Sensorics and Elements of Artificial Intelligence (FSI-GSE)

Academic year 2020/2021
Supervisor: Ing. Pavel Houška, Ph.D.  
Supervising institute: ÚVSSR all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
Theoretical fundamentals and practical know-how of applied sensors. Sensor applications are pointed to automation and mechatronics. Acquired knowledge enables students to integrate into teams dealing with implementation of advanced systems within interdisciplinary fields in engineering practice.
Learning outcomes and competences:
Measurement fundamentals, signal processing methods (DAQ) and sensors overview based on various physical principles and sensors applications in practice. Introduction to modern sensor trends, sensor fusion and integration, artificial intelligence methods.
Prerequisites:
Theoretical knowledge of physics, fundamentals of electronics and algorithmization.
Course contents:
Fundamentals of electrical quantities measurement, data processing. Sensors fundamentals, selection, utilization and characteristics of sensors: temperature, proximity, position, velocity and acceleration; force, torque, mass, pressure and flow. Selection of control systems, DAQ, signal conditioning, communication busses, SMART sensors and complex sensors systems.
Teaching methods and criteria:
The course is taught through lectures explaining the basic principles and theory of the discipline. Teaching is suplemented by practical laboratory work.
Assesment methods and criteria linked to learning outcomes:
Course credit award requirements: active participation in laboratories, elaboration and commit of laboratory reports. Examinations: written and oral, classified by ECTS.
Controlled participation in lessons:
Attendance at lectures is recommended, attendance at seminars is monitored. Maximally two absence are compensated by individual missing laboratory reports working out.
Type of course unit:
    Lecture  13 × 2 hrs. optionally                  
    Laboratory exercise  13 × 1 hrs. compulsory                  
Course curriculum:
    Lecture 1. Introduction, basic terminology and general characteristic of sensors
2. Inputs and output of the digital systems
3. DAQ introduction
4. Temperature sensors
5. Opto-electrics sensors
6. Position sensors and detectors
7. Acceleration sensors and gyroscopes
8. Force, torque and mass sensors
9. Pressure sensors
10. Flow and level sensors
11-13. Communications protocols
    Laboratory exercise 1-3. Introduction to LabVIEW and DAQ
4-6. Static characteristic of Aripot
7-9. Temperature sensing
10-12. Position and velocity measuremnt
13. Laboratory works finishing , credit
Literature - fundamental:
1. Handbook of Modern Sensors: Physics, Designs, and Applications 5th ed. 2016 Edition, Springer International Publishing, Switzerland 2016
2. Frank Lamb: Industrial Automation: Hands-On, McGraw-Hill Education, 2013
3. Daďo S., Kreidel M.: Senzory a měřicí obvody. Praha. ČVUT 1996
Literature - recommended:
1. Getting Started with NI LabVIEW Student Training, National Instruments, dostupné z http://zone.ni.com/devzone/cda/tut/p/id/7466
2. LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com
3. Husák M.: Senzorové systémy. Praha, ČVUT 1993
4. Zehnula, K.: Čidla robotů. Praha, SNTL 1990
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
M2A-P full-time study M-MET Mechatronics -- Cr,Ex 6 Compulsory 2 2 W