Almallah, N., & Al-Quzwini, M. (2024, June), Introducing Spectral Analysis to Undergraduate Engineering Students  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47681

\bibitem{asee_peer_47681}
  Almallah, N., \& Al-Quzwini, M. (2024, June), \emph{Introducing Spectral Analysis to Undergraduate Engineering Students}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  10.18260/1-2--47681

Najjiya Almallah and Mahmoud Al-Quzwini.  "Introducing Spectral Analysis to Undergraduate Engineering Students".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/47681 Internet.  14 Dec, 2024

\bibitem{asee_peer_47681}
  Najjiya Almallah and Mahmoud Al-Quzwini.
  "Introducing Spectral Analysis to Undergraduate Engineering Students".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/47681 Internet.  14 Dec, 2024

@INPROCEEDINGS{asee_peer_47681
author = "Najjiya Almallah and Mahmoud Al-Quzwini"
title = "Introducing Spectral Analysis to Undergraduate Engineering Students"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/47681}
number = {10.18260/1-2--47681}
}

TY  - CPAPER
AB  - Currently, engineering students are only exposed to the theory of Fourier analysis in one of their math classes. They are not taught the relation between this transform and the frequency spectrum of the time domain data, or how to practically find it and plot its spectrum, nor how to filter the data to remove unwanted noise and disturbance. Since a significant range of engineering applications require analysis of the measured data in the frequency domain, students will need to fill this gap between theory and practice without proper guidance. While MATLAB makes the implementation of these processes simple, only electrical engineering students who have taken a DSP course are able to understand and implement these processes.
This paper presents a module for teaching spectral analysis to sophomore engineering students using an engaging and hands-on approach without the intense level of math found in DSP books. The module was applied in a core engineering course at Steven Institute of Technology taken by 309 students from six different engineering departments. It consisted of three steps: research in which students were asked to report an application or process which uses spectral analysis. This started with a class discussion of the shared demo examples from each engineering discipline. In the second step, the students learned how to use MATLAB to analyze music signals. The authors found music to be an invaluable illustrative tool for spectral analysis. It appeals to a wide range of students and is easy to generate. The analysis included understanding the concepts of the sampling frequency, single and multi-tone signals, as well as finding and plotting the frequency spectrum using the MATLAB FFT command. In the third step, students learned how to use MATLAB to design low pass, high pass, band pass, and band stop filters; then filtered the music signals to remove certain frequency bands. Finally, the students observed the effect of increasing the filter order on its performance.

AU  - Najjiya Almallah
AU  - Mahmoud Al-Quzwini
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Introducing Spectral Analysis to Undergraduate Engineering Students
UR  - https://peer.asee.org/47681
DO  - 10.18260/1-2--47681
ER  -