Employing vision transformers for crack detection and health monitoring of concrete structures

Acoustic emission (AE) is a nondestructive evaluation technique that is capable of monitoring the damage evolution of concrete structures in real time. Conventionally, AE sensors are surface mounted on the host structures, however, the AE signals attenuate quickly due to the high attenuation properties of concrete structures. This study conducts a feasibility study of using smart aggregates (SAs), which are a type of embedded piezoceramic transducers, as embedded AE sensors for the health monitoring of concrete structures. A plain concrete beam with two surface mounted AE sensors and two embedded SAs was fabricated in laboratory and loaded under a designed three-point-bending test. The performance of embedded SAs were compared with the traditional surface mounted AE sensors in their ability to detect and evaluate the damage to the concrete structure. The results verified the feasibility of using smart aggregates as embedded AE sensors for monitoring structural damage in concrete. Potentially, the low cost smart aggregates could function as embedded AE sensors, providing great sensitivity and high reliability in applications for the structural health monitoring of concrete structures.

Structural health monitoring (SHM) comes with the real data that is collected and calculated from the structures, which is not possible by mere visual inspection. The working principle of SHM is basically collecting essential data, including strain, temperature conditions, moisture content, etc., which are further transformed into digital data for the interpretation. It serves a tool in the synchronizing of the collected data, also with the responsibility of making it available at all times. It stores the data for the meticulous research and analysis. SHM is enabled with the leading-edge technology of big data, which has an added advantage of collecting and storing extensive data related to the structures. Different types of sensors are used for collecting the data; hence, with these data, real-time information about the structures is extracted. The elaborate process involves the big data, for exploring and analyzing a variety of datasets with different patterns to determine damages, and defects lying under the structures. Hence, health monitoring of the existing structures is possible and with high precision and information. SHM is a continuous process of measurement, collection, processing, and storage of massive amounts of data of the existing structures for diagnosing structural health. Hence, in this paper, various examples of the contemporary structural monitoring system and the ongoing efforts being made in the big data-based structural health monitoring of concrete structures has been presented. The work is dedicated to present the different monitoring sensors of structures to evaluate damage, defects, and serviceability by taking account of available literature.

A new method combining an embedded smart aggregate and surface mounted piezoceramic patches is introduced for health monitoring of concrete structures. The smart aggregate is embedded in a concrete beam as an actuator (or transmitter), and piezoceramic patches are attached on the surface of the concrete beam as sensors. Two tests using the smart aggregate and the piezoceramic patches are conducted. The first test investigates the sensitivity of the recorded signal amplitude-frequency relation on the piezoceramic patches. To explain the significant amplitude fluctuations in the results, the possibility of resonance occurring in the piezoceramic patches in a certain frequency range is verified through finite element modeling. In the second test, a damage index is proposed to evaluate the health of concrete structures and a three-point bending test is conducted to induce damage in the concrete beam. It is observed that, with increasing severity of damage in the concrete beam, the recorded signal amplitude at the patches decreases gradually while the value of the damage index increases significantly. The experimental results show that the proposed method is an effective tool for health monitoring of concrete structures.

Abstract. Smart materials with sensors can monitor the structure's performance under external loading circumstances. They may also monitor internal deformations or damages caused by environmental factors such as temperature, humidity, etc. As a result, the sensors are linked to structural health monitoring to create automated systems for structural monitoring, inspection, and damage identification. The formulation of this review article was prompted by a growing interest in structural health monitoring and the need to ensure structure safety to detect problems early and avert collapse. The structure, measurement methods, and potential of sensors such as fiber optic, piezoelectric, corrosion, ceramic, and self-sensing cement composite utilized in the health monitoring of concrete structures are discussed in this review paper. This review also includes a brief and comparative analysis of various sensors, as well as the optimal number and location of sensors. The study exposed that choosing a suitable sensor is critical for accurate sensing and long-term structure monitoring. The sensor can detect physical (stress, strain) and chemical (corrosion) variables that affect the structure's endurance. Despite significant advances in damage monitoring approaches utilizing sensors, the study suggests that efficient sensor deployment remains problematic. The review revealed that the type of parameter to be monitored (stress, strain, humidity, etc.) and the structural and climatic conditions in which the sensor will be used determine the sensor's selection. As a result, a self-sensing cement composite based on carbon nanofiber (CNF) has been developed, which has good durability and compatibility with concrete structures. However, increasing the amount of CNF lowers the composite's compressive and flexural strength due to particle agglomeration. As a result, the review covers several sensors used in structural health monitoring with their measurements, applications, benefits, and limitations.

