Authors:
S. Praveen Kumar, I. Gowtham, T. Anand, S. Suman Rajest, C. Satheesh, Fatma Bassyouni

Addresses:
Department of Aeronautical Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. Department of Research and Development, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Robotics and Automation Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Chemistry of Natural and Microbial Products, National Research Centre, Giza, Cairo Governorate, Egypt.

Abstract:

The research focuses on the design and implementation of an integrated system to support real-time structural health assessment, specifically the Aircraft Vibration and Fatigue Monitoring System (AVFMS). The dataset employed in the study comprises 289 varying data instances recorded across different flight regimes to test the structural integrity. The primary devices employed are MEMS-based accelerators to sense high-fidelity vibrations and an ESP32 microcontroller to process data edges and transmit data wirelessly. The system identifies, at the earliest stages, signs of stress in the form of vibrations before they can develop into disastrous failures. The condition-based maintenance methodology is no longer based solely on traditional scheduled inspections; it is now more dynamic and data-driven. Results indicate that the system can efficiently differentiate between the normal operating harmonics and the abnormal stress forms. This study provides a solid technological foundation for enhancing aviation safety and extending the service life of critical airframes.

Keywords: Structural Health Monitoring; MEMS Accelerometers; ESP32 Microcontroller; Vibration Analysis; Fatigue Prediction; Aircraft Vibration; Fatigue Analysis; Artificial Intelligence.

Received on: 03/09/2024, Revised on: 12/11/2024, Accepted on: 23/01/2025, Published on: 03/06/2026

DOI: 10.69888/FTSES.2026.000676

FMDB Transactions on Sustainable Energy Sequence, 2026 Vol. 4 No. 1, Pages: 22-31

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