Monitoring Of Crack Propagation Research Articles

Comparison between acoustic emission sensors and piezoelectric patches for damage detection in concrete beams

Acoustic emission (AE) sensing is an established technique to monitor crack nucleation and propagation in different types of structural elements and for different damage scenarios. Although effective for crack monitoring in civil infrastructure, off-the-shelf AE sensors can be expensive, discouraging their installation in large numbers for assessing the global structural performance or monitoring multiple assets in the infrastructure network. For this reason, this paper explores the use of piezoelectric patches as an alternative low-cost solution to AE sensors. These patches are considerably cheaper, do not require external power supply and can be easily attached to existing structural elements or embedded into new structures. Moreover, thanks to the direct and inverse piezoelectric effect, the same set of patches can act both as sensors and actuators, meaning that they can be used to “passively” monitor crack propagation over time, as well as to locate and characterize damage in ageing structures at a certain time by using the patches as emitters and receivers of waves. In this framework, this paper proposes a comparison between traditional AE sensors and piezoelectric patches. The comparison is performed on a set of three concrete beams subjected to four-point bending loading, each equipped with two grids of sensors, i.e. 8 AE sensors and 8 patches. The beams are tested under increasing monotonic loading, from zero-load uncracked condition up to collapse.

Machine Learning-Enabled Acoustic Emission Signal Processing for real-time crack growth monitoring in heterogeneous structures

Heterogeneous structures pose unique challenges for structural health monitoring, demanding advanced techniques for early detection of crack propagation. Acoustic Emission (AE) is a non-destructive testing technique that relies on the detection and analysis of stress-induced high-frequency acoustic waves. It is commonly used for identifying and monitoring the development of cracks, defects, or other structural anomalies. However, raw AE data is often noisy and contains background noise and interference, which make them not suitable for reliable real-time crack monitoring applications. This study integrates AE data with machine learning algorithms to provide a proactive and accurate system for continuous crack propagation monitoring. The performance of the proposed approach for features extraction to derive relevant information from the AE signals, data labeling for training machine learning models, and the deployment of these models for real-time monitoring, are discussed.

The multi-dimensional joint response of the electric potential time–frequency-field in the fracture process of flawed coal under dynamic load

The fracture failure of flawed coal has always been a problem in underground engineering. Therefore, it is necessary to monitor crack propagation and damage evolution during coal fracture. In this study, the split Hopkinson pressure bar (SHPB) and digital image correlation (DIC) were combined to analyze the impact failure electric potential (EP) of flawed coal samples. The multi-dimensional joint response characteristics of coal EP time–frequency-field under dynamic load were studied and the differential expression and multi-fractal characteristics of EP responses at different measuring points were analyzed. Based on the EP signals, the evolution of damage to the coal was calculated. The results show that the time series evolution of EP and stress–strain curves during coal failure is consistent. The generation of fracture zones will excite the high-value area of local EP, and the spectral distribution of EP signals in this area shows the characteristics of low frequency and high amplitude. Each channel’s EP signal and the degree of deformation at the corresponding place are perfectly matched. The multi-fractal spectrum of the EP signal close to the fracture zone has a higher Δα and a lower Δf, which demonstrates the dominance of the large-scale EP signal produced in this region by the destruction of sample. Theoretical study indicates that the main causes of the anomalous distribution of the EP field are crack tip potential, diffusion potential, etc. The results can provide theoretical basis for the evaluation of coal fracturing by EP technology.

Hole-edge crack monitoring in attachment lug with large bolt hole based on guided wave and circular piezoelectric sensor array

The crack damage monitoring of aircraft structures is very significant for ensuring aircraft safety, reducing maintenance costs and extending service life. Due to the extreme service environment, the attachment lug is prone to initiate crack damage at the hole edge, which leads to crack propagation and fracture failure. Structural health monitoring technology based on piezoelectric guided wave has been widely studied, promoting the development of crack monitoring. However, at present, research on hole-edge crack damage monitoring of attachment lugs still needs to be further carried out. It is difficult to monitor small cracks at the initial stage of crack propagation, and the accuracy of crack monitoring needs to be improved. By focusing on the accuracy of the crack monitoring in the attachment lug, a crack damage monitoring method based on the circular piezoelectric sensor array is proposed in this paper. Combined with damage alarming and localization imaging, this method comprehensively evaluates the hole-edge crack damage monitoring situation and improves the monitoring effect. The method is verified by an experiment in attachment lug, and this verification includes small crack monitoring and crack propagation monitoring. The experimental results demonstrate that this method can achieve correct damage alarming results, and the maximum localization error of crack damage is only 3.02 mm, which provides a research idea for the accurate monitoring of crack damage at the hole edge.

