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

• 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

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.

该创新合作伙伴关系 - 技术转化 (PFI-TT) 项目的更广泛影响/商业潜力是开发智能在线实时润滑油健康监测系统，以维持和延长许多关键行业中使用的高速旋转和往复式机械的健康状况。完整的系统将消除检查停机的需要，从而显着降低运营成本，同时避免运行期间发生灾难性的组件故障。 应用包括轴承、涡轮机械变速箱，甚至风电场、运输、制造和国防工业等领域的内燃机。该系统预计将为机械故障提供重要的早期预警，并将用于制定更有效的维护计划，以降低机器运营成本并避免灾难性故障。拟议项目旨在开发一个全面的润滑油状况监测系统，提供污染物碎片和润滑油质量的实时特征，以判断机器的运行健康状况。目标包括：1）感应脉冲传感和微流体信号复用技术将用于检测润滑油中的细小磨损碎片，从而能够监测整个磨损进程； 2）将采用实时处理来显着减少需要分析和存储的数据量； 3) 润滑油特性传感阵列将同时测量多种油品特性； 4) 人工神经网络将高精度地将测量的传感器信号与石油特性联系起来，消除交叉敏感性。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Oil property sensing array based on a general regression neural network

• DOI: 10.1016/j.triboint.2021.107221
• 发表时间: 2021-08-09
• 期刊: TRIBOLOGY INTERNATIONAL
• 影响因子: 6.2
• 作者: Jiao, Dian;Urban, Aaron;Zhe, Jiang
• 通讯作者: Zhe, Jiang

A Microsensor Array for Diesel Engine Lubricant Monitoring Using Deep Learning with Stochastic Global Optimization

• DOI: 10.1016/j.sna.2022.113671
• 发表时间: 2022-06
• 期刊: Sensors and Actuators A: Physical
• 作者: Aaron Urban;Jiang Zhe

A non‐contact gap measurement method for narrow and irregular targets using inductive planar sensors with simple calibration

一种使用简单校准的电感式平面传感器对狭窄和不规则目标进行非接触式间隙测量的方法

• DOI: 10.1049/smt2.12071
• 发表时间: 2021
• 期刊: Measurement & Technology
• 作者: Jiao, Dian;Ni, Liwei;Yu, Xueyang;Zhe, Jiang
• 通讯作者: Zhe, Jiang