Pattern Recognition Applications in Engineering

Pattern Recognition Applications in Engineering

Release Date: December, 2019|Copyright: © 2020 |Pages: 357
DOI: 10.4018/978-1-7998-1839-7
ISBN13: 9781799818397|ISBN10: 179981839X|EISBN13: 9781799818410
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Description & Coverage
Description:

The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking.

Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Bio-Inspired Developments
  • Chemical Processes
  • Clustering
  • Condition Monitoring
  • Data Acquisition
  • Data Mining
  • Data Normalization
  • Feature Extraction
  • Pre-Processing Strategies
  • Sensor Fusion
Reviews & Statements

“The need for renewable energies in a world in transition is unquestionable. Wind energy is crucial in this sense, to avoid energy dependence. It is of utmost importance for the wind industry to move from corrective and preventive maintenance to so-called predictive maintenance. Digitalization, machine learning, pattern recognition and artificial intelligence are key technologies for this strategy, to better exploit the information from the large amount of data coming from different sensors acquired from the assets.”

– Francesc Pozo, Universitat Politècnica de Catalunya
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Editor/Author Biographies
Diego Alexander Tibaduiza Burgos received his Electronic Engineer Degree from the Industrial University of Santander, Colombia in 2003, the M.Sc. degree in 2006 from the same university and his Doctoral Degree in 2013 from the Universitat Politècnica de Catalunya in Barcelona, Spain. He is the author and coauthor of more than 80 publications in journals, conferences, books and chapter books. Currently, Dr. Tibaduiza is a titular professor in the Faculty of Electronics Engineering at the Universidad Santo Tomás in Bogotá, Colombia. His research interest includes Structural Health Monitoring, Artificial Intelligence, Control Systems, Robotics and Signal Processing.

Maribel Anaya Vejar received in 2005 her Electronic Engineer Degree from the Industrial University of Santander in Colombia, the M.Sc. degree in 2010 in electronic engineering from the same university. Her Doctoral Degree was obtained in 2016 from the “Universitat Politècnica de Catalunya” in Barcelona-Spain, where she worked in the Structural Health Monitoring area focused on pattern recognition techniques. Her research interest includes Structural Health Monitoring, Artificial Intelligence, Pattern Recognition and Signal Processing.

Francesc Pozo received the degree in mathematics from the University of Barcelona, Barcelona, Spain, in 2000, and the Ph.D. degree in applied mathematics from the Universitat Politècnica de Catalunya, Barcelona, in 2005. Since 2000, he has been with the Department of Mathematics and the Barcelona East School of Engineering (EEBE), Universitat Politècnica de Catalunya, where he is currently an Associate Professor with the Control, Modeling, Identification and Applications Research Group (CoDAlab, codalab.upc.edu/en). He is also a Teaching Collaborator at the Open University of Catalonia, Barcelona. His research interests include wind turbine control, semiactive vibration mitigation in civil engineering structures (buildings and bridges), automotive and aeronautic systems, and offshore support structures, structural health monitoring (SHM) and condition monitoring (CM) for wind turbines and, in general, the application of applied mathematics in engineering problems. Dr. Pozo serves as a Secretary of the Spanish Joint Chapter of the IEEE Control Systems Society (CSS) and the IEEE Industrial Applications Society (IAS). He is also a member of the European Association for the Control of Structures (EACS) and an Editorial Board Member for international journals, such as Sensors, Structural Control and Health Monitoring, Journal of Vibration and Control, International Journal of Distributed Sensor Networks and Mathematical Problems in Engineering. Dr. Pozo is author of more than 55 research papers, 13 book chapters and 120 conference papers.

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