Date of Award
Mechanical, Automotive, and Materials Engineering
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
This study was performed to improve defect detection in the assembly process of internal combustion engines for a major engine manufacturer. The main objectives of this thesis are to identify and locate missing connecting rod inserts in a partially assembled V-8 engine, establish baseline operating conditions for this engine, and determine the feasibility of using a laser vibrometer as a non-contact transducer for vibration measurements in a manufacturing environment. Variance analysis was employed to locate defects in engine vibration signatures with respect to the crankshaft position. These statistical methods are independent of time so the naturally occurring speed fluctuations of the engine are insignificant. The non destructive diagnostic methods presented in this thesis are to be implemented into the in-process test stands on the engine assembly line. These methods will be used to detect the defects discussed herein and can be adapted to detect many other manufacturing and assembly defects early in the assembly process. The transducers used for this study include accelerometers, microphones and a laser vibrometer. Data was acquired with a custom designed 24 channel data acquisition system using special software. (Abstract shortened by UMI.)Dept. of Mechanical, Automotive, and Materials Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .R68. Source: Masters Abstracts International, Volume: 39-02, page: 0538. Adviser: Robert Gaspar. Thesis (M.A.Sc.)--University of Windsor (Canada), 2000.
Rowe, Andrea Christine., "Engine defect source identification by enhanced signature analysis." (2000). Electronic Theses and Dissertations. 1930.