Sensorics and Elements of Artificial Intelligence (FSI-GSE-A)

Academic year 2018/2019
Supervisor: Ing. Pavel Houška, Ph.D.  
Supervising institute: ÚAI all courses guaranted by this institute
Teaching language: English
Aims of the course unit:
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.
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 about control, design of control systems and electronics fundamentals.
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                  
    Labs and studios  13 × 1 hrs. compulsory                  
Course curriculum:
    Lecture 1. Introduction, basic terminology and general characteristic of sensors
2. Sensor modelling and identification
3. Methods of sensor connection - analog connections
4. Methods of sensor connection - digital interfaces
5. Principles of SMART sensors
6. Integrated and MEMS sensors
7. Sensors for electrical quantities measurement
9. Sensors for positions, velocity and acceleration measurement
10. Sensors for pressure, tension, force and torque measurement
11. Sensors for flow, flow rate and mass measurement
12. Sensors for level, density and viscosity measurement
13. Special sensors
    Labs and studios 1-2. Introduction to LabVIEW and DAQ
3-4. Introduction to measurement of analog quantities
5-6. Static characteristic of Aripot
7-8. Temperature sensing
9-10. Position sensing
11-12. Force and mass sensing
13. Laboratory works finishing , credit
Literature - fundamental:
1. Fraden, Jacob: Handbook of Modern Sensors - Physics, Designs and Applications (3rd Edition), Springer - Verlag, 2004
2. Isermann, Rolf: Mechatronic systems—fundamentals, Springer Netherlands, 2008
3. Mitchell, H.B: Multi-Sensor Data Fusion - An Introduction, Springer - Verlag, 2007
4. LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com
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. Daďo S., Kreidel M.: Senzory a měřicí obvody. Praha. ČVUT 1996
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  
M2I-Z visiting student M-STI Mechanical Engineering -- Cr,Ex 6 Recommended course 2 1 W