Date of Award
Mechanical, Automotive, and Materials Engineering
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This study was undertaken to investigate and develop engine defect detection methods using NVH indicators for future implementation into an on-line test system in a production environment. These methods utilized noise and vibration measurements collected from a variety of transducers to successfully detect lower-end engine defects. The on-line experimental testing of 5.4L V8 engines was conducted at one of the in-process Cold Test stations at the Ford Windsor Engine Plant. Transducers used included accelerometers, microphones, knock sensors and a laser vibrometer. The optimal measurement locations were found to be at each of the 4 locating lugs of the engine. Baseline measurements were made and based upon these results, control limits were established regarding the acceptable noise and vibration levels an engine can exhibit. A fault diagnosis algorithm that utilized variance analysis and RMS values was developed to detect lower-end engine defects. The algorithm was successful in identifying defect-free engines as well as detecting lower-end faults such as a non-machined cylinder bore, a cylinder bore containing a deep groove and connecting rod knock. The transducers found to be most effective in detecting noise and vibration were the accelerometer and the laser vibrometer. The knock sensor and microphone were found to be inconsistent in their ability to detect noise and vibration. Therefore, it was concluded that the development of an on-line test system that can successfully diagnose engine defects through the use of NVH indicators is feasible and would ultimately reduce the number of defective engines being produced.Dept. of Mechanical, Automotive, and Materials Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .L45. Source: Masters Abstracts International, Volume: 41-04, page: 1181. Adviser: R. Gaspar. Thesis (M.A.Sc.)--University of Windsor (Canada), 2002.
Leitzinger, Eric R., "Development of in-process engine defect detection methods using NVH indicators." (2002). Electronic Theses and Dissertations. 1713.