ZHU_JUNDA.pdf (3.25 MB)
Online Industrial Lubrication Oil Health Condition Monitoring, Diagnosis and Prognostics
thesis
posted on 2013-10-24, 00:00 authored by Junda Zhuto increase wind energy production rate, there is an urging need to improve the wind turbine availability and reduce the operational and maintenance costs. The safety and reliability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as gearbox and means for lubrication oil condition monitoring and degradation detection. In comparison with current vibration based machine health monitoring, online lubrication oil diagnostic solutions provide over 10 times earlier warning of possible machine failure. The purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oil has deteriorated to such a degree that it no longer fulfills its function in real time. A comprehensive review of current state of the art lubrication oil condition monitoring techniques and solution has been conducted. Viscosity and dielectric constant are selected as the performance parameters to model the degradation of lubricant based on the result of the literature review. Physics models have been developed to quantify the relationship between lubricant degradation level and the performance parameters. Commercially available viscosity and dielectric sensors have been acquired and installed in a temperature controlled chamber to validate the developed performance parameter based lubrication oil deterioration physics models. Particle filtering techniques are introduced and adapted to predict the remaining useful life of lubrication oil based on the developed physics models. The developed prognostic methodology has been implemented into two case studies to test the effectiveness and the robustness of the developed remaining useful life (RUL) prediction algorithm.
History
Advisor
He, DavidDepartment
Mechanical and Industrial EngineeringDegree Grantor
University of Illinois at ChicagoDegree Level
- Doctoral
Committee Member
Brown, Michael Li, Lin Darabi, Houshang Bechhoefer, EricSubmitted date
2013-08Language
- en
Issue date
2013-10-24Usage metrics
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