Harleen Sandhu

Works (6)

Updated: September 16th, 2024 08:21

2024 article

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Sandhu, H. K., Bodda, S. S., Yan, E., Sabharwall, P., & Gupta, A. (2024, March 1). MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol. 209.

By: H. Sandhu n, S. Bodda n, E. Yan*, P. Sabharwall * & A. Gupta  n

author keywords: Condition monitoring; Deep learning; Convolutional neural networks; Feature extraction; Nuclear piping; Degradation detection
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Source: Web Of Science
Added: March 4, 2024

2024 article

Deep learning application for monitoring degradation in nuclear safety systems

Sandhu, H. K., Sauers, S., Bodda, S. S., & Gupta, A. (2024, August 26). EUROPEAN JOURNAL OF ENVIRONMENTAL AND CIVIL ENGINEERING.

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

author keywords: Deep learning; condition monitoring; nuclear piping; feature extraction; experimental data
Source: Web Of Science
Added: September 9, 2024

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

author keywords: condition assessment; artificial intelligence; deep learning; damage detection; signal processing; data management; nuclear piping; concrete; advanced reactors; digital twin
TL;DR: AI can play a greater role in the condition assessment and can be extended to recognize concrete degradation before cracks develop, and data assimilation and storage is another challenging aspect of autonomous control. (via Semantic Scholar)
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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

TL;DR: A novel strategic recommendation to the operator can be beneficial in avoiding fatigue in piping systems due to pump-induced vibrations and is proposed for “safe” pump operating speeds, as per ASME design criteria. (via Semantic Scholar)
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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

author keywords: Condition assessment; Deep learning; Nuclear piping; Flow-assisted corrosion; erosion; Degradation detection
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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

author keywords: computer vision; acceleration response; target tracking; sparse optical flow
MeSH headings : Algorithms; Computers; Image Processing, Computer-Assisted; Optic Flow; Vibration
TL;DR: The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method, and achieves the best accuracy compared to other existing target tracking methods. (via Semantic Scholar)
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Sources: Web Of Science, ORCID
Added: September 14, 2022

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