13E052PMS - Practicum of measurement and data acquisition systems

Course specification
Course title Practicum of measurement and data acquisition systems
Acronym 13E052PMS
Study programme Electrical Engineering and Computing
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 3.0 Status elective
Condition none
The goal Introduce students to the basics of data acquisition and real-time programming.
The outcome At the end of the course, students should be able to independently design virtual instrumentation for measurement and control as well as modular, stand-alone interface for real-time data acquisition and processing.
URL to the subject page
URL to lectures
Contents of lectures Principles of data acquisition in Labview, Arduino and Python environment. Software modularity. Data flow programming. Sequential programming. Machine state. Race conditions. Synchronization techniques. Event programming. File I/O techniques. Error handling. Code optimization. Basics of image acquisition: setting up Field of View, exposure time, triggering, camera calibration.
Contents of exercises Setting up data acquisition hardware. Troubleshooting and debugging. Using local, global and functional global variables. Using arrays, clusters and type definitions. Creating SubVIs. Methods for controlling the user interface. Using events. Synchronization techniques. Using spreadsheet, bitmap and TDMS files. Creating a stand-alone application.
  1. Labview Core 1 Participant Guide, National Instruments, November 2014 (Original title)
  2. Labview Core 2 Participant Guide, National Instruments, November 2014 (Original title)
  3. Kye-Si Kwon and Steven Ready, "Practical Guide to Machine Vision Software - An Introduction with LabVIEW", Wiley-VCH Verlag GmbH & Co. KGaA, Germany, 2015. (Original title)
  4. Jeremy Blum, "Exploring Arduino: Tools and Techniques for Engineering Wizardry", John Wiley&Sons Inc, Indiana, 2013. (Original title)
  5. Vernon L. Ceder, "The Quick Python Book", Manning Publications Co, United Kingdom, 2010. (Original title)
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
0 1 2
Methods of teaching For each lesson, after explaining the theoretical principles and illustration through the examples (practice), students have the opportunity to apply new knowledge by working the appropriate exercises (labwork).
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 45
Practical lessons 0 Oral examination
Colloquia 10
Seminars 45