Vibration Sensing for Smart Monitoring of Ultra-precision Manufacturing Equipment: A Review
Hujeong Lee, Jaeyoon Kim, Guseon Kang, Young‐Jin Kim
Korea Advanced Institute of Science and Technology Korea Institute of Industrial Technology
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Ultra-precision manufacturing (UPM) is essential in advanced industries such as semiconductor fabrication, precision optics, photonics, and micro-scale engineering, where nanometer- and sub-nanometer-level accuracy is required. Vibration is a major disturbance that affects the relative displacement of critical functional elements, including tool-workpiece interfaces, wafer stages, projection optics, and probe-sample assemblies. Originating from both external environments and internal machine dynamics, vibration degrades product quality and production yield. To address this issue, vibration sensing technologies have been widely adopted for equipment condition monitoring and performance evaluation. Inertial sensors, such as IEPE and capacitive MEMS accelerometers, provide reliable measurements over broad frequency ranges. Optical sensors, including laser Doppler vibrometers and interferometric displacement sensors, enable non-contact measurements with sub-nanometer resolution. However, individual sensing technologies often suffer from limitations such as restricted bandwidth, noise amplification, and sensitivity to installation conditions. This review defines smart vibration monitoring as an integrated framework that combines vibration sensing, signal processing, and intelligent data analytics for equipment diagnostics and performance assessment. Major vibration sensing technologies used in ultra-precision machining, lithography, and metrology are reviewed, and future directions toward multi-sensor fusion and intelligent monitoring are discussed.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Advanced Measurement and Metrology Techniques
Advanced machining processes and optimization · Machine Fault Diagnosis Techniques