Course detail

Sensorics and Elements of Artificial Intelligence

FSI-GSEAcad. year: 2019/2020

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.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

Ing. Pavel Houška, Ph.D.

Department

Institute of Production Machines, Systems and Robotics (ÚVSSR)

Learning outcomes of the course unit

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.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

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.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

Theoretical fundamentals and practical know-how of applied sensorics. Sensor applications are pointed to automation and mechatronics. Acquired knowledge enables students to integrate into realisation teams solving system development, projection and production of intelligent systems and interdisciplinary tasks in engineering practice.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is recommended, attendance at seminars is monitored. Maximally two absence are compensated by individual missing laboratory reports working out.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Frank Lamb: Industrial Automation: Hands-On, McGraw-Hill Education, 2013 (EN)
Handbook of Modern Sensors: Physics, Designs, and Applications 5th ed. 2016 Edition, Springer International Publishing, Switzerland 2016 (EN)

Recommended reading

Getting Started with NI LabVIEW Student Training, National Instruments, dostupné z http://zone.ni.com/devzone/cda/tut/p/id/7466 (EN)
Husák M.: Senzorové systémy. Praha, ČVUT 1993 (CS)
LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com (EN)
Zehnula, K.: Čidla robotů. Praha, SNTL 1990 (CS)

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme M2A-P Master's

    branch M-MET , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Pavel Houška, Ph.D.

Syllabus

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

13 hod., compulsory

Teacher / Lecturer

Ing. Pavel Houška, Ph.D.

Syllabus

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

Elearning

eLearning: currently opened course