Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	366036	Vibration and Noise Control	1	3.0	3	★	MA KUEN WAI	GME IMMA	0	0	機電、外生專班合開，限20人，英文授課

Course Plan：

Instructor	MA KUEN WAI　Office Hours
Email	kwma@ntut.edu.tw
Last Updated	2026-06-03 21:23:10
Course Objective	課程內容涵蓋機械振動與噪音、聲學基礎、聲波傳播、聲音之反射與折射、聲學量測、振動抑制與隔離技術、噪音降低與吸音材料、消音器與噪音控制，以及相關法規與環境議題。 Topics include: Mechanical vibration and noise, Fundamentals of acoustics, Sound wave propagation, Reflection and refraction of sound, Acoustic measurement, The use of vibration isolators and absorbers, Noise reduction and sound-absorbing materials, Silencers and noise control, Noise regulations, and environmental considerations.
Course Schedule	Week Topic 1 Course introduction & vibration and noise control concepts 2 Vibration and noise fundamentals (I) 3 Vibration and noise fundamentals (II) 4 Vibration and noise transmission 5 Vibration and noise assessments 6 Noise and environmental sustainability 7 Noise prediction (I) 8 Mid-term exam 9 Noise prediction (II) 10 Mechanical vibration (I) 11 Mechanical vibration (II) 12 Instrumentation and standards 13 Signal processing & data science 14 Vibration and noise control methods (I) 15 Vibration and noise control methods (I) 16 Final exam 17 Flexible Learning (see Note) 18 Flexible Learning (see Note)
Evaluation and grading policy	Subject Mark = Attendance 20% + Mid-term exam 30% + Final exam 35% + Student group practice and discussion 15% (see Note)
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Mak, C. M., Ma, K. W., and Wong, H. M., “Prediction and control of noise and vibration from ventilation systems.” 1st ed, ISBN 9781032061986. (Taylor & Francis, Oxfordshire, United Kingdom, 2023). Use of self-made materials.
The access to curricular consultation	Email: kwma@ntut.edu.tw; Tel: 02-27712171 #2074
Expanding teaching and resources	● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.
The course corresponds to the SDGs	SDG11：永續城市與社區（Sustainable Cities and Communities）
Does the course incorporate AI	● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
Note	Flexible Learning: 1. Category: Student group practice and discussion 2. Content: Week 17: Each student group conducts practice and discussion on a noise prediction problem and completes the analysis according to the given conditions. Week 18: Each group presents the results of the Week 17 practice, followed by class Q&A and discussion. 3. Hours: Total: 6 hours. 4. Learning outcomes: Students apply the learned methods in noise prediction to case analysis, result organization, and oral presentation. 5. Subject mark: Weeks 17–18 class report and performance: 15%