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, JulienJ
• 金额: $ 4.37万
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754375
• 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 proposedI2I 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.

我们已经开发了一种新的MEMS设备，这些设备可以在传感器中添加人工智能（AI）功能。这项独特的技术已在实验室中得到了彻底的验证，现在正在现实世界应用中进入原型演示阶段。这些原型要求改善鲁棒性，包装，与MEMS驱动电子和培训软件的集成。提出的I阶段项目的目的是通过创建AI-MEMS传感器平台来自动检测有故障的机械，以在工业环境中触发先发制的维护操作，从而实现这些改进。拟议的AI-MEMS传感器将很小，完全自主，并且适用于工业环境。他们将接受训练，可以将异常条件与正常手术分开，并无线报告异常。