Combining Passive and Active Ultrasonic Stress Wave Monitoring Techniques: Opportunities for Condition Evaluation of Concrete Structures

Concrete structures are invaluable assets to a society and managing them efficiently and effectively can be supported by information gathered through structural health monitoring (SHM). In this paper, a combined approach based on passive, i.e., acoustic emission (AE), and active, i.e., ultrasonic stress wave (USW) monitoring techniques for application to concrete structures is proposed and evaluated. While AE and USW are based on the same underlying physics, i.e., wave motion in solids, they differ fundamentally with respect to the nature of the source. For the former, external stimuli such as mechanical loads or temperature cause the rapid release of energy from initially unknown locations. As a result, AE events are unique and cannot be repeated. For the latter, a known source at a known location is employed at a specified time. This approach is thus controlled and repeatable. It is argued that a combination of these two techniques has the potential to provide a more comprehensive picture of ongoing fracture processes, damage progression, as well as slowly occurring aging and degradation mechanisms. This combined approach does thus promise new opportunities to support condition assessment of concrete structures. After providing an overview and comparison of the two techniques, results, and observations from a full-scale laboratory experiment and an in-service bridge monitoring study are discussed to demonstrate the promise of the proposed combined monitoring approach. Finally, suggestions for further work are presented

Combined Passive and Active Ultrasonic Stress Wave Monitoring of Concrete Structures: An Overview of Data Analysis Techniques and Their Applications and Limitations

Combined passive ultrasonic (US) stress wave [better known as acoustic emission (AE)] and active US stress wave monitoring has been shown to provide a more holistic picture of ongoing fracture processes, damage progression, as well as slowly occurring aging and degradation mechanisms in concrete structures. Traditionally, different data analysis techniques have been used to analyze the data generated from these two monitoring techniques. For passive US stress wave monitoring, waveform amplitudes, hit rates, source localization, and b-value analysis, among others, have been used to detect and locate cracking. On the other hand, amplitude tracking, magnitude squared coherence (MSC), and coda wave interferometry (CWI) are examples of analyses that have been employed for active US stress wave monitoring. In this paper, we explore some of these data analysis techniques and show where their respective applications and limitations might be. After providing an overview of the monitoring approach and the different data analysis techniques, results and observations from selected laboratory experiments are discussed. Finally, suggestions for further work are proposed

Early Detection of Structural Damage in UHPFRC Structures through the Combination of Acoustic Emission and ultrasonic stress wave monitoring

Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC) offers several advantages compared to concrete, notably due to the strain hardening behavior under tensile actions. Structures made of this composite material are lightweight and highly durable, thanks to the UHPFRC waterproofing quality. Nonetheless, the tensile behavior leads to a different cracking pattern than conventional concrete and is not fully understood yet. This paper presents a combined approach using both passive ultrasonic (US) stress wave (or acoustic emission) and active US stress wave monitoring to localize and quantify damage progression in a full-scale UHPFRC beam during experimental load testing. The proposed monitoring approach involves 24 US transducers that are embedded randomly throughout a 4.2meter-long laboratory UHPFRC T-beam. Continuous monitoring enabled accurate localization of US stress sources caused by loading-induced cracking as well as from pulses generated by the embedded US transducers. This study shows that it is possible to predict the location and shape of the macro-crack that is linked to structural failure early on, i.e., just after the end of the elastic domain. This combined approach opens new possibilities to monitor the structural behavior and detect damage on UHPFRC structures before they affect the structural behavior in terms of deflection and strain

Methodologies and Applications Review

Funding Information: The Authors acknowledge Fundação para a Ciência e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI). Pedro M. Ferreira also acknowledges FCT-MCTES for funding the PhD grant UI/BD/151055/2021. Publisher Copyright: © 2022 by the authors.Sensing Technology (ST) plays a key role in Structural Health-Monitoring (SHM) systems. ST focuses on developing sensors, sensory systems, or smart materials that monitor a wide variety of materials’ properties aiming to create smart structures and smart materials, using Embedded Sensors (ESs), and enabling continuous and permanent measurements of their structural integrity. The integration of ESs is limited to the processing technology used to embed the sensor due to its high-temperature sensitivity and the possibility of damage during its insertion into the structure. In addition, the technological process selection is dependent on the base material’s composition, which comprises either metallic or composite parts. The selection of smart sensors or the technology underlying them is fundamental to the monitoring mode. This paper presents a critical review of the fundaments and applications of sensing technologies for SHM systems employing ESs, focusing on their actual developments and innovation, as well as analysing the challenges that these technologies present, in order to build a path that allows for a connected world through distributed measurement systems.publishersversionpublishe

