Hariram Arni

About Hariram Arni

PhD Candidate in Industrial Engineering at Northeastern University, funded by FM…

Experience

1. Research Assistant

   FM

   Jan 2024 — Present

   1) Evaluating the Efficacy of Acoustic Monitoring Solutions for Wind Turbine Blades• Collaborated with UMass Lowell and industry partners to test and evaluate novel acoustic monitoring systems.• Conducted wind tunnel tests, achieving a 78% detection rate for perforation-type damage under optimal conditions.• Led field tests for on-tower sensors, demonstrating the system’s capability to assess overall turbine damage levels.• Identified key factors influencing the reliability of detection, including wind speed, damage location, and sensor placement.• Proposed improved evaluation methods to enhance the reliability of acoustic monitoring technologies for wind turbines.2) Induction Motor Failure Detection Using Explainable Features from Motor Current• Developed an explainable machine learning pipeline using XGBoost and SHAP to classify induction motor failures.• Achieved 91% accuracy in classifying motor failure modes, including short circuit, rotor imbalance, and broken rotor bars.• Extracted 30+ features from the time, frequency and wavelet domain to detect subtle motor current anomalies.• Provided engineers with actionable diagnostic insights, enhancing model transparency and industrial maintenance.• Published findings at the 2025 RAMS conference, DOI: 10.1109/RAMS48••••••••84.