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School of Environment and Society
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- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Mechanical Engineering
- Instructor(s)
- Okuma Masaaki
- Class Format
- Lecture / Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Mon1-2(I123)
- Group
- -
- Course number
- MEC.B333
- Credits
- 1
- Academic year
- 2018
- Offered quarter
- 2Q
- Syllabus updated
- 2018/4/9
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
Spectral analysis plays a basic and important technique to analyze the data of dynamic phenomena such as vibration. This course aims to lecture the fundamental theories and knowledges of the specialized technique with exercise using some case-studies in structural dynamics.
An emphasized aim is to lecture for students to gain deep understanding of the theory of Fourier Transformation from the viewpoints of both physics and mathematics and to be able to use the theory for analyzing various actual data.
Student learning outcomes
At the end of this course, students will be able to :
1) understand fundamental theories of dynamics for spectral analysis
2) understand the methods from data acquisition to spectral analysis concretely for practical use
Keywords
Dynamic Phenomena, Spectrum, Random Vibration, Correlation
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
Lecturing and exercise using PC to concretely understand the lectured theories and practical usage.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Brief introduction of the history of spectral analysis, and basics of random vibration and spectrum | Realize the research history of spectral analysis, and enhance academic interest in it |
| Class 2 | Relationship of autocorrelation and spectrum | Understand autocorrelation and spectrum. |
| Class 3 | Relationship of crosscorrelation, crossspectrum and transfer function | Understand relationship of crosscorrelation, crossspectrum and transfer function |
| Class 4 | Stationary and ergodic | Understand "stationary" and "ergodic" conditions. |
| Class 5 | Data acquisition and treatment | Understand basic and standard methods of data acquisition and treatment. |
| Class 6 | Programing | Make programming codes to realize the theories. |
| Class 7 | Exercise | Understand the theories by computer programming and execution using sample data. |
| Class 8 | Applications of spectral analysis in mechanical engineering | Think the applicability of the analysis. |
Textbook(s)
Several materials are provided by lecturer.
Reference books, course materials, etc.
Spectral analysis, written by Mikio Hino, Asakura.
Assessment criteria and methods
Students' course scores are determined based on final examination (about 70%) and exercises (about 30%).
Related courses
- MEC.D201 ： Mechanical Vibrations
- MEC.D311 ： Vibration Analysis
- MEC.D531 ： Experimental Modal Analysis for Structural Dynamics
- MEC.D431 ： Advanced Sound and Vibration Measurement
- CVE.A210 ： Structural Dynamics in Civil Engineering
- MEC.D431 ： Advanced Sound and Vibration Measurement
- SCE.I432 ： Acoustic measurement engineering
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Bring a note-PC in which Matlab and/or some programing software is available.
Other
Each student is required to attend with his/her note-PC in which Matlab software has been installed.
