Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors

S. C. Mukhopadhyay*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

2 Citations (Scopus)

Abstract

The impedance of a coil in proximity of any metal surface is a complex function of many parameters including near-surface properties (such as conductivity, permeability, lift-off etc.) of the material. The transfer impedance (i.e., the ratio between the sensing voltage and the exciting current) of the planar type micromagnetic sensors consisting of exciting and sensing coil is used for the estimation of the near-surface material properties. Two methods have been discussed for the post-processing of output parameters from the measured impedance data. Based on the estimation of near-surface properties it is possible to detect the existence of defects and to predict the degradation of material, fatigue etc.

Original languageEnglish
Title of host publicationProceedings of IEEE Sensors
Subtitle of host publicationFirst IEEE International Conference on Sensors
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages747-752
Number of pages6
Volume1
Edition2
Publication statusPublished - 2002
Externally publishedYes
EventFirst IEEE International Conference on Sensors - IEEE Sensors 2002 - Orlando, FL, United States
Duration: 12 Jun 200214 Jun 2002

Other

OtherFirst IEEE International Conference on Sensors - IEEE Sensors 2002
CountryUnited States
CityOrlando, FL
Period12/06/0214/06/02

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