ArticleMicromachines2026
Experimental Characterization and Calibration of a MEMS Electric Field Sensor Under DC Ionized Field Conditions.
Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Lie Classification and Symmetry-Preserving Reduced-Order Modeling of Nonlinear Electrostatic MEMS.Micromachines · 2026Article
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Authors and funding
3 authors.
Funding
Abstract
Accurate electric field measurement in high-voltage direct current (HVDC) environments is essential for power system monitoring. This study systematically investigates the output characteristics of a micro-electro-mechanical system (MEMS) electric field sensor under DC ionized field conditions. Using a controlled experimental platform capable of generating independent nominal electric fields and ion flows, the influence of ion current density on sensor sensitivity and offset was quantitatively analyzed. Experimental results reveal that ion flow leads to a progressive output drift and significant measurement deviations when using conventional electrostatic calibration. To address this issue, a joint calibration method incorporating ion current density is proposed. Validation experiments demonstrate that the proposed method significantly improves measurement accuracy, reducing the maximum relative error from 29.28% to approximately 5.07%. This work provides a reliable experimental basis and calibration methodology for utilizing MEMS electric field sensors in complex ionized DC environments.
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Registered trials
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