Infrared imaging surface roughness criticality assessment of Wire Arc Additive Manufactured specimens

Infrared imaging surface roughness criticality assessment of Wire Arc Additive Manufactured specimens

On-chip Sensor for Monitoring Crack Propagation in Solder Joints Using RF signals: Electrical Modeling and Circuit Design

On-chip Sensor for Monitoring Crack Propagation in Solder Joints Using RF signals: Electrical Modeling and Circuit Design

Fracture properties evaluation of structural adhesives using the dual actuator test frame and digital image correlation technique

ABSTRACT This paper implements a dual actuator testing protocol to evaluate the fracture behavior of a toughened epoxy adhesive under mode I and mixed mode I+II loading conditions. Digital image correlation is used to monitor crack propagation and assess adherend and adhesive deformations. A good repeatability between the test results is observed for both failure modes (I and I+II). The constitutive law is obtained by evaluating the J-integral while measuring the crack tip opening displacement. Different mixed mode test strategies are developed in this work. First, an actuator load control protocol is implemented so as to propagate the crack under constant mixed mode I+II ratio and evaluate the fracture envelope of the studied adhesive, which turns out to be adequately described by the Gong-Benzeggagh failure criterion. A second strategy is proposed with a variable mixed mode ratio during the experiment for faster investigation. Using this technique, stable fracture energy values are recorded along the crack propagation path, thus leading to very fast and accurate results.

Online monitoring of fatigue damage in welded joints using diffuse ultrasound

Fatigue damage is a common cause of failure in welded structures, and it is often difficult to detect it in the early stage. While ultrasonic-based methods can effectively monitor crack propagation, it remains a significant challenge to indicate the initiation of cracks. In this study, a novel method is proposed to monitor the diffuse ultrasonic field affected by ratcheting strain and microcracks formed in welded joints during fatigue degradation. The energy density in the diffuse ultrasonic signal is computed and correlated with different fatigue cycles, allowing for online monitoring of fatigue damage in welded joints. Six butt and cross-welded joints were studied under different fatigue conditions, and digital image correlation (DIC) technology was used for comparison throughout the fatigue tests. The results indicate that the correlation coefficient of the energy density in diffuse ultrasound exhibits a significant decreasing trend when crack initiation occurs, providing a unique signal to indicate crack initiation in welded joints. This signal may appear earlier than that from ratcheting strain monitored by DIC due to ultrasound’s sensitivity to internal damages.

In-situ delamination detection in multi-layered semiconductor packages

Accurately determining the material properties of large-area solder joints is crucial for developing precise lifetime models in modern power electronic devices, as these joints play a vital role in providing both electrical and mechanical connections between components. This study presents a novel, non-destructive, and in-situ technique based on laser Doppler vibrometry for detecting crack initiation and monitoring crack growth in semiconductor structures. This method was successfully applied to determine various stages of die attach degradation during accelerated mechanical cyclic tests of large area solder joints, and was verified by scanning acoustic microscopy (SAM) measurements as well as optical methods. Furthermore, analysis of the acoustic emission (AE) signal was conducted as an alternative method for monitoring crack propagation. Optical and electron microscopy were employed to analyse crack initiation, crack paths, and crack surface morphologies. The in-situ delamination detection technique can provide essential information for robust lifetime prediction modelling of material systems in advanced semiconductor components.

Ordinary state-based peri‑ultrasound modeling for monitoring crack propagation in plate structures using sideband peak count-index technique

This work presents a nonlocal theory based on ordinary state-based (OSB) peridynamics for numerical modeling of crack propagation under loadings and peri‑ultrasound modeling for elastic wave propagation that interacts with generated cracks in 3-D plate structures. Propagating cracks in plate structures for two types of loading – tensile and shear are considered. For both loading cases, at six different times after the start of the loading the analysis is carried out to investigate how the results vary for these six different stages of crack propagation. An ultrasonic excitation is applied at a point on the surface of the plate to generate guided waves propagating through the plate structure and interacting with generated cracks at different stages of crack formation. The out-of-plane velocity fields are recorded at the receiving material point for further analysis. A relatively new and promising nonlinear ultrasonic (NLU) technique called sideband peak count-index (or SPC-I) is adopted to extract the nonlinear response due to the generated cracks. Results show that when the crack propagation is at its early stage the SPC-I value first increases, and then decreases with time at the advanced stages of crack propagation. This is because for both types of loading (tensile or shear) the newly generated cracks are small cracks (or micro-cracks) in the beginning and then they evolve into macro-cracks under increasing loadings. The observation for SPC-I trends is consistent with other numerical modelings and experimental observations reported in the literature, and such qualitative matching gives confidence in the proposed method. The proposed method combining the peri‑ultrasound modeling and SPC-I technique presented in this paper can provide a new insight for monitoring crack propagation and give some guidance for experimental structural health monitoring (SHM) applications.

