GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
SENSORS, SIGNAL OPTIMISATION AND DATA COLLECTION/OM333
Course Title: SENSORS, SIGNAL OPTIMISATION AND DATA COLLECTION
Credits 2 ECTS 3
Semester 5 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Assist. Prof. Dr. Fatih ŞAHİN
 -- WEB SITE(S) OF LECTURER(S)
  websitem.gazi.edu.tr/site/fasahin
 -- EMAIL(S) OF LECTURER(S)
  fasahin@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
After the completing the course, student should:
Have a good knowledge about sensor structures and be able to select suitable sensor for a given system,
Have a good knowledge about signal conditioning for sensor signals,
Have knowledge about signal converter circuits
Have knowledge about the structures of data acquisition cards, sampling rate and sampling methods.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  Sensor terminology, Classification of sensors, Static and dynamic characteristics of measurement systems, Sensor characteristics
2. Week  Resistive sensors (Potentiometers, Strain gages, RTDs, Thermistors)
3. Week  Resistive sensors (Magnetoresistors, LDRs, Resistive hygrometers, Resistive gas sensors, Liquid conductivity sensors)
4. Week  Signal conditioning for resistive sensors
5. Week  Reactance variation sensors (Inductive sensors)
6. Week  Reactance variation sensors (Capacitive sensors), Electromagnetic sensors
7. Week  Signal conditioning for reactance variation and electromagnetic sensors
8. Week  Midterm exam
9. Week  Self-generating sensors (Thermoelectric sensors, Piezoelectric sensors, Pyroelectric sensors)
10. Week  Self-generating sensors (Photovoltaic sensors, Electrochemical sensors)
11. Week  Signal conditioning for self-generating sensors
12. Week  Digital sensors, Smart sensors
13. Week  Signal conversion and transmission circuits, noise and interference
14. Week  Signal conversion and transmission circuits, noise and interference
15. Week  Structures of data acquisition cards, Input signal connections
16. Week  Sampling rate and Nyquist theorem, Sampling methods
 -- RECOMMENDED OR REQUIRED READING
  1.Pallas-Areny, R., Webster, J.G., Sensors and Signal Conditioning Second Edition, John Wiley & Sons Inc., New York, 2000. 2.Gürdal, O., Algılayıcılar ve Dönüştürücüler, Nobel Yayın Dağıtım, Ankara, 2000. 3.Park, J., Mackay, S., Practical Data Acquisition for Instrumentation and Control Systems, Elsevier, New York, 2003.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer
 -- WORK PLACEMENT(S)
  Not Applicable
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
20
 Assignment
1
30
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
50
 Contribution of Final Examination to Overall Grade  
50
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
2
28
 Practising Hours of Course Per Week
0
 Reading
0
 Searching in Internet and Library
14
2
28
 Designing and Applying Materials
0
 Preparing Reports
10
1
10
 Preparing Presentation
4
1
4
 Presentation
0
 Mid-Term and Studying for Mid-Term
1
2
2
 Final and Studying for Final
1
3
3
 Other
0
 TOTAL WORKLOAD: 
75
 TOTAL WORKLOAD / 25: 
3
 ECTS: 
3
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Capability of obtaining adequate knowledge in mathematics, science and engineering subjects in the automotive field; applying theoretical and practical knowledge for modeling and solving engineering problems in this field.X
2Capability of formulation and solving engineering problems; for this purpose selecting and appliying the appropriate analysis and modeling methods.X
3Capability of evaluation of engine and vehicle design projects, designing any engine and vehicle parts, to bring prototype and series production stage.X
4Capability of design of complex systems for specific needs, component or process in whole or in part.X
5Capability of development of modern methods and tools necessary for engineering applications, selection and effective use and to use of information technologies effectively.X
6Capability of analysis of the engineering problems and for the solution designing and performing experiments, collecting data, analyzing and interpretting the results.X
7Capability of work in team and individual and ability to work effectively with other disciplines.X
8Capability of effective communication both verbal and written in Turkish and at least one foreign language konwledge
9Capability of access to information in the framework of lifelong learning, to follow the developments in science and technology and self-improvement.X
10Resposibility of professional and ethical liability.
11Awareness of leadership, entrepreneurship, innovation and sustainable development in business life.X
12Being competent in the engineering applications, legislations, legal consequences and in the field of occupational health and safety.X
13Capability of research and application in the subjects of noise, environment and emissions.X
14Capability of making education in the field.X