Noncontact Human Body Voltage Measurement using Microsoft Kinect and Field Mill for ESD Applications
A technique for measuring the voltage on a person by combining an overhead mounted electrostatic field sensor with Microsoft Kinect image recognition software and hardware is presented in this paper. The Kinect's built-in skeleton detection method was used to determine the posture, height, and location of a person relative to the position of the field sensor. The voltage is estimated using field strength and geometry information. Two different algorithms are proposed for calculating the human body voltage using field strength data captured by the field sensor and human body coordinates recognized by the Kinect. First, using calibration data, the human body voltage was obtained by charging a person to a known voltage and walking through the field of vision, then a correction was performed to convert the field sensor data into the human body voltage. The second algorithm is based on solving Laplace equation. The human body is modeled by using a superposition of spheroids, and the E-field is solved analytically. Results of the algorithms were compared, with the proposed methodology providing less than a ±15%error margin for the human body voltage over a detection area of 2.0 m x 2.5 m.
S. Yong et al., "Noncontact Human Body Voltage Measurement using Microsoft Kinect and Field Mill for ESD Applications," IEEE Transactions on Electromagnetic Compatibility, vol. 61, no. 3, pp. 842-851, Institute of Electrical and Electronics Engineers (IEEE), Jun 2019.
The definitive version is available at https://doi.org/10.1109/TEMC.2018.2836869
Electrical and Computer Engineering
Keywords and Phrases
Electrostatic devices; Electrostatic discharge; Electrostatics; Image recognition; Laplace equations; Laplace transforms; Calibration data; Detection methods; Electrostatic field sensor; Field mills; Geometry information; Microsoft kinect; Software and hardwares; Tribocharging; Electromagnetic field effects
International Standard Serial Number (ISSN)
Article - Journal
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jun 2019