Nondestructive deformation measurements and crack assessment of concrete structure using close-range photogrammetry

Reliable measurement of deformations and crack assessment of concrete structural elements under loading is essential for evaluating the performance and durability of these elements. Traditionally, structural elements are monitored under loading with strain gauges, deflectometer, and data acquisition systems. Limited studies have investigated the potential of close-range photogrammetry and three-dimensional (3D) modeling in analyzing deformations, internal stresses/strains, and crack propagation. This research proposes an innovative four-phase testing method to develop 3D models of the concrete beam with close-range photogrammetry and image processing techniques. The proposed method entails the capabilities of analyzing deformations, internal stresses/strains, and monitoring crack propagation. The main phases of the proposed method are as follows: 1) preparing the test setups, beam preparation, photogrammetry preparation, and surveying preparation; 2) testing the beam under loading while recording deformation data, collecting high-resolution images, and conducting ground-controlled surveying from nine points around the beam; 3) performing photogrammetric processing of the images to generate a textured 3D model of the beam; and 4) comparing the results from both the 3D model and the direct measurements. For triangulation accuracy, the overall RMSE of the generated model is 4.974 mm. While for product accuracy, the RMSE is 9.303 mm. Moreover, the RMSE for deformations is 0.115 mm, indicating acceptable accuracy of measurements through the model. In addition, a photogrammetric-based deformation model can be generated for the beam surface, and cracks area, length, and width are efficiently extracted and monitored.

Fatigue Life Prediction of Notched Details Using SWT Model and LEFM-Based Approach

The fatigue crack initiation life of unwelded steel components accounts for the majority of the total fatigue life, and the accurate prediction of it is of vital importance. In this study, a numerical model utilizing the extended finite element method (XFEM) and Smith-Watson-Topper (SWT) model is established to predict the fatigue crack initiation life of notched details extensively used in orthotropic steel deck bridges. Using the user subroutine UDMGINI in Abaqus, a new algorithm was proposed to calculate the damage parameter of SWT under high-cycle fatigue loads. The virtual crack-closure technique (VCCT) was introduced to monitor crack propagation. Nineteen tests were performed, and the results were used to validate the proposed algorithm and XFEM model. The simulation results show that the proposed XFEM model with UDMGINI and VCCT can reasonably predict the fatigue lives of the notched specimens within the regime of high-cycle fatigue with a load ratio of 0.1. The error for the prediction of fatigue initiation life ranges from -27.5% to 41.1%, and the prediction of total fatigue life has a good agreement with the experimental results with a scatter factor of around 2.

A novel data-based approach for monitoring fatigue crack propagation in welded joints under varying ambient temperature using the electromechanical admittance

Fatigue crack growth is one of the most common damage mechanisms of structural components and can result in a sudden and unexpected abrupt fracture which can cause catastrophic failure. Thus, monitoring of crack propagation is an important topic of structural health monitoring. For that reason, this work aims at the detection of crack propagation by the application of a high-frequency vibration-based method, using the electromechanical admittance (EMA). It enables the local monitoring of the coupled dynamic behavior of the structure and the piezoelectric transducer which changes, for example, due to damage. It is the purpose of this study to develop a method from the recorded data reflecting fatigue crack growth in weld zones. As it is known that the data are affected by temperature, a temperature compensation strategy is considered. In this study, a presentation of the coupled EMA data has been found, which allows the isolation of the crack propagation effects. Within the scope of fatigue experiments, fatigue cracks were introduced into threaded bolts of rail support points, welded onto base plates. In practice, they are embedded in a layer of mortar and, therefore, have poor accessibility. Electromechanical impedance measurements were carried out at different states of fatigue crack growth. The fatigue crack growth was validated by strain gauge measurements executed during the fatigue experiment. The proposed feature was calculated from the recorded EMA data. The technique produces promising results detecting fatigue cracks and can also be transferred to similar types of welded joints or rods where fatigue crack growth occurs.

