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Using Micro-Electro-Mechanical Systems MEMS to Develop Diagnostic Tools

Using Micro-Electro-Mechanical Systems MEMS to Develop Diagnostic Tools

Published on: October 1, 2007

Developing and Testing High-Performance SHM Sensors Mounting Low-Noise MEMS Accelerometers.

Marianna Crognale¹, Cecilia Rinaldi¹, Francesco Potenza²

¹Department of Structural and Geotechnical Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Roma, Italy.

Sensors (Basel, Switzerland)

|April 27, 2024

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Micro-electrical mechanical system (MEMS) accelerometers offer a cost-effective, low-power solution for structural health monitoring (SHM). These sensors accurately detect modal frequencies, enabling continuous structural assessment and damage detection.

Area of Science:

Engineering
Materials Science
Computer Science

Background:

Increasing demand for continuous structural health monitoring (SHM) necessitates advanced sensing technologies.
Micro-electrical mechanical system (MEMS) sensors offer advantages like low cost, ease of installation, and reduced power consumption for SHM applications.

Purpose of the Study:

To present an innovative, high-performance MEMS accelerometer device for SHM.
To provide guidelines and results on the capabilities of MEMS devices for structural vibration monitoring and modal identification.

Main Methods:

Design, development, and calibration of low-noise triaxial MEMS accelerometer sensor nodes.
Implementation of a reliable network protocol for command dissemination and data collection.
Software improvements for data pipelining, jitter control, and high-frequency sampling.

Keywords:

SHM-board internet of things structural health monitoring ultra-low-power micro-controller

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Last Updated: Jun 27, 2025

Using Micro-Electro-Mechanical Systems MEMS to Develop Diagnostic Tools

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Laboratory testing using shaker excitation and a real-world case study deployment.

Main Results:

MEMS accelerometers are a viable, cost-effective alternative to traditional piezo-based sensors.
MEMS deployment significantly minimizes sensor node energy consumption.
Accurate detection of modal frequencies for damage assessment was demonstrated.
The proposed network architecture successfully provided dense and accurate vibration data in a real case study.

Conclusions:

MEMS-based accelerometers are a feasible and promising technology for pervasive structural health monitoring.
The developed system enables continuous structural assessment with reduced energy consumption and cost.
The successful deployment validates the robustness and accuracy of the MEMS sensor network for real-world applications.