| Academic Year |
2024Year |
School/Graduate School |
School of Engineering |
| Lecture Code |
K5313010 |
Subject Classification |
Specialized Education |
| Subject Name |
計測工学 |
Subject Name
（Katakana） |
ケイソクコウガク |
Subject Name in
English |
Instrumentation Engineering |
| Instructor |
SHINTAKU EIJI |
Instructor
(Katakana) |
シンタク エイジ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
2nd-Year, Second Semester, 4Term |
| Days, Periods, and Classrooms |
(4T) Mon5-8：ENG 115 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| Lecture with blackborad |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
J
:
Japanese |
| Course Level |
2
:
Undergraduate Low-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
10
:
Integrated Engineering |
| Eligible Students |
2nd-year students of Program of Transportation Systems, Cluster I |
| Keywords |
Unit, least square method, digital measurement, Fourier transform |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Program of Transportation Systems
（Knowledge and Understanding）
・The area of systems: Technical knowledge on systems, information and transportation systems relating to transportation equipment and coexistence with the environment
（Abilities and Skills）
・The area of systems: The ability to apply technical knowledge of systems, information and transportation systems to solve issues relating to the areas of transportation equipment and coexistence with the environment |
|---|
Class Objectives
/Class Outline |
It aims to understand the fundamental of instrumentation technology, and to be able to analyze measured data. |
| Class Schedule |
lesson1 Introduction and unit
lesson2 Uncertainty by measurement and accuracy
lesson3 Indirect measurement
lesson4 Statistical procedure of measuring data (1): Significant number and average
lesson5 Statistical procedure of measuring data (2): Least square method
lesson6 Statistical procedure of measuring data (3): Practice
lesson7 Statistical procedure of measuring data (4): Regression analysis
lesson8 Mid-term examination
lesson9 Basic configuration and signal transformation of instrumentation system
lesson10 Signal processing (1): Fourier series
lesson11 Signal processing (2): Fourier transform
lesson12 Signal processing (3): Practice of Fourier transform
lesson13 Signal processing (4): Analog signal processing and filter
lesson14 Signal processing (5): Digital signal processing
lesson15 Signal processing (6): Processing of time series signal and exercise of signal processing
lesson16 Term-end examination |
Text/Reference
Books,etc. |
Handout is distributed. |
PC or AV used in
Class,etc. |
|
| (More Details) |
Laptop PC |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Enough preparation and review of each class are required because many contents are taught in each class. |
| Requirements |
|
| Grading Method |
The result is evaluated by reports, mid-term and term-end examinations comprehensively: Reports (30%), mid-term (30%), and term-end examination (40%). It passes by 60 points or more in total.
Anyone who has more than six class-long, unexcused absences will receive a "D" grade for the course. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |