Location of Thesis Examination

Room 2009A Spencer Engineering Building

Degree

Doctor of Philosophy

Program

Mechanical and Materials Engineering

Supervisor

Dr. Evgueni Bordatchev, Dr. Jun Yang

Abstract

Monitoring automobile liquids, such as engine lubricants, has received increasing attention recently mainly due to environmental and safety legislation, coat saving measures, and customer demand.

Literature review in monitoring engine lubricant condition indicates systems approach, an intellectual discipline method to address complex problem, has never been used to monitor engine performance and health through the engine sub-systems such as lubricant system. The literature review also points toward deficiency in considering lubricant as a source of information for engine performance evaluation, and lack of understanding of engine lubricant as a medium with random properties.

Engine lubricant condition reflects the state of health of engine through its properties. Recognition and analysis of the correlation between engine lubricant system based on the lubricant properties and engine performance is crucial to provide insight into engine health.

The contribution of this research will be implementation of systems approach to monitor engine performance through engine lubricant using new methodologies of surface plasmon resonance, object shape based optical analysis and statistical optical analysis methodologies to monitor optical properties of lubricant with respect to aging process and contaminants in real time and on-line.

Degradation of engine lubricant causes variation in the optical properties of lubricant such as refractive index, absorption, statistical optical characteristics, shape parameters and etc. The purpose of using surface plasmon resonance (SPR) is to study the change in the reflectivity and incidence angle caused by variation in the refractive index and absorption of lubricant due to its degradation and presence of contaminants. Utilization of SPR measurement for characterization of engine lubricant will develop new knowledge which can be used for on-line condition monitoring of lubricant quality.

To investigate the variation in statistical optical characteristics of lubricant, this research also introduces two new methodologies. Statistical optic and object shape-based methodologies are based on the optical analysis of the distortion effect when an object image is obtained through a thin random medium. In the object shape-based optical analysis, several parameters of an acquired object image are measured and compared. In the statistical optic analysis methodology, statistical auto and cross-characteristics are used for the analysis of combined object-lubricant images. Both proposed methodologies utilize the comparison of measured and calculated parameters for fresh and contaminated lubricants.

Proposed methodologies are verified experimentally showing ability to distinguish lubricant with different contamination individually and in a combined form. Capabilities of the proposed methodologies are extended to establish the linkage between accumulated travelled distance and the change in the optical statistical properties of the lubricant. Also, on board analysis to detect the presence of coolant, gasoline and water (1%-5%) are performed.