# Ultrasonic Guided-Waves Sensors and Integrated Structural Health Monitoring Systems for Impact Detection and Localization: A Review

## TL;DR

This paper reviews ultrasonic sensors and systems for detecting and locating impacts in structures, covering sensor technologies, signal processing, and AI applications.

## Contribution

The paper provides a comprehensive review of recent advances in ultrasonic sensor technologies and integration for structural health monitoring.

## Key findings

- Various ultrasonic sensor technologies are analyzed for their advantages and disadvantages in impact detection.
- Integration of autonomous sensor networks with energy harvesting and embedded processing is explored.
- Deep learning and AI are highlighted as emerging tools for impact detection and characterization.

## Abstract

This review article is focused on the analysis of the state of the art of sensors for guided ultrasonic waves for the detection and localization of impacts for structural health monitoring (SHM). The recent developments in sensor technologies are then reported and discussed through the many references in recent scientific literature. The physical phenomena that are related to impact event and the related main physical quantities are then introduced to discuss their importance in the development of the hardware and software components for SHM systems. An important aspect of the article is the description of the different ultrasonic sensor technologies that are currently present in the literature and what advantages and disadvantages they could bring in relation to the various phenomena investigated. In this context, the analysis of the front-end electronics is deepened, the type of data transmission both in terms of wired and wireless technology and of online and offline signal processing. The integration aspects of sensors for the creation of networks with autonomous nodes with the possibility of powering through energy harvesting devices and the embedded processing capacity is also studied. Finally, the emerging sector of processing techniques using deep learning and artificial intelligence concludes the review by indicating the potential for the detection and autonomous characterization of the impacts.