Skip to content
Sergio Martin Del Campo Barraza
Sergio Martin Del Campo Barraza

Sergio Martin Del Campo Barraza

Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
sergio.martindelcampo@ltu.se
+46 (0)920 493032
A2316 Luleå

Brief Information

I am a post-doc at the EISLAB division of the department of Computer Science, Electrical and Space Engineering. Simultaneously, I belong to the SKF-LTU University Technology Center for advanced condition monitoring.

Currently, I focus on ​the use of machine learning to the analysis of time wave signals on condition monitoring applications. In particular, the diagnosis of rotating machinery (i.e. wind turbines) using methods that could be implemented in resource constrained devices.

My research interests include:

  • Machine intelligence
  • Sparse coding
  • Dictionary learning
  • Anomaly detection
  • Time series analysis
  • Bio-inspired computation

History

I was born 1983 in Guadalajara, Mexico. I received my BSc in Mechatronic Engineering from the Monterrey Institute of Technology and Higher Education (ITESM), Campus Guadalajara in 2007. During 2007 to 2010, I worked as Design Engineer of Electrical Systems at GE-Aviation. I started my master degree education in 2010 with an Erasmus Mundus scholarship from the European Comission. I received my double degree of MSc in Space Science and Technology in 2012 from Luleå University of Technology and Julius Maximilians University of Würzburg. I started as a PhD student at Luleå University of Technology in 2013 and received my PhD degree in 2017. The main focus of my PhD was the use of machine learning on industrial applications.

Related documents

Publications

Article in journal

Algorithmic performance constraints for wind turbine condition monitoring via convolutional sparse coding with dictionary learning (2021)

Martin-del-Campo. S, Sandin. F, Schnabel. S
Journal of Risk and Reliability, Vol. 235, nr. 4, s. 660-675
Article in journal

Dictionary Learning Approach to Monitoring of Wind Turbine Drivetrain Bearings (2021)

Martin-del-Campo. S, Sandin. F, Strömbergsson. D
International Journal of Computational Intelligence Systems, Vol. 14, nr. 1, s. 106-121
Conference paper

Unsupervised Ranking of Outliers in Wind Turbines via Isolation Forest with Dictionary Learning (2020)

Martin-del-Campo. S, Al-Kahwati. K
Part of: PHME 2020, Proceedings of the 5th European Conference of the Prognostics and Health Management Society 2020, PHM Society, 2020
Article in journal

Detection of particle contaminants in rolling element bearings with unsupervised acoustic emission feature learning (2019)

Martin del Campo Barraza. S, Schnabel. S, Sandin. F, Marklund. P
Tribology International, Vol. 132, s. 30-38
Conference paper

Kinematic Frequencies of Rotating Equipment Identified with Sparse Coding and Dictionary Learning (2019)

Martin del Campo Barraza. S, Sandin. F, Schnabel. S
Part of: Proceedings of the Annual Conference of the Prognostics and Health Management Society 2019, Prognostics and Health Management Society, 2019