Human impedance characteristic investigation by low voltage square wave excitation

C. D. Xu, K. W.E. Cheng, D. H. Wang, X. L. Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In order to obtain the characteristic of the human impedance [1][2], A square wave electric signal is proposed to apply to the human beings. The peak current when a human is in initial contact of an electrical signal is examined. The use of square wave is a better method for human detection as it gives an exponential current that is unique as compared to another electrical appliance. The result provides a critical judgment for smart electric socket which could identify human being from another appliance. The whole research is based on the human model in the standard of IEC 479[3]. Considering the instant effect in the first charging moment by the step pulse, the human model is simplified to an RC circuit.

Original languageEnglish
Title of host publication2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
EditorsK.W. Eric Cheng
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538613863
DOIs
Publication statusPublished - 31 Jan 2018
Event7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017 - Hong Kong, Hong Kong
Duration: 12 Dec 201714 Dec 2017

Publication series

Name2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
Volume2018-January

Conference

Conference7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer and Security, PESA 2017
Country/TerritoryHong Kong
CityHong Kong
Period12/12/1714/12/17

Keywords

  • Human impedance
  • safety
  • square wave excitation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

Cite this