Machine vision and Sensor technology (5 ECTS)
Code: TX00BU98-3005
General information
- Enrollment
-
04.05.2020 - 31.08.2020
Registration for the implementation has ended.
- Timing
-
24.08.2020 - 31.12.2020
Implementation has ended.
- Number of ECTS credits allocated
- 5 ECTS
- Mode of delivery
- On-campus
- Unit
- (2019-2024) School of Automotive and Mechanical Engineering
- Campus
- Eerikinkatu 36
- Teaching languages
- Finnish
- Seats
- 1 - 40
- Degree programmes
- Mechanical Engineering
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
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.
Qualifications
Basics of Automation and Measurement Technology