Works (4)

Updated: July 24th, 2023 08:20

2023 review

A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities

[Review of ]. ENERGIES, 16(6).

By: H. Sandhu n, S. Bodda n & A. Gupta n

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
author keywords: condition assessment; artificial intelligence; deep learning; damage detection; signal processing; data management; nuclear piping; concrete; advanced reactors; digital twin
Source: Web Of Science
Added: April 17, 2023

2023 journal article

Condition Monitoring of Nuclear Equipment-Piping Systems Subjected to Normal Operating Loads Using Deep Neural Networks

JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME, 145(4).

By: H. Sandhu n, S. Bodda n, S. Sauers & A. Gupta n

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
Source: Web Of Science
Added: July 19, 2023

2023 journal article

Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning

INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING, 201.

By: H. Sandhu n, S. Bodda n & A. Gupta n

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
author keywords: Condition assessment; Deep learning; Nuclear piping; Flow-assisted corrosion; erosion; Degradation detection
Source: Web Of Science
Added: January 23, 2023

2022 journal article

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method

SENSORS, 22(18).

By: G. Nie n, S. Bodda n, H. Sandhu n, K. Han n  & A. Gupta n

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
author keywords: computer vision; acceleration response; target tracking; sparse optical flow
MeSH headings : Algorithms; Computers; Image Processing, Computer-Assisted; Optic Flow; Vibration
Sources: Web Of Science, ORCID
Added: September 14, 2022