Pressure-induced damage monitoring in prestressed concrete of nuclear containment wall segments using acoustic emission technique – Application to VeRCoRs containment building

This paper reports benchmark findings of an experimental study of pressure-induced damage monitoring in a nuclear containment building (NCB) reproducing realistic conditions of internal pressure increase accidents. The leak-tightness of NCBs is assessed every 10 years during integrated leak-rate tests (IRLT). For double-wall containments, which have no metallic liners, the leak-tightness is strongly influenced by the degree of cracking of concrete and opening of the cracks. This paper is focused on assessing the effectiveness of the Acoustic Emission (AE) technique to evaluate the damage evolution of a reinforced concrete containment wall under pressure loading test. Piezoelectric accelerometers were mounted on the internal containment wall of the VeRCoRs mockup, which constitutes the containment building of a Nuclear Power Plant in a 1:3 scale. The Akaike criterion (AIC) as an AE hit picking method and the adaptive meshing algorithm (AMA) as an AE events localization algorithm have been applied for damage and cracking monitoring. A benchmark analysis based on the distribution of AE events and energy is presented for the detection of damages and the monitoring of crack propagation in correlation with the known locations of main cracks. The potential and limitations of the AE technique for in situ damage sources estimation are discussed upon two experimental campaigns (2017 and 2019), and the main conclusions of the benchmark survey are given. The results show that the AE technique is adequate for damage evaluation in large-scale concrete structures. It provides important information about the integrity of the structure and the assessment of damage evolution with time.

Monitoring structural health status of asphalt pavement using intelligent sensing technology

• A method for estimating the global pavement health based on partial data is proposed. • A new indexe is developed to accurately characterize the damage degree of pavement. • SmartRock sensor can be used to monitor the stress changes within the cement mortar. Pavement health monitoring (PHM) based on intelligent sensing technology is of great significance for road maintenance and management. This paper proposes a method for local damage monitoring and global health evaluation of pavement based on embedded wireless sensors. Firstly, 3D finite element (FE) models are employed to investigate the response characteristics of healthy and degraded pavement structures under moving loads, whereby an index DI is proposed to quantitatively evaluate the damage characteristics. In addition, three-point bending (TPB) fracture tests are carried out on cement mixture to investigate the effectiveness of Smartrock in monitoring crack propagation, and the results show that the stresses recorded by the sensors can be used to characterize the different stages of crack propagation. Further, a method for estimating the global stress distribution in pavement structure using the monitoring data obtained from a limited number of sensors is developed based on Kriging method. The test results show that the prediction accuracy decreases as the number of training sets decreases, but when the training sets account for 50% of the total, the correlation coefficient R 2 between the predicted and true values is still more than 0.9 and the average relative error (ARRE) is less than 10%, and demonstrate that the interpolation method proposed in this paper can accurately evaluate the global stress distribution based on the monitoring data obtained from a limited number of sensors.

A Digital Image Correlation (DIC) prototype system for crack propagation monitoring in aircraft assemblies.

Background: In the Clean Sky 2 project DIMES, the cyclic loading of a section of an A320 wing with pre-existing damage was carried out. Methods: We present a Digital Image Correlation (DIC) prototype system to monitor crack propagation in the aircraft wing. This system includes a mount for easy installation and adjustment in a confined space. Results: Strain localization and evaluation due to crack propagation was successfully observed in the Region-of-Interest (ROI) during cyclic fatigue loading. The results from the DIC prototype system were supported by conventional contact Resistance Strain Gauge (RSG) sensors acting as a far-field monitor. Conclusions: Future improvements, the combination of two DIC modules for a stereo DIC system and the potential of the DIC system for ground-based tests and Structural Health Monitoring (SHM) applications are also discussed.

An island-bridge packaging piezoelectric sensor for structural health monitoring in high-strain environments

Piezoelectric sensor failure triggered by high structural strain is a critical problem in structural health monitoring (SHM) that cannot be neglected. Thus, a novel island-bridge packaging piezoelectric sensor for SHM in high-strain environments is proposed in this paper. The trapezoidal-section island-bridge structure of the new sensor greatly optimizes the high-strain survivability of the piezoelectric layer. Additionally, good impedance matching characteristics between the monitored structure and the sensor guarantee the transmission strength of high-frequency dynamic sensing signals. The feasibility of the structure and the principle of operation for the novel sensor were demonstrated via theory, simulation and experiment. Besides, an established analytical model and its simulation and experimental verification results displayed that the structural parameters of the sensor could significantly adjust the strain-bearing capacity. Under a specific parameter configuration, the strain transfer coefficient of the novel sensor was only 0.087, which was 12.1% of the conventional sensor, thus could safely operate in the monitoring structure environment of 10,000 με. On the other hand, the proposed sensor’s impedance signal strength was satisfactory in the SHM frequency range of 10–110 kHz, where its average impedance value was as high as 397.7 Ω. Moreover, the optimized signal demonstrated very good stability, reliability, and strength in the test, thus ensuring the effective monitoring of crack propagation via the new sensor. Therefore, this work is a good complement to the existing piezoelectric sensors SHM technique.

