# Design of a Modularized IoT Multi-Functional Sensing System and Data Pipeline for Digital Twin-Oriented Real-Time Aircraft Structural Health Monitoring

**Authors:** Shengkai Guo, Andrew West, Jan Papuga, Stephanos Theodossiades, Jingjing Jiang

PMC · DOI: 10.3390/s25216531 · Sensors (Basel, Switzerland) · 2025-10-23

## TL;DR

This paper presents a modular IoT-based system for real-time aircraft structural health monitoring during flights.

## Contribution

A modular IoT system integrating multiple sensors for real-time aircraft structural health monitoring is designed and tested.

## Key findings

- A sampling rate of 1000 Hz is necessary to balance data quality and fatigue life estimation.
- The MMFS system was tested on real aircraft and in laboratory stress/strain experiments.
- The system integrates strain, acceleration, vibration, and temperature sensors for comprehensive monitoring.

## Abstract

A modular, multi-functional (encompassing data acquisition, management, preprocessing, and transmission) sensing (MMFS) system based upon the Internet of Things (IoT) paradigm is discussed in this paper with the goal of continuous real-time, multi-sensor and multi-location monitoring of aircraft (including drones) structural performances during flight. According to industrial and system requirements, a microcontroller and four sensors (strain, acceleration, vibration, and temperature) were selected and integrated into the system. To enable the determination of potential in-flight failures and estimates of the remaining useful service life of the aircraft, resistance strain gauge networks, piezoelectric sensors for capturing structural vibrations and impact, accelerometers, and thermistors have been integrated into the MMFS system. Real flight tests with Evektor’s Cobra VUT100i and SportStar RTC aircraft have been undertaken to demonstrate the features of recorded data and provide requirements for the MMFS functional design. Real flight test data were analysed, indicating that a sampling rate of 1000 Hz is necessary to balance representation of relevant features within the data and potential loss of quality in fatigue life estimation. The design and evaluation of the performance of a prototype (evaluated via representative stress/strain experiments using an Instron Hydraulic 250 kN machine within laboratories) are detailed in this paper.

## Full-text entities

- **Diseases:** fatigue (MESH:D005221)

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12608597/full.md

## References

69 references — full list in the complete paper: https://tomesphere.com/paper/PMC12608597/full.md

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Source: https://tomesphere.com/paper/PMC12608597