TY - GEN
T1 - Maintaining NIST-traceability for MEMS sensors via in-field electrical recalibration
AU - Bassi, Ishaan
AU - Ozev, Sule
AU - Chang, Doohwang
N1 - Funding Information:
This work is supported by the National Science Foundation through the grant number NSF-CISE-1910380. DISTRIBUTION STATEMENT A. Approved for public release: distribution is unlimited.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/25
Y1 - 2021/4/25
N2 - Micro Electro-Mechanical Systems (MEMS) accelerometers are used in safety critical applications, such as airbags and airplanes. While providing very accurate results, they can degrade over time due to many wearout mechanisms. According to the National Institutes of Standards and Technology (NIST), the accuracy of motion sensors used in safety critical applications needs to be maintained within 1% error. In-field electrical stimulation and calibration can enable long-term sensor operation without removing the sensor from its environment. While electrical stimulation has been proposed to replace the physical stimulation to reduce testing cost for sensors, it has not yet been shown to achieve the 1% error requirement as required by the NIST standard of safety. In this paper, we propose an incremental sensor-based model that can relate the degradation in the sensitivity of the sensor to its electrical response for infield monitoring. In order to extract such a relation, we need to generate multiple sensitivity states for the sensor however, which is not possible using the normal mode of operation. We propose to temporary place the sensor in an enhanced state where the sensitivity can be changed also via electrical signalling, thereby generating an adequate number of measurements to solve for model coefficients. We show through simulations and hardware experiments that the model can predict the sensitivity changes within 1% error.
AB - Micro Electro-Mechanical Systems (MEMS) accelerometers are used in safety critical applications, such as airbags and airplanes. While providing very accurate results, they can degrade over time due to many wearout mechanisms. According to the National Institutes of Standards and Technology (NIST), the accuracy of motion sensors used in safety critical applications needs to be maintained within 1% error. In-field electrical stimulation and calibration can enable long-term sensor operation without removing the sensor from its environment. While electrical stimulation has been proposed to replace the physical stimulation to reduce testing cost for sensors, it has not yet been shown to achieve the 1% error requirement as required by the NIST standard of safety. In this paper, we propose an incremental sensor-based model that can relate the degradation in the sensitivity of the sensor to its electrical response for infield monitoring. In order to extract such a relation, we need to generate multiple sensitivity states for the sensor however, which is not possible using the normal mode of operation. We propose to temporary place the sensor in an enhanced state where the sensitivity can be changed also via electrical signalling, thereby generating an adequate number of measurements to solve for model coefficients. We show through simulations and hardware experiments that the model can predict the sensitivity changes within 1% error.
KW - Accelerometer
KW - Calibration
KW - Electrical stimulus
KW - MEMS
KW - Sensors
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U2 - 10.1109/VTS50974.2021.9441000
DO - 10.1109/VTS50974.2021.9441000
M3 - Conference contribution
AN - SCOPUS:85107505814
T3 - Proceedings of the IEEE VLSI Test Symposium
BT - Proceedings - 2021 IEEE 39th VLSI Test Symposium, VTS 2021
PB - IEEE Computer Society
T2 - 39th IEEE VLSI Test Symposium, VTS 2021
Y2 - 26 April 2021 through 28 April 2021
ER -