Enhancing Seismic Resilience of High-Tech Equipment through Advanced AI-Controlled Isolation Systems

Abstract

This paper explores the seismic vulnerability of high-tech industries that rely on vibration-sensitive equipment and presents an AI-driven solution to improve protection. It proposes a piezo-electric smart isolation system (PSIS) combining Deep Reinforcement Learning (DRL), Fuzzy Inference System (FIS), and Non-striking Friction (NSF) control. This paper uses a quantitative methodology to analyze the performance of the system in real-time, its adaptability, and its effect on nano-scale manufacturing processes. Results indicate that the DRL-FIS-NSF strategy significantly improves isolation performance, reduces displacement and acceleration metrics, and enhances manufacturing precision. Despite limitations such as reliance on simulations, this research demonstrates the transformative potential of AI in seismic protection for high-tech industries