D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 32 Citations 4,477 316 World Ranking 6860 National Ranking 2109

Research.com Recognitions

Awards & Achievements

2013 - Fellow, National Academy of Inventors

2003 - IEEE Fellow For contributions to the development of methods for solving inverse problems in the field of nondestructive evaluation.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Electrical engineering
  • Optics

Satish S. Udpa mostly deals with Artificial neural network, Finite element method, Eddy-current testing, Magnetic flux leakage and Eddy current. His work carried out in the field of Artificial neural network brings together such families of science as Inverse problem, Signal processing, Algorithm and Wavelet, Pattern recognition. As part of the same scientific family, he usually focuses on Finite element method, concentrating on Nuclear magnetic resonance and intersecting with Giant magnetoresistance and Canalisation.

His Acoustics research extends to the thematically linked field of Eddy-current testing. His research in Magnetic flux leakage focuses on subjects like Magnetic flux, which are connected to Iterative method. The various areas that Satish S. Udpa examines in his Eddy current study include Signal, Representation, Electromagnetic coil and Massively parallel.

His most cited work include:

  • Advanced signal processing of magnetic flux leakage data obtained from seamless gas pipeline (111 citations)
  • Pulsed Eddy-Current Based Giant Magnetoresistive System for the Inspection of Aircraft Structures (97 citations)
  • Electromagnetic NDE signal inversion by function-approximation neural networks (90 citations)

What are the main themes of his work throughout his whole career to date?

Satish S. Udpa mainly focuses on Eddy current, Acoustics, Electronic engineering, Finite element method and Eddy-current testing. Satish S. Udpa has included themes like Signal, Excitation and Magnetic flux leakage in his Acoustics study. His study focuses on the intersection of Magnetic flux leakage and fields such as Wavelet with connections in the field of Artificial neural network.

Satish S. Udpa combines subjects such as Pipeline transport and Signal processing with his study of Electronic engineering. He works mostly in the field of Finite element method, limiting it down to topics relating to Inverse problem and, in certain cases, Integral equation and Iterative method, as a part of the same area of interest. His studies deal with areas such as Giant magnetoresistance, Algorithm and Bobbin as well as Eddy-current testing.

He most often published in these fields:

  • Eddy current (25.76%)
  • Acoustics (25.38%)
  • Electronic engineering (20.45%)

What were the highlights of his more recent work (between 2008-2021)?

  • Eddy current (25.76%)
  • Acoustics (25.38%)
  • Eddy-current testing (15.91%)

In recent papers he was focusing on the following fields of study:

Satish S. Udpa mainly investigates Eddy current, Acoustics, Eddy-current testing, Finite element method and Electromagnetic coil. His Eddy current study incorporates themes from Electronic engineering, Excitation, Rotating magnetic field and Boiler. His Acoustics research incorporates elements of Finite-difference time-domain method, Sensitivity, Signal, Signal processing and Fastener.

His study in Eddy-current testing is interdisciplinary in nature, drawing from both Giant magnetoresistance, Solver, Bobbin and Computational model. His research in Finite element method intersects with topics in Ferrite core, Inverse problem and Magnetoresistance. His Electromagnetic coil research is multidisciplinary, incorporating elements of Magnetic potential and Nuclear magnetic resonance.

Between 2008 and 2021, his most popular works were:

  • Pulsed Eddy-Current Based Giant Magnetoresistive System for the Inspection of Aircraft Structures (97 citations)
  • Classification of pulsed eddy current GMR data on aircraft structures (62 citations)
  • Reduced Magnetic Vector Potential Formulation in the Finite Element Analysis of Eddy Current Nondestructive Testing (47 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Artificial intelligence
  • Optics

Satish S. Udpa spends much of his time researching Eddy current, Acoustics, Eddy-current testing, Electromagnetic coil and Finite element method. The concepts of his Eddy current study are interwoven with issues in Artificial neural network, Boiler, Transient and Rotating magnetic field. The study incorporates disciplines such as Wave propagation, Excitation, Finite difference method and Finite-difference time-domain method in addition to Acoustics.

His work focuses on many connections between Eddy-current testing and other disciplines, such as Giant magnetoresistance, that overlap with his field of interest in Signal, Fastener, Signal processing and Frequency domain. His research in Electromagnetic coil tackles topics such as Nuclear magnetic resonance which are related to areas like Magnetic potential. His Finite element method study combines topics from a wide range of disciplines, such as Iterative method and Numerical stability.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Advanced signal processing of magnetic flux leakage data obtained from seamless gas pipeline

Muhammad Afzal;Satish Udpa.
Ndt & E International (2002)

177 Citations

Electromagnetic NDE signal inversion by function-approximation neural networks

P. Ramuhalli;L. Udpa;S.S. Udpa.
IEEE Transactions on Magnetics (2002)

164 Citations

Pulsed Eddy-Current Based Giant Magnetoresistive System for the Inspection of Aircraft Structures

Guang Yang;A. Tamburrino;L. Udpa;S.S. Udpa.
IEEE Transactions on Magnetics (2010)

146 Citations

Adaptive Wavelets for Characterizing Magnetic Flux Leakage Signals From Pipeline Inspection

A.V. Joshi;L. Udpa;S. Udpa;A. Tamburrino.
ieee international magnetics conference (2006)

137 Citations

Frequency invariant classification of ultrasonic weld inspection signals

R. Polikar;L. Udpa;S.S. Udpa;T. Taylor.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control (1998)

131 Citations

Three-dimensional defect reconstruction from eddy-current NDE signals using a genetic local search algorithm

Yue Li;L. Udpa;S.S. Udpa.
IEEE Transactions on Magnetics (2004)

127 Citations

Eddy current defect characterization using neural networks

L. Udpa;S. S. Udpa.
Materials evaluation (1990)

124 Citations

Invariance transformations for magnetic flux leakage signals

S. Mandayam;L. Udpa;S.S. Udpa;W. Lord.
IEEE Transactions on Magnetics (1996)

114 Citations

Characterization of gas pipeline inspection signals using wavelet basis function neural networks

K. Hwang;S. Mandayam;S.S. Udpa;L. Udpa.
Ndt & E International (2000)

113 Citations

Neural networks for the classification of nondestructive evaluation signals

L. Udpa;S.S. Udpa.
IEE Proceedings F Radar and Signal Processing (1991)

110 Citations

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