Course detail

Sensorics and Data Processing

FSI-GSZ-KAcad. year: 2019/2020

Fundamentals of electrical quantities measurement, A/D and D/A convertors and signal conditioning. Communication busses and protocols for sensors and sensor systems. Fundamentals of sensors with electric outputs. Selection and utilization of sensors for production machines and systems. Introduction into design and implementation of DAQ systems, data processing and archiving.

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, the industrial communication protocols in sensorics and DAQ.

Prerequisites

Theoretical knowledge of physics, fundamentals of electronics and algorithmization.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Handbook of Modern Sensors: Physics, Designs, and Applications 5th ed. 2016 Edition, Springer International Publishing, Switzerland 2016
Frank Lamb: Industrial Automation: Hands-On, McGraw-Hill Education, 2013
LabVIEW Measurements Manual, National Instruments, April 2003 Edition, Part Number 322661B-01, dostupné z www.ni.com
Behzad Ehsani: Data Acquisition using LabVIEW, Packt Publishing, 2016

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.

Language of instruction

Czech

Work placements

Not applicable.

Aims

Theoretical fundamentals and practical know how of the applied sensorics, data acquisition (DAQ) and industrial communication protocols. The course focused on the field of modern production machines and systems, mobile robotics and standalone testing. 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.

Classification of course in study plans

  • Programme M2I-K Master's

    branch M-VSR , 2. year of study, summer semester, 5 credits, compulsory

Type of course unit

 

Guided consultation

9 hours, optionally

Teacher / Lecturer

Syllabus

1. Introduction, basic terminology and general characteristic of sensors
2. Inputs and output of the digital systems
3-4. DAQ introduction
5. DAQ of slow process - temperature and humidity
6. DAQ of fast process - position and velocity
7. DAQ of dynamics process – velocity, acceleration, force and torque
8. Process sensors
9-10. Communications protocols
11. DAQ hardware
11-13. DAQ multi instruments synchronization

Laboratory exercise

9 hours, compulsory

Teacher / Lecturer

Syllabus

1-3. Introduction to LabVIEW and DAQ
4-6. Static characteristic of Aripot
7-8. Position and velocity measurement
9-12. Sensors net
13. Laboratory works finishing , credit

Controlled Self-study

34 hours, optionally

Teacher / Lecturer

Syllabus

1. Introduction, basic terminology and general characteristic of sensors
2. Inputs and output of the digital systems
3-4. DAQ introduction
5. DAQ of slow process - temperature and humidity
6. DAQ of fast process - position and velocity
7. DAQ of dynamics process – velocity, acceleration, force and torque
8. Process sensors
9-10. Communications protocols
11. DAQ hardware
11-13. DAQ multi instruments synchronization

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