2020 Fundamentals of Instrumentation Engineering

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Academic unit or major
Undergraduate major in Mechanical Engineering
Instructor(s)
Yoshioka Hayato  Yagi Tohru 
Course component(s)
Lecture
Mode of instruction
ZOOM
Day/Period(Room No.)
Fri5-6(石川台3号館201A号室)  
Group
-
Course number
MEC.I311
Credits
1
Academic year
2020
Offered quarter
1Q
Syllabus updated
2020/9/18
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

In order to understand the basics in the field of measurement engineering, sensors, measurement system configurations, data processing will be taught through hands-on work. Moreover, statistical analysis, reliability of measured data, and sensing machine systems containing various sensors will be offered.

Student learning outcomes

The purpose of this course is to understand various sensing devices, measurement systems, data processing, data analysis, and evaluation of obtained results.

Course taught by instructors with work experience

Applicable How instructors' work experience benefits the course
This course will be offered using some examples in clinical field, since one instructor has experience at a biomedical engineering company.

Keywords

sensor, measurement, signal processing, statistical analysis

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

This course will be offered by lecture in class and combined with PC-based exercise at home. Please install Arduino software and MATLAB prior to the first class. (It takes two hours to install all software in some case.)

Arduino
https://www.arduino.cc/

MATLAB
https://jp.mathworks.com/academia/tah-portal/tokyo-institute-of-technology-1070812.html

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction of various sensors, training using Arduino and CdS cells, systematization technology (A / D conversion, sampling theorem, aliasing) 1) Take pictures of the 3 types of sensors used in your daily life, paste them in Word, etc., add comments about the sensor (sensor name, physical quantity to be detected, etc.), convert it to a PDF file, and upload the file to OCW. 2) Install the Arudino hardware support package of MATLAB, reading the instruction on the following site. https://jp.mathworks.com/matlabcentral/answers/uploaded_files/41209/SupportPackage_InstallGuide_for_Arduino.pdf
Class 2 MATLAB Tutorial https://jp.mathworks.com/learn/tutorials/matlab-onramp.html Take a tutorial on-line course of MATLAB and upload the certificate file to OCW.
Class 3 MATLAB signal processing basic practice (graph display), connecting MATLAB and Arduino and displaying CdS cell output on MATLAB Measure something in your daily life, using sensors (the subject of measurement will be explained in class). Connect the MATLAB and Arduino to display the sensor output on the MATLAB graph. Paste the graph (or screenshot) to Word file, add comments (what you noticed in this measurement experiment, etc.), and upload its PDF file to OCW.
Class 4 Signal processing (ensemble average, moving average), Fourier transform (power, phase, continuous / discontinuous, Gibbs phenomenon, window function), signal processing with MATLAB Using MATLAB, analyze the measurement results obtained in the previous exercise in frequency domain. Paste the time domain graph and the frequency domain graph (power spectrum) into the word, add comments (what you noticed in this measurement experiment, etc.), and upload the PDF file to OCW.
Class 5 Statistical analysis (variance, SD, error function) By using MATLAB, statistical parameters are calculated with a m-file.
Class 6 Reliability (traceability, uncertainty, calibration) By using MATLAB, relationship amoung parameters are calculated with graphs.
Class 7 Measurement system (CMM, roughness gauge, material testing machine) By using MATLAB, analysis exercise with experimental data are carried out.

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

The lecture materials will be uploaded to OCW-i. Please download by the day before the class. May not be available during or immediately before class.

Reference books, course materials, etc.

「計測システム工学の基礎」西原主計,山藤和男,森北出版 (Japanese textbook only)

Assessment criteria and methods

The evaluation is based on reporting assignments.

Related courses

  • MEC.I211 : Robot Kinematics

Prerequisites (i.e., required knowledge, skills, courses, etc.)

This class uses Arduino and photocells, i.e., CdS cells or photoregisters.

If you do not have Arduino, you can purchase at the following shop.

ELEGOO UNO R3 stater kit (1840 yen + delivery fee)
https://www.amazon.co.jp/gp/product/B06ZXXJL2B/ref=ox_sc_act_title_6?smid=A21X7DQBM2LL85&psc=1

In class, we will use the CdS cell (photo register) included in the above kit. If you have an Arduino but don't have a photo register, you can buy it at Akizuki Denshi's online shop, Sengoku Densho's online shop, or Amazon.

CdS cell only (30 yen + delivery fee)
http://akizukidenshi.com/catalog/g/gI-00110/

A part kit including CdS cell, bread board, jumper cables, and others. (2546 yen + delivery fee )
https://www.sengoku.co.jp/mod/sgk_cart/detail.php?code=EEHD-57Z8

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