Room 326 McLaughlin Hall
Phone: (613) 533-3148/2575
FAX: (613) 533-6489
Chris K Mechefske received his undergraduate training (B.Sc. Eng.) at the University of Guelph in Canada (1989) and Ph.D. (Mech. Eng.) at Monash University, Melbourne, Australia (1992). He has worked as a Research Engineer for Powertech Labs in Vancouver, Canada (1993-95), as a Senior Lecturer at Victoria University of Technology, Melbourne, Australia, (1995-97), and as an Assistant Professor at the University of Western Ontario, London, Ontario, Canada (1997-2001). He is currently a Professor in the Department of Mechanical and Materials Engineering at Queen's University in Kingston, Canada.
Areas of Research
- vibration and noise reduction
- vibration based machine condition monitoring and fault diagnostics
- June 2014 - Dr. Mechefske was named a Fellow of the Canadian Society of Mechanical Engineers.
- September 2003 - Dr. Mechefske was awarded the Gunma University Science and Technology Foundation Award, which provides funding for collaborative visits to Gunma University, Kiryu, Japan.
- September 2001 - Dr. Mechefske was awarded the Ontario Premier's Research Excellence Award for his work on reducing noise in and around magnetic resonance imagers (MRIs).
- 1998 - Dr. Mechefske was awarded the National Science Foundation's New Faculty Fellow Award for the best paper by a new faculty member at the 1998 Frontiers in Education Conference.
- Canadian Society of Mechanical Engineers - Fellow
- American Society of Mechanical Engineers - Member
- Canadian Advisory Council for ISO TC08 SC5 - Member
- Canadian Machinery Vibration Association - Member, Past President
- International Journal of COMADEM - Editorial Board Member
- International Institute for Acoustics and Vibration - Member and Director
Ongoing projects include acoustic noise and vibration modeling and reduction in various applications (MRI scanners, aircraft fuselage skin, mining skips and headfrane structures) and machine condition monitoring and fault diagnostics (remote equipment monitoring systems, monitoring systems for non-steady state systems, automatic machinery fault diagnosis). For more information please see System Dynamics Research Group homepage.