Ultrasonic Guided-Waves Sensors and Integrated Structural Health Monitoring Systems for Impact Detection and...

Area of Science:

• Materials Science
• Mechanical Engineering
• Electrical Engineering

Background:

• Structural Health Monitoring (SHM) is crucial for infrastructure safety.
• Impact detection and localization are key challenges in SHM.
• Guided ultrasonic waves offer a promising non-destructive evaluation method.

Purpose of the Study:

• To review the state-of-the-art in sensors for guided ultrasonic waves used in SHM.
• To analyze recent developments in sensor technologies, electronics, and data processing.
• To explore the potential of AI and deep learning for autonomous impact analysis.

Main Methods:

• Comprehensive literature review of sensor technologies for guided ultrasonic waves.
• Analysis of physical phenomena related to impact events and their measurement.
• Discussion of front-end electronics, wired/wireless data transmission, and signal processing techniques.
• Investigation of sensor integration, autonomous nodes, energy harvesting, and embedded processing.

Main Results:

• Detailed comparison of various ultrasonic sensor technologies, highlighting their advantages and disadvantages.
• Assessment of different data transmission and signal processing approaches for SHM.
• Exploration of advancements in sensor networking and autonomous node capabilities.
• Identification of emerging deep learning and AI techniques for impact detection and characterization.

Conclusions:

• Guided ultrasonic wave sensors are vital for effective impact detection in SHM.
• Advancements in sensor technology, data processing, and AI are enhancing SHM capabilities.
• Future SHM systems will likely feature integrated, autonomous sensor networks powered by AI.