Noise Reduction for Improvement of Ultrasonic Monitoring Using Coda Wave Interferometry on a Real Bridge

Journal article

AbstractReinforced concrete bridges are iconic parts of modern infrastructure. They are designed for a minimum service life of 100 years. However, environmental factors and/or inappropriate use might cause overload and accelerate the deterioration of bridges. In extreme cases, bridges could collapse when necessary maintenance lacks. Thus, the permanent monitoring for structure health assessment has been proposed, which is the aim of structural health monitoring (SHM). Studies in laboratories have shown that ultrasonic (US) coda wave interferometry (CWI) using diffuse waves has high sensitivity and reliability to detect subtle changes in concrete structures. The creation of micro-cracks might be recognized at an early stage. Moreover, large-volume structures can be monitored with a relatively small number of US transducers. However, it is still a challenge to implement the CWI method in real SHM practical applications in an outdoor environment because of the complex external factors, such as various noise sources that interfere with the recorded signals. In this paper, monitoring data from a 36-m long bridge girder in Gliwice, Poland, instrumented with embedded US transducers, thermistors, and vibrating wire strain gauges, is presented. Noise estimation and reduction methods are discussed, and the influence of traffic, as well as temperature variation, are studied. As a result, the relative velocity variation of US waves following the temperature change with a very high precision of $$10^{-4} \%$$ 10 - 4 % is shown, and a good bridge health condition is inferred. The influence of lightweight real traffic is negligible. The study verified the feasibility of the implementation of the CWI method on real bridge structures.

Authors: Wang, X; Chakraborty, J; Niederleithinger, E

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: Journal of Nondestructive Evaluation
• Volume: 40
• Issue: 1
• Pages: 14
• Article number: 14
• Publication date: 2021-01-11
• DOI: 10.1007/s10921-020-00743-9
• EISSN: 1573-4862
• ISSN: 0195-9298
• Language: English
• Keywords: Computer science; Physics; Geology; Solid mechanics; Optics; Acoustics; Ultrasonic sensor; Bridge (graph theory); Transducer; Structural health monitoring; Composite material; Noise (video); Strain gauge; Reduction (mathematics); Interferometry; Artificial intelligence; Materials science