abstract: The applications which use MEMS accelerometer have been on rise and many new fields which are using the MEMS devices have been on rise. The industry is trying to reduce the cost of production of these MEMS devices. These devices are manufactured using micromachining and the interface circuitry is manufactured using CMOS and the final product is integrated on to a single chip. Amount spent on testing of the MEMS devices make up a considerable share of the total final cost of the device. In order to save the cost and time spent on testing, researchers have been trying to develop different methodologies. At present, MEMS devices are tested using mechanical stimuli to measure the device parameters and for calibration the device. This testing is necessary since the MEMS process is not a very well controlled process unlike CMOS. This is done using an ATE and the cost of using ATE (automatic testing equipment) contribute to 30-40% of the devices final cost. This thesis proposes an architecture which can use an Electrical Signal to stimulate the MEMS device and use the data from the MEMS response in approximating the calibration coefficients efficiently. As a proof of concept, we have designed a BIST (Built-in self-test) circuit for MEMS accelerometer. The BIST has an electrical stimulus generator, Capacitance-to-voltage converter, ∑ ∆ ADC. This thesis explains in detail the design of the Electrical stimulus generator. We have also designed a technique to correlate the parameters obtained from electrical stimuli to those obtained by mechanical stimuli. This method is cost effective since the additional circuitry needed to implement BIST is less since the technique utilizes most of the existing standard readout circuitry already present. / Dissertation/Thesis / M.S. Electrical Engineering 2014
| Identifer | oai:union.ndltd.org:asu.edu/item:21039 |
| Date | January 2014 |
| Contributors | Jangala Naga, Naveen Sai (Author), Ozev, Sule (Advisor), Bakkaloglu, Bertan (Committee member), Kiaei, Sayfe (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 77 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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