2025, Vol. 6, Issue 2, Part B
Integrating wireless sensors and artificial intelligence for vibration fault detection
Author(s): Ansam R Raheem, Abbas Swayeh Atiyah, Hayder Aqeel Mohammed and Nada Tarik Abdul Jabar
Abstract: Operating a steam turbine (ST) while experiencing infrequent vibration faults is challenging. A revolutionary intelligent approach utilizing wireless sensors and artificial intelligence (AI) was designed in this work to accurately identify such defects in real time, safeguarding STs from catastrophic failure. The system is comprised of a three-level process: The first level covers communication, collecting and sending data to the main computer, the second level focuses on signal processing the data to minimize the noise and transferring data to the frequency domain, while at the third level, the data is processed, and the vibration fault identified via a neural network. The first level is designed within sensors, while levels two and three were constructed in a main computer using MATLAB. This system enhances real-time fault detection and classification using wireless technology with AI, and as a result, vibration fault is processed, identified, and neutralized before reaching the danger zone, minimizing damage to the ST to be on the safe side during operations.
DOI: 10.22271/27083969.2025.v6.i2b.83
Pages: 95-101 | Views: 130 | Downloads: 63
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How to cite this article:
Ansam R Raheem, Abbas Swayeh Atiyah, Hayder Aqeel Mohammed, Nada Tarik Abdul Jabar. Integrating wireless sensors and artificial intelligence for vibration fault detection. Int J Electr Data Commun 2025;6(2):95-101. DOI: 10.22271/27083969.2025.v6.i2b.83
