Publications by Hamidreza Karami

An experimental proof of concept of time‐reversal single‐sensor acoustic source localisation: Application to partial discharges

Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami, Zhaoyang Wang

In this paper, for the first time, an experimental proof of concept for utilising time reversal (TR) in the acoustic regime to localise partial discharge (PD) sources was presented using a single sensor. To achieve this, an experimental setup comprising a ...

Institution of Engineering and Technology (IET)2025

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024

High Resolution Time-Reversal Imaging: A Comparison between Time-Reversal MUSIC and DORT

Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami

2024

Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami, Elias Per Joachim Le Boudec, Nicolas Mora Parra

Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

2024

Landmine Detection Using Electromagnetic Time Reversal-Based Methods: 1. Classical TR, Iterative TR, DORT and TR-MUSIC

Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami, Carlos Alberto Romero Romero

In this paper, we present a review and classification of the published works on the use of Electromagnetic Time Reversal (EMTR)-based methods to locate landmines. Different approaches for landmine localization using EMTR are investigated. Specifically, the ...

American Geophysical Union (AGU)2024

An Efficient Machine Learning Model for Lightning Localization via Lightning-Induced Voltages on Transmission Lines

Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami

In this paper, three machine learning (ML)-based approaches—XGBoost, Artificial Neural Network (ANN), and Random Forest algorithms—are compared for the localization of lightning through the analysis of lightninginduced voltages on power transmission lines. ...

URSI – International Union of Radio Science2024

Landmine Detection Using Electromagnetic Time Reversal‐Based Methods: 2. Performance Analysis of TR‐MUSIC

Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami, Carlos Alberto Romero Romero

In this paper, a series of numerical simulations are conducted for various 2D and 3D configurations to demonstrate the performance of the Time Reversal MUltiple SIgnal Classification (TR‐MUSIC) method. The results reveal the excellent performance of TR‐MUS ...

American Geophysical Union (AGU)2024

Rigorous Assessment of Natural Frequencies of Fault-Originated Travelling Waves

Mario Paolone, Hamidreza Karami, Zhaoyang Wang, Pier Luigi Dragotti

This paper presents a rigorous assessment of natural frequencies associated with fault-originated travelling waves in power networks, factoring in the presence of multiple junctions and branches. The proposed assessment exploits the Baum-Liu-Tesche (BLT) e ...

2024

Lightning Localization Using Three-Dimensional Time Reversal MUltiple SIgnal Classification (TR-MUSIC) Algorithm

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

In this paper a three-dimensional (3D) Time Reversal MUltiple SIgnal Classification (TR-MUSIC) algorithm is proposed to localize lightning discharges. The performance of the proposed algorithm was evaluated considering different scenarios and taking into a ...

2023

On the Efficiency of MW-FDTD Methods Based on Parallel Computing Using OpenMP, OpenACC, and CUDA Python: Application to Lightning Electromagnetic Fields

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

2023