Predictive Maintenance and Damage Mitigation in Bridge Structures using Integrated Acoustic Emission and Digital Image Correlation Techniques
Bilal Hussain *
Ohio University, United States.
Samson Oluyomi Akintola
Ohio University, United States.
*Author to whom correspondence should be addressed.
Abstract
Aim: To examine the predictive maintenance and damage mitigation in bridge structures using integrated acoustic emission and digital image correlation techniques.
Problem Statement: Bridges are essential infrastructural facilities in any society. However, cases of loss of lives coupled with massive financial losses have been reported resulting from bridge failures. The acts of using bridge structures beyond their life expectancy and original design loads have been prevailing.
Significance of Study: Dependable techniques are needed to monitor bridges and ensure their efficiency and safety because they are essential part of society’s infrastructure. Numerous non-destructive methods are present for local structural health monitoring whose mechanisms of operation are based on the principle of electromagnetic waves, mechanical waves and fiber optics. However, the advantages of acoustic emission and digital image correlation techniques have been found promising over other methods.
Methodology: Recent relevant published articles in the area of predictive maintenance and damage mitigation in bridge structures using integrated acoustic emission and digital image correlation techniques were consulted.
Discussion: In this critical review, predictive maintenance and damage mitigation in bridge structures using integrated acoustic emission and digital image correlation were discussed. Digital image correlation is a sensing technique having a full field, non-contact, optical measuring technique that utilizes digital cameras to evaluate the displacement, surface geometry and strain. Concrete and steel, being the most commonly utilized materials for building, were referenced and considered under integrated acoustic emission technique. The basic principle of DIC image tracking involves its coding with a matrix of natural numbers (such as using 0 to represent white areas and 100 to stand for black). The use of a suitable algorithm via specialized software is subsequently encouraged in order to identify the region with a matching distribution of pixel shades. In short, this review has presented the research gaps that should be bridged in the future studies.
Conclusion: In conclusion, integrated acoustic emission and digital image correlation are effective techniques for predictive maintenance and damage mitigation in bridge structures.
Keywords: Predictive maintenance, integrated acoustic emission, digital image correlation, damage mitigation, bridge structures