2021 Engineering Measurement I

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Academic unit or major
Undergraduate major in Transdisciplinary Science and Engineering
Instructor(s)
Yagi Tohru 
Class Format
Lecture     
Media-enhanced courses
Day/Period(Room No.)
Mon7-8(S422)  
Group
-
Course number
TSE.A232
Credits
1
Academic year
2021
Offered quarter
2Q
Syllabus updated
2021/4/26
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

In this course, you learn the basic principles of sensors, systemization techniques (A/D conversion, D/A conversion), and signal processing. The course consists of lectures and practical training to design and build a system to control a servo motor based on sensor data.

Student learning outcomes

To be able to explain the measurement principles of various sensors.
Explain the types of analog and digital signals and noise reduction.
To be able to explain basic signal processing.
This course is designed to help students achieve the following academic goals.
 1) Genera measurement and computation technologies
 2) Ability to design and operate systems.

Course taught by instructors with work experience

Applicable How instructors' work experience benefits the course
In this course, an instructor, who has practical experience at a medical device manufacturer, will use his practical experience to provide education by giving examples of human body measurements.

Keywords

Sensor, measurement, signal processing

Competencies that will be developed

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

Class flow

1) In this course, students are supposed to deepen their understanding through online lectures and practical assignments using sensors and a microcomputer at home.

2) We use OCW-i and Slack. You can find Slack invitation on OCW-i. Immediately after your registration process, please check OCW-i.

3) You will use Arduino and breadboard. Please prepare Arduino software and MATLAB software in advance (note that the installation can take up to 2 hours).

Arduino
https://www.arduino.cc/

MATLAB
https://www.citl.titech.ac.jp/matlab_intro/

If you have any questions about installing MATLAB, please contact MATLAB-TA at the Education Innovation Center.

MATLAB_TA
https://www.citl.titech.ac.jp/matlab_officehour/

The following items will be rented out in the first class. Be sure to attend the first class. If you are absent, be sure to contact the course instructor.

1 Arduino UNO
1 USB cable (Type B for UNO)
1 breadboard
Several male-male jumper lines
Several male-female jumper lines
1 photo cell (CdS cell)
1 LED
1 resistor 220Ω
1 resistor 1KΩ
1 Battery box
1 Photo reflector
Some Header pin
2 Servomotors
2 wheels

Course schedule/Required learning

  Course schedule Required learning
Class 1 face-to-face class Introduction of various sensors Practice using Arduino and CdS cells Parts distribution (RC servo motors, battery boxes, resistors, CdS cells, photo-reflectors, male and female jumper wires, header pins) 1) Take photos of three types of sensors used in daily life, paste them into Word or PowerPoint, etc., add comments about the sensors (name of the sensor, physical quantity to be detected, etc.), convert them into a PDF file, and upload the file to OCW. 2) Install the Arduino hardware support package for MATLAB by referring to the following site: https://jp.mathworks.com/help/supportpkg/arduino/ug/install-support-for-arduino-hardware.html#bvfxo09 or https://jp.mathworks.com/videos/install-the-matlab-and-simulink-support-packages-for-arduino-106497.html
Class 2 Online Class: MATLAB practice https://www.mathworks.com/learn/tutorials/matlab-onramp.html Upload MATLAB Onramp Certificate (PDF) to OCW
Class 3 Online Class Signal processing (ensemble averaging, moving averaging) Basic MATLAB signal processing practice (graph display) Connecting MATLAB and Arduino to display the output of CdS cell on MATLAB Perform an experiment to measure an everyday object using a sensor (the detail will be explained in class). Connect MATLAB and Arduino, and graph the sensor output on MATLAB. Paste the graph (or screenshot) into MS Word, and add comments, such as what you noticed in this experiment. Convert the word file to PDF, and upload the PDF file to OCW.
Class 4 Online Class Signal processing (Fourier transform, power, phase, continuous and discontinuous, Gibbs phenomenon, window function) Signal processing practice using MATLAB Using MATLAB, perform a frequency analysis of the measurement results obtained in the previous assignment. Paste the time domain graph and the frequency domain graph (power spectrum) into a word document, add comments (such as what you noticed in this measurement experiment) Upload the PDF file to OCW.
Class 5 Online Class Systematization technology (A/D converter, sampling theorem, aliasing) Fabrication of a line tracer using a photo-reflector and RC servo motor #1 Make a circuit using photo interrupter on a breadboard to detect a line. You will also build a line tracer that runs along the line by moving RC servo motors based on the sensor values.
Class 6 Online Class Line tracer fabrication using photo interrupters and RC servo motors #2 Line tracer fabrication
Class 7 face-to-face class Line tracer driving test Everyone bring his/her own line tracer and drive it on a predetermined course to compete for time.

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)

There is no textbook. Class materials will be uploaded to OCW-i. (OCW-i will be crowded during or just before class, so please download them in advance.)

Reference books, course materials, etc.

Fundamentals of Measurement System Engineering (in Japanese), Chikei Nishihara and Kazuo Yamafuji, Morikita Publishing Co.
Prototyping Lab 2nd Ed. (in Japanese), S.Kobayashi, O'Reilly Japan.

Assessment criteria and methods

A comprehensive evaluation of the assignments given in the lectures will be conducted.

Related courses

  • TSE.M204 : Statistics and Data Analysis
  • TSE.A203 : Electrical Engineering
  • TSE.M201 : Ordinary Differential Equations and Physical Phenomena
  • TSE.M203 : Theory of Linear System
  • TSE.A202 : Solid Mechanics and Structure Engineering
  • TSE.A205 : Fluid Engineering
  • TSE.A201 : Material and Molecular Engineering
  • TSE.A204 : Engineering Thermodynamics
  • TSE.A351 : Transdisciplinary Engineering Experiment A
  • TSE.A352 : Transdisciplinary Engineering Experiment B

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

1) In this course, students are supposed to deepen their understanding through online lectures and practical assignments using sensors and a microcomputer at home.

2) We use OCW-i and Slack. You can find Slack invitation on OCW-i. Immediately after your registration process, please check OCW-i.

3) You will use Arduino and breadboard. Please prepare Arduino software and MATLAB software in advance (note that the installation can take up to 2 hours).

Arduino
https://www.arduino.cc/

MATLAB
https://www.citl.titech.ac.jp/matlab_intro/

If you have any questions about installing MATLAB, please contact MATLAB-TA at the Education Innovation Center.

MATLAB_TA
https://www.citl.titech.ac.jp/matlab_officehour/

The following items will be rented out in the first class. Be sure to attend the first class. If you are absent, be sure to contact the course instructor.

1 Arduino UNO
1 USB cable (Type B for UNO)
1 breadboard
Several male-male jumper lines
Several male-female jumper lines
1 photo cell (CdS cell)
1 LED
1 resistor 220Ω
1 resistor 1KΩ
1 Battery box
1 Photo reflector
Some Header pin
2 Servomotors
2 wheels

Other

In this course, we use OCW-i and Slack. You can find Slack invitation on OCW-i. Immediately after your registration process, please check OCW-i.

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