SBIR Phase I: A Manufacturing Monitoring System Using Sound Spectrograms and Artificial Intelligence

小型企业创新研究(SBIR)第一阶段项目的更广泛影响是以更低的成本提高制造性能。该项目将开发一种基于智能内部声音传感器和人工智能(AI)的机器和过程监控系统，作为一种简单的即插即用边缘设备。它的目标是成为一种低成本、多功能和可定制的解决方案，适用于生产车间的各种设备和设备。这项技术可以显著降低产品不良率，提高产品质量，延长机器寿命，提高设备整体效能，并使更好的人为决策。虽然这种监测系统可以被任何新的/现代的制造商部署，但中小型企业(SME)公司可以改造传统的设备/装置，以了解他们的机器、工艺行为、及时维护和剩余寿命等。拟议的项目是一种听诊器式传感器，可以捕获多个频率的内部声音，而不会受到外部工厂声音的污染。为了将捕获的声音解释为根据机器/过程事件(异常、情况、停机时间等)发布仪表板的有用信息，该项目正在开发基于人工智能的声音分类或“机器语音”识别技术。声音数据可以无线获取和处理，使设备能够在目标设备的外部进行非侵入性应用。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve manufacturing performance at decreased costs. The project will develop a smart internal sound sensor- and artificial intelligence (AI)-based machine and process monitoring system as a simple plug-and-play edge device. It aims to be a low-cost, versatile, and customizable solution for a wide range of equipment and devices on production floors. This technology can significantly reduce the product defect rate, improve product quality, prolong machine life, increase the overall equipment effectiveness, and enable better human decisions. While this monitoring system can be deployed by any new/modern manufacturers, small and mid-sized enterprise (SME) companies can retrofit legacy equipment/ devices for understanding their machines, process behaviors, timely maintenance, and remaining life, etc. The proposed project is a stethoscope-like sensor that captures internal sounds across many frequencies without contamination from external factory sounds. To interpret the captured sounds into useful information for dashboard publishing in terms of machine/process events (anomaly, situation, downtime, etc.), this project is developing AI-based sound classification or ‘machine speech’ recognition techniques. The sound data can be wirelessly acquired and processed, enabling a device for non-invasive application on the outside of target equipment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.