Health monitoring of concrete structures strengthened with advanced composite materials using piezoelectric transducers

The application of piezoelectric transducers in in situ health monitoring of concrete structures has been widely investigated. However, previous experimental studies were normally performed in an isothermal room environment, which offers insufficient considerations for temperature variations that real engineering structures experience in practical monitoring cases. In this article, the temperature effects on smart aggregate–based monitoring results are treated by performing active structural health monitoring on two plain concrete specimens at various temperatures. Experimental results show that the amplitude of the monitoring signal increases with temperature, with low-frequency signals being more sensitive to temperature variation while high-frequency signals less temperature dependent. This research demonstrates the necessity of temperature compensation in smart aggregate–based monitoring techniques.

Crack detection is an important issue in the health monitoring and performance evaluation of concrete structures. Based on the heat transfer theory, a temperature tracer method and a monitoring system for crack detection in underwater concrete structures are presented in this paper. The system is composed of an integrated sensing and heating system, a monitoring tube, and multiple casing tubes. The inner diameter of the casing tube should be larger than the outer diameter of the monitoring tube so that there is a certain gap between the casing tube and the monitoring tube to form a cavity. Water fills the cavity along the crack face when the underwater concrete structure cracks, resulting in a change in the surrounding medium at the cracked site. Thus, the cooling rate of the heat source in the monitoring tube corresponding to the cracked site will be accelerated. Crack identification can be done based on a comparative analysis of the cooling curves of the heat source in the uncracked and cracked states. The effects of cavity geometry size and intensity of heat source on crack identification are studied using numerical simulations and crack detection tests. Both simulations and test results confirm the feasibility of the proposed crack detection method.

Carbon fibre incorporated smart cement-based composite has great potential for the multifunctional health monitoring of concrete structures. This paper presents the microstructural, electrical, and mechanical properties of smart cement-based composites incorporating chopped carbon fibres from low dosages at 0–0.1% by volume (vol%) with detailed intervals, to high dosages up to 2.4 vol%. In comparison to a plain mortar, smart cement-based composites at all fibre contents had higher flexural strength. A 95% improvement in flexural strength was obtained at a fibre content of 0.3 vol%, whereas compressive strength increased up to a fibre content of 1.0 vol%, with the highest improvement, 105%, at 0.2 vol%. The bulk conductivity of smart cement-based composites underwent a double percolation process where the percolation zone of the fibres was identified at fibre contents of 0–0.1 vol% and the percolation zone of the capillary pores resided at fibre contents of 2.1–2.4 vol% indicating an extremely low durability. This study presents the laboratory characterization on smart cement-based composites where the fundamentals of the transitional behaviours of the mechanical properties and the percolation in electrical property through fibre loading were studied, which is a necessary step prior to the assessment of the self-sensing performance. The impact of this study will enable the physical properties of carbon fibre incorporated smart cement-based composites to be optimized through the design and manufacturing process. This will lead to robust performance and superior in-situ multi-functional health monitoring of concrete structures.

This paper presents an easy method of embedding piezoceramic transducer (PZT) and its implementation in electromechanical (EM) impedance based health monitoring of concrete structures. The basic principle used in this monitoring is to record EM admittance signatures acquired from the actuations of PZT transducer in the presence of electric field. Any deviations in these signatures during the monitoring period indicate disturbance/ damage in the structure. The PZT can be either surface bonded or embedded, however the important features of embedding PZT inside the host structure are durability and protection from surface finish, vandalism and environment attacks. The embedment of PZT in the structure is not as simple as surface bonding because there are several issues such as bonding between PZT and host structure. Moreover, it should withstand the curing pressures and temperatures of the host material. This paper is also expected to be useful for monitoring embeddable composite structures.

Structural health monitoring (SHM) of civil engineering structures has been widely developed to increase safety and to provide cost-effective maintenance programmes. Although the current approaches of SHM systems using traditional single-point sensors – such as electric strain sensors, accelerometers and global positioning system-based sensors – have appropriate measurement precision for SHM purposes, they present challenges when deployed in real-scale applications, given the limited number of possible points to assess structural behaviour and the harsh environmental conditions during operation. When it comes to reinforced-concrete structures, the development of health monitoring and damage identification presents further challenges, since this type of structure is affected by a variety of chemical, physical and mechanical degradation processes, has a heterogeneous composition and shows non-linear behaviour. On the other hand, fibre optic (FO) technology can provide integrated sensing along with extensive measurement lengths of high sensitivity, durability and stability, which makes it ideal for the SHM of concrete structures. In this paper, FO sensing principles and the different types of FO sensors for civil structure applications are briefly described and a state-of-the-art review of SHM applied to concrete structures using FO sensors in recent decades is presented.

