Machine vision and Sensor technology (5 cr)

Objective

On completion of the course, the student
• is able to apply sensors and measuring equipment in measurements, and is familiar with various possibilities for data transmission
• knows the effects of noise and disruptions in measurements, and is able to prevent them
• is able to shape a digital measurement signal
• is familiar with the possibilities and principles of machine vision
• is able to use suitable software to recognise and dimension objects from a picture
• is able to filter a picture for machine vision operations.

Content

• Sensors and wiring in machine automation applications
• Use of sensors, equipment and data transmission in practice
• Digital signal processing
• Basics of machine vision
• Components of a machine vision system
• Filtering of a picture
• Morphological operations
• Picture formats

Teaching methods

Itsenäisenä suorituksena SICK-anturikurssi
Seminaariesityskset
Laboraatioharjoitukset
Konenäön PC-harjoitukset itsenäisenä suorituksena
Antureihin liittyvät PC-harjoitukset ohjatusti
Antureiden selvitystehtävä ja loppuesitys

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student
• knows the sensors used in machine automation and is able to connect and test sensors in an application
• is familiar with the most common needs for digital signal processing and is able to set the parameters for signal filtering
• knows the components of a machine vision system
• understands the principles of filtering a picture
• is familiar with the term of morphology and with the most common picture formats.

Assessment criteria, good (3)

The student
• knows the sensors and their wiring used in machine automation
• can choose, connect and commission the necessary sensors for various applications
• recognises the need for signal processing and is able to shape signals according to the needs
• can choose the components for a machine vision system
• can choose a suitable filtering method for a picture, and use morphologic operations
• can change the format of a picture.

Assessment criteria, excellent (5)

The student
• knows the sensors and measuring equipment, including the wiring, in machine automation applications
• can choose the necessary sensors and equipment for a machine automation application and is able to commission them
• is able to apply signal processing to measurements
• can compare different machine vision systems and select the correct system principle
• can optimise the chosen filtering and morphologic operation
• can select the optimal picture format for each application.

Assessment criteria, approved/failed

The student
• knows the sensors used in machine automation and is able to connect and test sensors in an application
• is familiar with the most common needs for digital signal processing and is able to set the parameters for signal filtering
• knows the components of a machine vision system
• understands the principles of filtering a picture
• is familiar with the term of morphology and with the most common picture formats.

Assessment methods and criteria

Yhteensä max. 100 p.
• Läpipääsyn alaraja 40 p.
• Pisteytys suorituksista:
• SICK-anturikurssi. 12 p. (täydet pisteet kun tehty ja palautettu ajoissa)
• Seminaariesitys + vertaisarviointi 15 p
• Esitys 10 p
• Vertaisarviointi (täydet pisteet kaikilla kerroilla läsnä antamassa
palautetta muille) 5 p
• Labrat 20 p (4 x 5 p)
• Yhteensä 4 labraa, jotka tehdään koululla r1 ja r2
• Konenäön PC-harjoitukset tehty ja selostukset palautettu 30 p (6 kpl x 5p,
itsenäinen suoritus omalla ajalla)
• Antureihin liittyvät PC-harjoitukset 4+4 p (2 harjoitusta, jotka tehdään
yhdessä tunnilla)
• Antureiden ”selvitystehtävä” lisäinfoa erillisellä kalvolla 15 p.

Qualifications

Basics of Automation and Measurement Technology

Objective

On completion of the course, the student
• is able to apply sensors and measuring equipment in measurements, and is familiar with various possibilities for data transmission
• knows the effects of noise and disruptions in measurements, and is able to prevent them
• is able to shape a digital measurement signal
• is familiar with the possibilities and principles of machine vision
• is able to use suitable software to recognise and dimension objects from a picture
• is able to filter a picture for machine vision operations.

Content

• Sensors and wiring in machine automation applications
• Use of sensors, equipment and data transmission in practice
• Digital signal processing
• Basics of machine vision
• Components of a machine vision system
• Filtering of a picture
• Morphological operations
• Picture formats

Qualifications

Basics of Automation and Measurement Technology