AI Article Synopsis

  • The axial self-inductive displacement sensor is used to measure the axial movement of rotors, but traditional models often fail to account for fringing and eddy current effects, leading to inaccuracies.
  • The paper introduces an improved model that incorporates fringing factor and complex permeability, enhancing the sensor's output predictions.
  • This enhanced model offers better alignment with experimental data and analyzes how air gap length and excitation frequency affect sensitivity, making it a valuable tool for sensor design and analysis.

Article Abstract

Axial self-inductive displacement sensor can be used in rotor systems to detect the axial displacement of the rotor. The design and analysis of the sensor are mostly based on the traditional ideal model, which ignores the influence of fringing effects and eddy current effects, resulting in significant discrepancies between theoretical analysis and experimental results. To take into account the influence of fringing effects and eddy current effects, this paper proposed the introduction of the fringing factor and complex permeability and then established an improved model. The results show that the prediction of the sensor's output voltage based on the improved model is in better agreement with the experimental results than the traditional ideal model, and the improved model can analyze the influences of the length of the air gap and excitation frequency on sensitivity. Therefore, the model could provide a significant reference for the design and analysis of the axial self-inductive displacement sensor.

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http://dx.doi.org/10.1063/5.0168684DOI Listing

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Article Synopsis
  • The axial self-inductive displacement sensor is used to measure the axial movement of rotors, but traditional models often fail to account for fringing and eddy current effects, leading to inaccuracies.
  • The paper introduces an improved model that incorporates fringing factor and complex permeability, enhancing the sensor's output predictions.
  • This enhanced model offers better alignment with experimental data and analyzes how air gap length and excitation frequency affect sensitivity, making it a valuable tool for sensor design and analysis.
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