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Damage detection and healing performance monitoring using embedded piezoelectric transducers in large-scale concrete structures

Concrete keeps being the leading structural material due to its low production cost and its great structural design flexibility. However, concrete is prone to various ambient and operational loads which are responsible for crack initiation and extension, leading to decrease of its anticipated operational service life. The current study is focusing on the use of ultrasonic wave propagation techniques based on low-cost and aggregate-size embedded piezoelectric transducers for the online monitoring of the damage state and the healing performance in concrete structures with an autonomous healing system in the form of encapsulated polyurethane-based healing agent embedded in the matrix of concrete. The crack formation triggers the autonomous healing mechanism which promises material recovery and extension of the operational service life. The proposed technique is applied on large-scale, steel reinforced, concrete beams (150mm × 250 mm × 3000 mm), subjected to four-point bending. After the capsules are broken and the healing agent is released, which results in filling of the crack void, and polymerized, the concrete beams are reloaded. The results demonstrate the ability of the monitoring system to detect the initiation and propagation of the cracking as well as to assess the performance of the self-healing system

Monitoring early-age acoustic emission of cement paste and fly ash paste

In this study, a combined approach of several monitoring techniques was applied to allow correlations between the AE activity and related processes such as shrinkage and settlement evolution, capillary pressure and temperature development in fresh cementitious media. AE parameters related to frequency, energy, and cumulative activity which exhibit sensitivity to the particle size distribution of cement paste are compared with inert fly ash (FA) leading to isolation of the mechanical sources from the chemical ones. Characterization of the origin of different processes occurring in cement paste during hydration is complex. Although acoustic emission (AE) monitoring has been used before, a qualitative relation between the microstructural formation or other early-age processes and the number or parameters of AE signals has not been established. The high sensitivity of AE enables the recording of elastic waves within the cementitious material, allowing the detection of even low-intensity activities

Structural Health Monitoring with Piezoelectric Wafer Active Sensors--Predictive Modeling and Simulation

This paper starts a review of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with highlighting the limitations of the current approaches which are predominantly experimental. Subsequently, the paper examines the needs for developing a predictive modeling methodology that would allow to perform extensive parameter studies to determine the sensing method’s sensitivity to damage and insensitivity to confounding factors such as environmental changes, vibrations, and structural manufacturing variability. The thesis is made that such a predictive methodology should be multi-scale and multi-domain, thus encompassing the modeling of structure, sensors, electronics, and power management. A few examples of preliminary work on such a structural sensing predictive methodology are given. The paper ends with conclusions and suggestions for further wor

Structural Health Monitoring with Piezoelectric Wafer Active Sensors—Predictive Modeling and Simulation

This paper starts a review of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with highlighting the limitations of the current approaches which are predominantly experimental. Subsequently, the paper examines the needs for developing a predictive modeling methodology that would allow to perform extensive parameter studies to determine the sensing method’s sensitivity to damage and insensitivity to confounding factors such as environmental changes, vibrations, and structural manufacturing variability. The thesis is made that such a predictive methodology should be multi-scale and multi-domain, thus encompassing the modeling of structure, sensors, electronics, and power management. A few examples of preliminary work on such a structural sensing predictive methodology are given. The paper ends with conclusions and suggestions for further work

Detection of structural changes in concrete using embedded ultrasonic sensors based on autoregressive model

International audienceEmbedded ultrasonic transmission measurements can be a cost effective and more user-friendly alternative in comparison to commonly used structural health monitoring systems used in civil engineering to detect operational or environmental changes in structure. They can be used to detect small structural changes in large concrete structures without necessity of placing a sensor on the spot where the changing is taking place. This paper presents the investigations on the possibility of utilising autoregressive model, where the velocity of ultrasonic wave in a medium is dependent on the operational state. The goal is to use the model for localization of operational changes in the large concrete structure by means of embedded ultrasonic transducer networks. In this study, several static load tests and dynamic test on large reinforced concrete beams have been performed using embedded ultrasonic sensors. Using the autoregressive model it is possible to localize operational changes in the concrete structure. The proposed approach of diagnostic signal processing allows for precise evaluation of structural changes in concrete