Sensing performances of hybrid steel wires and fibers reinforced ultra-high performance concrete for in-situ monitoring of infrastructures

Steel wires (SWs) with microscale diameter and high aspect ratio can overlap each other to form the stable conductive network at a low content, thus they are the promising conductive fillers to enhance the poor conductivity and sensing capacity of ultra-high performance concrete (UHPC) containing steel fibers (SFs) for in-situ monitoring of infrastructures. In this paper, the electrical conductivity and sensing performances to flexural loading of hybrid SWs and SFs reinforced UHPC are investigated, meanwhile, the conductive and sensing mechanisms are revealed by the analysis on microstructure, equivalent circuit and cracking behavior of composites. The test results indicated that 0.4 vol% SWs are in the percolation threshold zone, and the hybrid SWs and SFs have a positive synergistic effect on the conductivity of UHPC. The optimum electrical resistivity of UHPC with SFs can be reduced from 12900 Ω cm to 1310 Ω cm due to the addition of SWs. The hybrid SWs and SFs reinforced UHPC can effectively monitor the cracking initiation and development by measuring the fractional change in resistivities (FCR) under flexure, especially it performs more stable and accurate in monitoring the initial cracking and more sensitive in monitoring residual flexural loading and cracking development compared to mono SFs reinforced UHPC. This can be attributed to the inhibition effect of SWs on microcracks and the extensively conductive network formed by both SWs and SFs. UHPC with low content of hybrid SWs and SFs can already achieve self-sensing with high stability and sensibility in terms of in-situ monitoring crack initiation and propagation under flexural loading.

Effect of different exposure conditions on the self‐healing capacity of engineered cementitious composites with crystalline admixture

AbstractIn this study, the effect of different exposure conditions of ambient air, tap water, and seawater on two levels of crack widths in engineered cementitious composites (ECC) were investigated. Crystalline admixture (CA) was implemented in the ECC mix to promote self‐healing capacity. Flexural testing on prism specimens (100 × 100 × 350 mm) was conducted to evaluate self‐healing by recovering the stiffness in the specimens with crack widths below 200 μm. Water permeability test was also carried out to assess the crack‐filling capability of ECC disk specimens (100‐mm diameter × 50‐mm thickness) with single crack widths over 1 mm. Digital image correlation technique was used to monitor crack propagation patterns and crack widths. To analyze the microstructure of the healing products, X‐ray diffraction test was conducted on groups of tap water and seawater exposures. Concluding results proved seawater to be a promising environmental condition for the self‐healing process in ECC specimens incorporating CA, in terms of recovery of mechanical and transport properties. Brucite was found to be formed as the additional healing agent that promoted self‐healing in this condition. These results can be applied for coastal concrete structures.

Blade tip timing for monitoring crack propagation of rotor blades using Block-AOLS

Blade tip timing (BTT) as a non-contact measurement technique can identify the blade vibration parameters. However, the signal recorded by BTT usually does not satisfy the Nyquist sampling theorem. To monitor blade crack propagation, it is important to accurately reconstruct the BTT signal to track the natural frequency shift of the rotor blade. In this paper, a sparse reconstruction method named block-accelerated orthogonal least-squares (Block-AOLS) is proposed to reconstruct the undersampled BTT signal in the time-frequency domain. Block-AOLS not only inherits the advantage of the high accuracy of AOLS but also makes use of the characteristic of block sparsity to reduce the interference components in the BTT signal. Furthermore, Block-AOLS is used to reconstruct the undersampled BTT signal to track the natural frequencies of cracked blades. The advantage of Block-AOLS is illustrated through simulation by comparing with the classical orthogonal matching pursuit. In the spin testing, the vibration of a blisk with eight blades is measured by both BTT and strain gauges, where two symmetrical blades without artificial cracks suddenly broke. The process of crack propagation can be inferred according to the shift of natural frequencies between the perfect and cracked blades. Moreover, a vibration frequency prediction method is provided to avoid comparing the natural frequencies among different blades for crack propagation monitoring, which is suitable to monitor the mistuning blades. To verify the reliability of the crack propagation monitoring using BTT, the strain signal with interval sample is analyzed by synchroextracting transform. Compared the natural frequency of the perfect blade with that of the cracked blade, the time when the natural frequency of the cracked blade shift is the same as that of the BTT result.