Liquid Composition Identification and Characteristic Measurement Using Ultrasonic Transmission Technique via Neural Network

Authors

  • Muhammad Naufal Mansor Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Sofi Yahya Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Wan Azani Mustafa Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Habibah Hj Mokhtaruddin Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Syahrul Affandi Saidi Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Ilham Shafini Ahmad Mahyudin Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Mohd Aminudin Jamlos Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, Malaysia
  • Noor Anida Abu Talib Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia
  • Mohd Zamri Hasan Centre of Excellence for Intelligent Robotics & Autonomous Systems (CIRAS), Universiti Malaysia Perlis, Arau, 02600, Perlis, Malaysia

DOI:

https://doi.org/10.37934/araset.31.3.328335

Keywords:

Liquid identification, ultrasonic, Fast Fourier Transform, Neural Network

Abstract

This project is to determine the composition of liquids solvent by using the ultrasonic frequency signal from echoscope scan machine. The transmission technique of ultrasonic signal is focused. On the research experiment, studies on mixing of distilled water with control sodium chloride (Kitchen Salt), kitchen sugar and monosodium glutamate (MSG). The Parameters such as Fast Fourier Transform (FFT) which is the parameters are using to identify the ratio of composition of liquid solvent. The feature extraction of median, average and root mean square (RMS) from FFT is represented with different result analysis such as sensitivity, specificity, accuracy, Area under curve, kappa, F-measure and precision. The results performed more than 90% with Neural Network.

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Author Biographies

Muhammad Naufal Mansor , Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

naufal@unimap.edu.my

Sofi Yahya , Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

sofi@unimap.edu.my

Wan Azani Mustafa, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

wanazani@unimap.edu.my

Habibah Hj Mokhtaruddin, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

habibah@unimap.edu.my

Syahrul Affandi Saidi, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

syahrulaffandi@unimap.edu.my

Ilham Shafini Ahmad Mahyudin, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

ilhamshafini@unimap.edu.my

Mohd Aminudin Jamlos, Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, Malaysia

mohdaminudin@unimap.edu.my

Noor Anida Abu Talib, Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, 02100 Padang Besar, Perlis, Malaysia

anidatalib@unimap.edu.my

Mohd Zamri Hasan, Centre of Excellence for Intelligent Robotics & Autonomous Systems (CIRAS), Universiti Malaysia Perlis, Arau, 02600, Perlis, Malaysia

zamrihasan@unimap.edu.my

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Published

2023-08-18

How to Cite

Muhammad Naufal Mansor, Sofi Yahya, Wan Azani Mustafa, Habibah Hj Mokhtaruddin, Syahrul Affandi Saidi, Ilham Shafini Ahmad Mahyudin, Mohd Aminudin Jamlos, Noor Anida Abu Talib, & Mohd Zamri Hasan. (2023). Liquid Composition Identification and Characteristic Measurement Using Ultrasonic Transmission Technique via Neural Network. Journal of Advanced Research in Applied Sciences and Engineering Technology, 31(3), 328–335. https://doi.org/10.37934/araset.31.3.328335

Issue

Vol. 31 No. 3: August (2023)

Section

Articles
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