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

SBIR 第二阶段：使用声谱图和人工智能的制造监控系统

• 批准号: 2335395
• 负责人: Michael Meyer
• 金额: $ 100万
• 依托单位: MAIJKER CORP.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-15 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335395&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Manufacturing; Monitoring

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project lies in its sound-based AI sensing technology. This innovation is poised to significantly elevate the quality and productivity of our nation's manufacturing sector. Central to this mission is its ability to "listen" to the subtle languages of machinery, translating every hum and rattle into actionable insights. This ensures early detection of potential issues, minimizes downtime, and drives optimal performance. Collaborative tests with large manufacturing enterprises are set to showcase its potential in not only averting costly disruptions but also championing a culture of accurate diagnostics and continuous improvement. The societal implications stretch beyond factories. This technology could be embedded in vehicles, bestowing even age-old models with a modern-day protective insight, or in homes, warding off unexpected appliance mishaps. By unlocking the 'speech' of machines, this SBIR project propels us towards a future where our relationship with machinery becomes more intuitive and proactive. Ultimately, this project is a stride towards a seamless conversation between machines and humans, ensuring enhanced safety, efficiency, and an enriched quality of life for all Americans.This Small Business Innovation Research (SBIR) Phase II project aims to push the boundaries of machine condition monitoring by harnessing the underexplored potential of internal machine sounds. Merging Industrial IoT (IIoT) with advanced AI, the project crafts a system primed to provide real-time health and status updates for industrial machinery. The innovation's intellectual merit is in its pioneering method of capturing and analyzing internal machine sounds, paralleling techniques used in AI-based speech recognition systems. The project’s mission is to develop a "machine speech" recognition system that decodes the subtle intricacies of machine sounds for humans. This initiative will enhance our understanding of machine operations and introduce cutting-edge predictive maintenance systems, drawing from a largely untapped data source: internal sounds of machines. Mirroring the precision of a medical doctor using a stethoscope to assess human health and fueled by robust neural network models behind human speech recognition, this project represents the fusion of AI and manufacturing. Empowering workers to "tune in" to machine sounds assures a profound understanding of equipment processes and performance nuances. Diverging from traditional solutions that lean on vibration or current monitoring, this sound-centric approach promises a comprehensive view of machine health, marking a pivotal evolution in manufacturing.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.

这项小型企业创新研究（SBIR）II期项目的更广泛/商业影响在于其基于声音的AI敏感性技术。这项创新被毒死，以显着提高国家制造业的质量和生产力。这项任务的核心是它可以“聆听”机械的微妙语言，将每一个嗡嗡声和嘎嘎作响转化为可行的见解。这样可以确保尽早发现潜在问题，最大程度地减少停机时间并推动最佳性能。与大型制造企业的协作测试设置为展示其潜力，不仅在避免昂贵的破坏中，而且还倡导一种准确的诊断和持续改进的文化。社会含义超越了工厂。这项技术可以嵌入车辆中，甚至具有现代保护的洞察力，也可以赋予古老的型号，或者在房屋中避免了意外的设备不事。通过解锁机器的“语音”，这个SBIR项目推动我们走向我们与机械的关系变得更加直观和积极主动的未来。最终，该项目迈向了机器和人类之间的无缝对话，确保了所有美国人的安全性，效率和丰富的生活质量。这项小型企业创新研究（SBIR）II期项目旨在通过利用机器内部机器的潜在潜力来推动机器状况监测的界限。该项目将工业物联网（IIOT）与高级AI合并，该项目旨在为工业机械提供实时健康和状态更新。创新的智力优点在于其捕获和分析内部机器声音的开创性方法，这是基于AI的语音识别系统中使用的并行技术。该项目的使命是开发一个“机器语音”识别系统，该系统解码了人类机器声音的微妙复杂性。该计划将增强我们对机器运营的理解，并引入最先进的预测维护系统，从大量未开发的数据来源借鉴：机器的内部声音。使用听诊器反映医生的精度来评估人类健康，并以强大的神经元网络模型在人类语音识别背后的助推器中推动，这代表了AI和制造业的融合。授权工人“调音”到机器声音中，对设备过程和性能的细微差别有深刻的了解。这种以声音为中心的方法与倾斜振动或当前监控的传统解决方案有所不同，有望对机器健康有全面的看法，这标志着制造业中关键的发展。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。