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

S. C. Mukhopadhyay

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 proceeding › Conference proceeding contribution › peer-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 language	English
Title of host publication	Proceedings of IEEE Sensors
Subtitle of host publication	First IEEE International Conference on Sensors
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	747-752
Number of pages	6
Volume	1
Edition	2
Publication status	Published - 2002
Externally published	Yes
Event	First IEEE International Conference on Sensors - IEEE Sensors 2002 - Orlando, FL, United States Duration: 12 Jun 2002 → 14 Jun 2002

Other

Other	First IEEE International Conference on Sensors - IEEE Sensors 2002
Country/Territory	United States
City	Orlando, FL
Period	12/06/02 → 14/06/02

Cite this

@inproceedings{5b29d06ed2114b76ade5483adedac64a,

title = "Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors",

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.",

author = "Mukhopadhyay, \{S. C.\}",

year = "2002",

language = "English",

volume = "1",

pages = "747--752",

booktitle = "Proceedings of IEEE Sensors",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

edition = "2",

note = "First IEEE International Conference on Sensors - IEEE Sensors 2002 ; Conference date: 12-06-2002 Through 14-06-2002",

}

Mukhopadhyay, SC 2002, Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors. in Proceedings of IEEE Sensors: First IEEE International Conference on Sensors. 2 edn, vol. 1, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 747-752, First IEEE International Conference on Sensors - IEEE Sensors 2002, Orlando, FL, United States, 12/06/02.

Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors. / Mukhopadhyay, S. C.
Proceedings of IEEE Sensors: First IEEE International Conference on Sensors. Vol. 1 2. ed. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2002. p. 747-752.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Neural network aided estimation of near-surface material properties using planar type micromagnetic sensors

AU - Mukhopadhyay, S. C.

PY - 2002

Y1 - 2002

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/1542301630

M3 - Conference proceeding contribution

AN - SCOPUS:1542301630

VL - 1

SP - 747

EP - 752

BT - Proceedings of IEEE Sensors

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - First IEEE International Conference on Sensors - IEEE Sensors 2002

Y2 - 12 June 2002 through 14 June 2002

ER -

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

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