A Review of Artificial Intelligence-Driven Active Vibration and Noise Control
Zongkang Jiang, Hongtao Xue, Huiyu Yue, Xiaoyi Bao, Junwei Zhu, Xuan Wang, Liang Zhang
Abstract
The core objective of Active Vibration and Noise Control (AVNC) is to enhance system performance by generating real-time counter-phase signals of equal amplitude to cancel out vibration and noise interference from mechanical or structural systems. As the demand for low-noise, low-vibration environments grows in fields such as new energy vehicles (NEVs), aerospace, and high-precision manufacturing, traditional AVNC methods—which rely on precise linear models and have poor adaptability to nonlinear and time-varying conditions—struggle to meet the dynamic requirements of complex engineering scenarios. However, with advancements in artificial intelligence (AI) technology, AI-driven Active Vibration and Noise Control (AI-AVNC) technology has garnered significant attention from both industry and academia. Based on a thorough investigation into the state-of-the-art AI-AVNC methods, this survey has made the following contributions: (1) Introducing the theoretical foundations of AVNC and its historical development; (2) Classifying existing AI-AVNC methods from the perspective of control strategies; (3) Analyzing engineering applications of AI-AVNC; (4) Discussing current technical challenges and future development trends of AI-AVNC.