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Abstract
Low-cost MEMS accelerometers have the potential to be used in a number of tilt-based monitoring applications but have the disadvantage of being very sensitive to temperature variation (thermal drift). In this paper, we analyze the thermal behavior of a low-cost sensor in the range −10 to +45 °C in order to provide a simple compensation strategy to mitigate this problem. For sensor analysis, we have developed a miniaturized thermal chamber, which was mounted on a tilting device to account for tilt angle variation. The obtained raw data were used to construct low degree polynomial equations that by relating the measurement error induced by thermal drift (i.e., acceleration residuals) to temperature and inclination (of each specific axis), can be used for thermal compensation. To validate our compensation strategy, we performed a field monitoring test and evaluated the compensation performance by calculating RMS errors before and after correction. After compensation, the RMS errors calculated for both the X and Y axes decreased by 96%, indicating the potential of using a simple set of equations to solve common drawbacks that currently make low-cost MEMS sensors unsuitable for tilt-based monitoring applications.
Highlights
MEMS accelerometers have a wide range of applications in consumer electronics and are of common use in environmental and geotechnical applications
MEMS accelerometers have the disadvantage of being very sensitive to temperature variations, suffering from thermal drift that induces error in the acceleration measurements
To provide a simple compensation strategy the can be used in most monitoring applications, we have performed a thermal calibration analysis of onboard accelerometers of a low-cost
Summary
MEMS accelerometers have a wide range of applications in consumer electronics and are of common use in environmental and geotechnical applications. The idea behind the paper is to underline the increased potential of low cost sensors for multiple environmental monitoring applications providing simple tools for measurement improvement In this perspective, the analyzed sensor is being used for the development of a tilt-based landslide monitoring/early warning system that will be presented in a forthcoming paper. We used calibration data to derive specific compensation polynomial equations (i.e., surfaces of compensation) for each axis of the accelerometer and estimate compensation performance through RMS error evaluation This strategy can be applicable to all capacitive low-cost MEMS sensor in order to make them applicable to a number of tilt-based monitoring conditions where medium to high precision and stability is needed
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