Mechanical Vibrations and Condition Monitoring

Juan Carlos Jauregui is a Professor at the Universidad Autonoma de Queretaro, in Mexico, where he researches the design and dynamics of machinery. He obtained his PhD at the University of Wisconsin-Milwaukee. He has been responsible for the design of a large number of automatic, tailor-made industrial machines, and the development of monitoring systems based on vibration analysis. He is a member of ASME (the American Society of Mechanical Engineers), the Mexican Society of Mechanical Engineering, the Academy of Engineering (Mexico), IFToMM, and the National Research System, the most prestigious research evaluation program in Mexico. He has published over 70 papers in international journals, several chapters, and three books, including Parameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration, also published by Elsevier (in 2014). Along with Alejandro Lozano-Guzman, he pioneered the introduction to Mexico of monitoring systems based on vibration analysis.Alejandro Lozano-Guzman is a Professor at CICATA Querétaro, in Mexico. His research focusses on mechanical systems analysis, particularly mechanical vibrations and condition monitoring systems. He holds a PhD from the University of Newcastle upon Tyne in the UK. He was a founding member of the Mexican Society for Mechanical Engineering, President of the Specialty of Mechanical Engineering at the Mexican Academy of Engineering, Secretary of the National Network of Science and Technology Councils, and organizer of the Aerospace Research and Innovation Network for Querétaro. He has published 31 articles in mechanical systems analysis and is a member of the National Research System. Along with Juan Carlos Jauregui, he pioneered the introduction to Mexico of monitoring systems based on vibration analysis.

1. Fundamentals of mechanical vibrations2. Spectral analysis3. Instruments4. Causes and effects of vibration5. Alignment and balancing methods6. Practical cases7. Guidelines for the implementation of a predictive maintenance program8. Conditioning monitoring