PFI-TT: Translating an intelligent lubricant condition monitoring system into a commercially viable prototype

PFI-TT：将智能润滑油状态监测系统转化为商业上可行的原型

基本信息

批准号：
1940879
负责人：
Jiang Zhe
金额：
$ 25万
依托单位：
University of Akron
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940879&HistoricalAwards=false
关键词：
PFI TT Translating intelligent lubricant

项目摘要

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to develop an intelligent online real-time lubricant oil health monitoring system to maintain and extend the health of high-speed rotating and reciprocating machinery used in many key industries. The completed system will significantly reduce operation costs by eliminating the need for inspection shutdowns, while avoiding catastrophic component failure during operation. Applications include bearings, turbomachinery gearboxes, and even combustion engines in sectors such as the wind farm, transportation, manufacturing and defense industries. The system is expected to provide an important early warning of mechanical failure and will be used to develop more efficient maintenance schedules to reduce machine operation costs and avoid catastrophic failure.The proposed project aims to develop a comprehensive lubricant oil condition monitor system offering real-time characterization of contaminant debris and lubricant oil quality to judge a machine’s operating health. Objectives include: 1) inductive pulse sensing and microfluidic signal multiplexing technologies will be used to detect fine wear debris in lubricant oil to enable monitoring of the entire wear progression; 2) real-time processing will be used to significantly reduce the data size to be analyzed and stored; 3) a lubricant property-sensing array will measure multiple oil properties simultaneously; 4) an artificial neural network will link measured sensor signals to oil properties with high accuracy, eliminating cross-sensitivities.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.

这种伙伴关系对创新 - 技术翻译（PFI-TT）项目的更广泛的影响/商业潜力是开发一个智能的在线实时润滑油油健康监测系统，以维护和扩展许多在许多关键工业中使用的高速旋转和回报机械的健康。完成的系统将通过消除检查的需求，在避免操作过程中避免灾难性组件故障，从而大大降低操作成本。应用包括轴承，涡轮机械变速箱，甚至包括风电场，运输，制造和国防行业等领域的混合发动机。该系统有望提供机械故障的重要预警，并将用于制定更有效的维护时间表，以降低机器运营成本并避免灾难性故障。该项目旨在开发全面的润滑油机油状况监测仪，从而为污染物碎屑和润滑油油质提供实时表征，以判断机器的运营状况。目标包括：1）电感脉冲灵敏度和微流体信号多路复用技术将用于检测润滑油中的细磨损碎屑，以便监测整个磨损进展； 2）实时处理将用于显着减少要分析和存储的数据大小； 3）润滑剂特性感应阵列将简单地测量多个石油性能； 4）人工神经网络将以高准确性将测量的传感器信号与石油特性联系起来，消除了跨敏感性。该奖项反映了NSF的法定任务，并使用基金会的知识分子和更广泛的影响审查标准，被视为通过评估来获得珍贵的支持。