Performance Enhancement of Industrial Drive Systems Using AI-Enabled Multi-Domain Thermal and Vibration Control

Abstract

Industrial drive systems frequently suffer from efficiency loss and accelerated component degradation due to uncontrolled thermal buildup and vibration-induced mechanical stress. This research presents an AI-enabled multi-domain thermal and vibration control system designed to address these issues in real time. The proposed model integrates high-frequency sensor fusion, adaptive thermal regulation, and machine-learning-based vibration prediction to maintain optimal operating conditions across varying load profiles. Experiments performed on a 4.5 kW drive system demonstrate a reduction of 14–20% in peak temperature rise, a 9% improvement in rotational efficiency, and a vibration-related fault prediction accuracy of 92%, outperforming conventional PID systems. These results highlight the potential of intelligent multi-domain control systems for enhancing performance, reliability, and energy efficiency in industrial drive applications.

Cite as:

P. Bhise, & S. Patil. (2025). Performance Enhancement of Industrial Drive Systems Using AI-Enabled Multi-Domain Thermal and Vibration Control. Recent Trends in Thermodynamics and Thermal Energy System, 1(3), 41–44. https://doi.org/10.5281/zenodo.17734097