AI-MEMS Sensors for Preemptive Maintenance (Phase I)

用于预防性维护的 AI-MEMS 传感器（第一阶段）

• 批准号: 555555-2020
• 负责人: Sylvestre, Julien
• 金额: $ 9.11万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Idea to Innovation
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705352
• 关键词: AI; MEMS; Sensors; Preemptive; Maintenance

We have developed a new class of MEMS devices that add artificial intelligence (AI) capabilities to sensors. This unique technology has been validated thoroughly in the laboratory, and is now entering a phase of prototype demonstrations in real world applications. These prototypes demand improved robustness, packaging, integration with the MEMS drive electronics and training software. The objective of the proposed I2I Phase I project is to deliver these improvements by creating an AI-MEMS sensor platform to detect faulty machinery automatically to trigger preemptive maintenance actions in an industrial setting. The proposed AI-MEMS sensors will be small, fully autonomous, and robustly packaged for an industrial environment. They will be trained to separate abnormal conditions from normal operation, and to report wirelessly the detected abnormalities.

我们开发了一类新的MEMS器件，为传感器增加了人工智能（AI）功能。这项独特的技术已经在实验室中得到了彻底的验证，现在正在进入现实世界应用的原型演示阶段。这些原型需要改进的稳健性、封装、与MEMS驱动电子器件和培训软件的集成。提出的目标