Sensor TechnologyLaajuus (5 cr)
Code: TE00BO34
Credits
5 op
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Enrollment
02.12.2024 - 31.12.2024
Timing
13.01.2025 - 31.05.2025
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Teaching languages
- English
Degree programmes
Teachers
- Jarno Tuominen
Groups
-
MKEMIK23
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Materials
To be announced later
Teaching methods
Contact teaching ~15 hours
Group work + remote exercises ~110 hours
Student workload
Self study 110 h
Guided sessions 15 h
Content scheduling
Sensor structures and functionality
* Heat sensors
* Pressure sensors
* Acceleration sensors
* Flowrate sensors
Evaluation scale
H-5
Assessment methods and criteria
Exercises
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores
Enrollment
01.06.2024 - 15.09.2024
Timing
18.09.2024 - 15.12.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Campus
Lemminkäisenkatu
Teaching languages
- English
Degree programmes
Teachers
- Jarno Tuominen
Groups
-
MKEMIK22
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Materials
To be announced later
Teaching methods
Contact teaching ~15 hours
Group work + remote exercises ~110 hours
Student workload
Self study 110 h
Guided sessions 15 h
Content scheduling
Sensor structures and functionality
* Heat sensors
* Pressure sensors
* Acceleration sensors
* Flowrate sensors
Evaluation scale
H-5
Assessment methods and criteria
Exercises
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores
Enrollment
02.12.2023 - 26.01.2024
Timing
26.01.2024 - 30.04.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Campus
Lemminkäisenkatu
Teaching languages
- English
Degree programmes
Teachers
- Jarno Tuominen
Groups
-
MKEMIK21
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Materials
To be announced later
Teaching methods
Contact teaching ~15 hours
Group work + remote exercises ~110 hours
Student workload
Self study 110 h
Guided sessions 15 h
Content scheduling
Sensor structures and functionality
* Heat sensors
* Pressure sensors
* Acceleration sensors
* Flowrate sensors
Evaluation scale
H-5
Assessment methods and criteria
Exercises
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores
Enrollment
01.12.2022 - 20.01.2023
Timing
01.01.2023 - 31.07.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Teaching languages
- English
Degree programmes
Teachers
- Jarno Tuominen
Teacher in charge
Jarno Tuominen
Scheduling groups
- Vain avoimen AMK:n opiskelijoille (Tutkinto-opiskelija ilmoittaudu joka tapauksessa, toteutus ei ole vain avoimen opiskelijoille) (Size: 5. Open UAS: 5.)
Groups
-
MKEMIS20
Small groups
- For Open UAS studetns only
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Materials
To be announced later
Teaching methods
Contact teaching ~15 hours
Group work + remote exercises ~110 hours
Student workload
Self study 110 h
Guided sessions 15 h
Content scheduling
Sensor structures and functionality
* Heat sensors
* Pressure sensors
* Acceleration sensors
* Flowrate sensors
Evaluation scale
H-5
Assessment methods and criteria
Exercises
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores
Enrollment
01.12.2021 - 24.01.2022
Timing
11.01.2022 - 31.05.2022
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Engineering and Business
Teaching languages
- Finnish
- English
Degree programmes
Teachers
- Patric Granholm
Teacher in charge
Patric Granholm
Groups
-
MKEMIS19
Objective
After this course the student
* Understand the concepts of static and dynamic characterisation of sensors.
* Understand how sensors are calibrated.
* Can describe a sensor with a block diagram.
* Understands what error sources are connected to measurements
* Knows the most common measurements technologies used
Content
* Static characterisation, linearity, sensitivity, hysteresis, repeatability
* Dynamic characterisation, first and second order response
* Usage of block diagrams to describe sensors
* Basics of calibration
* Measurement signals and noise
* Sensor technologies, microsensors, electrochemical sensors
Materials
To be announced later
Teaching methods
Online teaching
Student workload
Self study 120 h
Guided sessions 15 h
Content scheduling
Sensor structures and functionality
* Heat sensors
* Pressure sensors
* Acceleration sensors
* Flowrate sensors
Evaluation scale
H-5
Assessment methods and criteria
Exercises
Assessment criteria, fail (0)
< 50 % of the scores
Assessment criteria, satisfactory (1-2)
50 - 75 % of the scores
Assessment criteria, good (3-4)
75 - 90 % of the scores
Assessment criteria, excellent (5)
> 90 % of the scores