Smartphone Application for Structural Health Monitoring of Bridges

Sensors (Basel). 2022 Nov 4;22(21):8483. doi: 10.3390/s22218483.

Abstract

The broad availability and low cost of smartphones have justified their use for structural health monitoring (SHM) of bridges. This paper presents a smartphone application called App4SHM, as a customized SHM process for damage detection. App4SHM interrogates the phone's internal accelerometer to measure accelerations, estimates the natural frequencies, and compares them with a reference data set through a machine learning algorithm properly trained to detect damage in almost real time. The application is tested on data sets from a laboratory beam structure and two twin post-tensioned concrete bridges. The results show that App4SHM retrieves the natural frequencies with reliable precision and performs accurate damage detection, promising to be a low-cost solution for long-term SHM. It can also be used in the context of scheduled bridge inspections or to assess bridges' condition after catastrophic events.

Keywords: damage identification; machine learning; smartphone application; structural dynamics; structural health monitoring.

MeSH terms

  • Algorithms
  • Machine Learning
  • Mobile Applications*
  • Smartphone*