed high for low frequency sensor designs in order to increase the collapse voltage level (proportional to the stiffness), which increases the sensor sensitivity. An insulator layer is deposited between stationary layer and freely vibration layer, which significantly reduces the potential of stiction as a failure mode. As conventional AE sensors made of piezoelectric materials cannot be designed for low frequencies (<300 kHz) with miniature size, the MEMS sensor frequencies are tuned to 50 kHz and 200 kHz. The each sensor contained several parallel-connected cells with an overall size of approximately 250μm × 500 μm. The electromechanical characterizations are performed using high precision impedance analyzer and compared with the numerical results, which indicate a good fit. The initial mechanical characterization tests in atmospheric pressure are conducted using pencil lead break simulations. The proper sensor design reduces the squeeze film damping so that it does not require any vacuum packaging. The MEMS sensor responses are compared with similar frequency piezoelectric AE sensors.
Silicon has piezoresistive property that allows designing strain sensor with higher gauge factor compared to conventional
metal foil gauges. The sensing element can be micro-scale using MEMS, which minimizes the effect of strain gradient
on measurement at stress concentration regions such as crack tips. The challenge of MEMS based strain sensor design is
to decouple the sensing element from substrate for true strain measurement and to compensate the temperature effect on
the piezoresistive coefficients of silicon. In this paper, a family of MEMS strain sensors with different geometric designs
is introduced. Each strain sensor is made of single crystal silicon and manufactured using deposition/ etching/oxidation
steps on a n- doped silicon wafer in (100) plane. The geometries include sensing element connected to the free heads of
U shape substrate, a set of two or more sensing elements in an array in order to capture strain gradients and two
directional sensors. The response function and the gauge factor of the strain sensors are identified using multi-physics
models that combine structural and electrical behaviors of sensors mounted on a strained structure. The relationship
between surface strain and strain at microstructure is identified numerically in order to include the relationship in the
response function calculation.