An improved concrete structure health monitoring method based on G-S-G is proposed, which fully combines an optimized Gray-Level Co-occurrence Matrix (GLCM) with an improved Self-Organizing Map (SOM) neural network to achieve accurate and real-time concrete structure health monitoring. First of all, in order to obtain a dynamic image of the crack damage region of interest (ROI) with clear contrast and obvious target, the image acquisition system and image optimization method are used to process the damaged image. Moreover, in order to realize the accurate location of crack damage, crack damage identification research based on GLCM-SOM effectively eliminates the interference of honeycomb and pothole damage on crack damage. In order to obtain the indicators for monitoring the health status of the structure, the damage characteristics and probability distribution characteristics of the concrete structure in the gray level co-occurrence matrix are combined to extract the probability range index (PRI). On the basis of extracting the crack damage index, in order to verify the reliability of the sensitive feature index, starting from the two dimensions of damage texture feature and data expansion, through reverse research of the damage model, the damage index of accurately locating the crack damage was selected. It follows that the final sensitive indicators: entropy (ENT) and PRI can be used for structural health monitoring because of their strong damage characterization ability and sensitivity to damage characteristics. This research shows that is helpful to realize the high precision intelligent concrete structure health monitoring of modern concrete structure crack damage.

Recently developed piezoceramic-based transducers, known as smart aggregates (SAs), have shown their applicability and versatility in various applications of structural health monitoring (SHM). The lead zirconate titanate (PZT) patches embedded inside SAs have different modes that are more suitable for generating or receiving different types of stress waves (e.g. P and S waves, each of which has a unique role in SHM). However, due to the geometry of the 2D PZT patch, the embedded SA can only generate or receive the stress wave in a single direction and thus greatly limits its applications. This paper is the first of a series of two companion papers that introduces the authors’ latest work in developing a novel, embeddable spherical smart aggregate (SSA) for the health monitoring of concrete structures. In addition to the 1D guided wave produced by SA, the SSA embedded in concrete structures can generate or receive omni-directional stress waves that can significantly improve the detection aperture and provide additional functionalities in SHM. In the first paper (Part I), the detailed fabrication procedures with the help of 3D printing technology and electrical characterization of the proposed SSA is presented. The natural frequencies of the SSA were experimentally obtained and further compared with the numerical results. In addition, the influence of the components’ thickness (spherical piezoceramic shell and epoxy) and outer radius (spherical piezoceramic shell and protection concrete) on the natural frequencies of the SSA were analytically studied. The results will help elucidate the key parameters that determine the natural frequencies of the SSA. The natural frequencies of the SSA can thus be designed for suitability in the damage detection of concrete structures. In the second paper (Part II), further numerical and experimental verifications on the performance of the proposed SSA in concrete structures will be discussed.

The existing fleet of nuclear power plants in the United States have initial operating licenses of 40 years, and many of these plants have applied for and received license extensions. As plant structures, systems, and components age, their useful life—considering both structural integrity and performance—is reduced as a result of deterioration of the materials. Assessment and management of aging concrete structures in nuclear plants require a more systematic approach than simple reliance on existing code-based design margins of safety. Structural health monitoring is required to produce actionable information regarding structural integrity that supports operational and maintenance decisions. The online monitoring of concrete structures project conducted under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability program at Idaho National Laboratory is seeking to develop and demonstrate capabilities for concrete structures health monitoring. Through this research project, several national laboratories and Vanderbilt University propose to develop a framework of research activities for the health monitoring of nuclear power plant concrete structures that includes the integration of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report briefly discusses activities in this project during October-December, 2014. The most significant activity during this period was the organizing of a two-day workshop on research needs in online monitoring of concrete structures, hosted by Vanderbilt University in November 2014. Thirty invitees from academia, industry and government participated in the workshop. The presentations and discussions at the workshop surveyed current activities related to concrete structures deterioration modeling and monitoring, and identified the challenges, knowledge gaps, and opportunities for advancing the state of the art; these discussions are summarized in this report

Structural health monitoring of concrete structures under seismic loads has alwaysattracted a lot of attention in the earthquake engineering community. In this paper, twotests of structural health monitoring of concrete columns using piezoceramic-based sensorsare presented. The first test was a shake table test of a reinforced concrete (RC) column. Apiezoceramic-based device, called a ‘smart aggregate’, was pre-embedded and adopted forthe structural health monitoring of the concrete column under earthquake excitations. Thesecond test of this study was the in situ health monitoring of RC piers of Niu-Dou Bridgein Taiwan, under seismic loading. RC piers instrumented with the post-embeddedpiezoceramic-based sensors were tested using reversed cyclic loading. During the shaketable test and the in situ reversed cyclic loading test, one sensor was used as an actuatorto generate propagating waves, and the other sensors were used to detect thewaves. By analyzing the wave response, the existence of cracks can be detectedand the severity can be estimated. The experimental results demonstrate thesensitivity and the effectiveness of the piezoceramic-based approach in the structuralhealth monitoring of large-scale concrete structures under earthquake loading.

Electrical resistance-based health monitoring of structural smart concrete