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A Highly Stable and Sensitive MEMS-Based Gravimeter for Long-Term Earth Tides Observations

Lujia Yang, Xiaochao Xu, Qian Wang, Ji'ao Tian, Yanyan Fang, Chun Zhao, Fangjing Hu, Liangcheng Tu

2022IEEE Transactions on Instrumentation and Measurement16 citationsDOI

Abstract

Precision measurements of local gravitational acceleration variations are of great importance in geophysical surveys. With advantages such as cost-effectiveness and portability, Micro-Electro-Mechanical system (MEMS)-based gravimeters have shown the potential for long-term gravity measurements. In this paper, aiming to further improve the stability of the instrument, the design considerations and system evaluations of a MEMS gravimeter are presented. With a linear spring design for the silicon proof-mass, a low natural frequency of ~14 Hz and a large linear range of ~10300 mGal are achieved with an ultra-low self-noise floor of 1.2 μGal/√Hz@1 Hz. By implementing a vacuum chamber system, the pressure variation is reduced from hundreds of Pa/day in atmosphere to a linear variation of ~6 Pa/day. In addition, an active temperature control system can suppress temperature fluctuations by 2 to 3 orders of magnitude within the band from 1×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> Hz to 1×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> Hz. The stability of the proposed MEMS gravimeter is demonstrated via long-term Earth tides observations within a 30-day time span, giving a correlation coefficient of 0.957 with the reference. An excellent bias instability of ≤4 μGal is demonstrated within the 8-3000 s averaging time range, representing one of the best performances to date in terms of stability for MEMS gravimeters. This shows the potential of high-performance MEMS gravimeters for petroleum and mineral prospecting, seismology and other geophysical applications.

Topics & Concepts

GravimeterProof massAllan varianceNoise (video)Stability (learning theory)Microelectromechanical systemsGravitational accelerationAccelerationLinearityPhysicsGeodesyGravitationElectrical engineeringComputer scienceGeologyGeophysicsEngineeringAstronomyMathematicsOptoelectronicsImage (mathematics)StatisticsClassical mechanicsStandard deviationMachine learningCasingArtificial intelligenceGeophysics and Gravity MeasurementsInertial Sensor and NavigationGeophysics and Sensor Technology
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