Martensitic grade stainless steel is generally used to manufacture steam turbine blades in power plants. The material degradation of those turbine blades, due to fatigue, will induce unexpected equipment damage. Fatigue cracks, too small to be detected, can grow severely in the next operating cycle and may cause failure before the next inspection opportunity. Therefore, a nondestructive electromagnetic technique, which is sensitive to microstructure changes in the material, is needed to provide a means to estimate the specimen’s fatigue life. To tackle these challenges, this paper presents a novel Magnetic Barkhausen noise (MBN) technique for garnering information relating to the material microstructure changes under test. The MBN signals are analyzed in time as well as frequency domain to infer material information that are influenced by the samples’ mate- rial state. Principal Component Analysis (PCA) is applied to reduce the dimensionality of feature data and extract higher order features. Afterwards, Probabilistic Neural Network (PNN) classifies the sample based on the percentage fatigue life to discover the most correlated MBN features to indicate the remaining fatigue life. Furthermore, one criticism of MBN is its poor repeatability and stability, therefore, Analysis of Variance (ANOVA) is carried out to analyze the uncertainty associated with MBN measurements. The feasibility of MBN technique is investigated in detecting early stage fatigue, which is associated with plastic deformation in ferromagnetic metallic structures. Experimental results demonstrate that the Magnetic Barkhausen Noise technique is a promising candidate for characterizing.

Ultrasonic structural health monitoring (SHM), employing embedded piezoelectric elements to actuate and sense ultrasonic waves, has greatly advanced in recent years. This paper presents a novel approach to address the prevailing challenges in the inspection of laminated structures for delamination using shear-mode (d15) piezoelectric transducers, composed of lead zirconate titanate (PZT). To experimentally evaluate the effectiveness of the proposed approach, a beam-like laminated specimen consisting of internally embedded d15 square PZTs was fabricated with simulated delamination at the interface of an adhesive joint. The evaluation of the results showed that the location of shear-mode actuators is a critical factor to detect delamination and to predict the propagation path of delamination. Delamination initiated close to actuators is more likely to be detected owing to their remarkable sensitivity of structural stiffness surrounding their region. The antisymmetric A0 wave mode generated by these actuators exhibits high interaction with damage, suggesting internally embedded d15 PZTs are a viable approach that can potentially advance the inspection tools of ultrasonic SHM.

An important advantage of guided waves is their ability to propagate large distances and yield more information about flaws than bulk waves. Unfortunately, the multi-modal, dispersive nature of guided waves makes them difficult to use for locating flaws. In this work, we present a method and experimental data for removing the deleterious effects of multi-mode dispersion allowing for source localization at frequencies comparable to those of bulk waves. Time domain signals are obtained using a novel 64-element phased array and processed to extract wave-number, and frequency spectra. By an application of Auld's reciprocity theorem, mode amplitudes are extracted approximately using a variational method. Once mode contributions have been obtained, the dispersion for each mode can be removed via back-propagation techniques. Excepting the presence of a small artifact at high frequency-thickness products, experimental data successfully demonstrates the robustness and viability of this approach to guided wave source location.

When stress in concrete exceeds certain threshold value, microcracks are nucleated, these microcracks can propagate and coalesce forming macrocracks, resulting in the gradual decay of the mechanical properties of concrete and eventual failure of the concrete structures. For safety concerns, one needs to develop suitable nondestructive testing methods capable of detecting past overloads of concrete structures during its service life. In this work, the stress-induced damage in concrete is monitored using ultrasonic techniques, exploiting the coupling between the stress level experienced by concrete and its wave propagation parameters. Cyclic compression tests with increasing maximum load level have been performed on specimens made of concrete with coarse-grained (CG) aggregates. Experimental results have been analyzed by two different ultrasonic methods—the linear and the nonlinear ultrasonic techniques. In linear ultrasonic technique, the stress level experienced by the specimens is related to the variations in signal amplitude and velocity of ultrasonic waves. In nonlinear ultrasonic method, the sideband peak count (SPC) technique is used for revealing the stress-induced damage corresponding to each load step. In comparison to linear ultrasonic parameters, the nonlinear ultrasonic parameter SPC-I appears to be more sensitive to the variations of the internal material structures during both loading and unloading phases. Moreover, the SPC technique has shown to be capable of identifying both the initial damage due to the evolution and nucleation of microcracks at the microscopic scale, and the subsequent damages induced by high overload, resulting in an irreversible degradation of the mechanical properties.

In view of their higher sensitivity in localizing an incipient damage, methods of NDE based on the nonlinear wave-damage interactions have been of continued interest. In this paper, the propagation of guided waves through a delamination with contacting interfaces is studied numerically using a finite element based framework. In particular, influence of the interlaminar location of the delamination on the nonlinear acoustic features in the response spectrum is investigated in detail. The numerical framework is validated by an in-house experimentation performed on a unidirectional GFRP laminate containing a through-width delamination. A parameter, referred to as the nonlinearity index, is defined for quantifying the strength of the nonlinear wave-damage interactions and its dependence on the interlaminar location of the delamination is studied across a range of interrogation frequencies. The notion of contact energy intensity is introduced and further used for justifying the trends of variation of the nonlinearity index obtained numerically and observed experimentally. Results indicate that two fundamental parameters govern the underlying contact phenomenon; they are, the phase difference between the wave packets passing through the two sub-laminates and the flexural rigidities of the two sub-laminates present at the site of the delamination defect. While the former controls the relative displacement between the two sub-laminates, the latter governs the propensity of collisions between the two sub-laminates. Finally, a diametric effect of these two parameters on the generation of nonlinear harmonic signals with varying interlaminar location of the delamination is brought out.

A novel failure model updating methodology is presented in this paper for composite materials. The innovation in the approach presented is found in both the experimental and computational methods used. Specifically, a dominant bottleneck in data-driven failure model development relates to the types of data inputs that could be used for model calibration or updating. To address this issue, nondestructive evaluation data obtained while performing mechanical testing at the laboratory scale are used in this paper to form a damage metric based on a series of processing steps that leverage raw sensing inputs and provide progressive failure curves that are then used to calibrate the damage initiation point computed by full-field three-dimensional finite element simulations of fiber-reinforced composite material that take into account both intra- and interlayer damage. Such curves defined based on nondestructive evaluation data are found to effectively monitor the progressive failure process, and therefore, they could be used as a way to form modeling inputs at different length scales.

Safety and reliability of large critical infrastructure such as long-span bridges, high-rise buildings, nuclear power plants, high-voltage transmission towers, rotating machinery, and so on, are important for a modern society. Research on reliability and safety analysis started with a “small data” problem dealing with relative scarce lifetime or failure data. Later, degradation modeling that uses performance deterioration, or, condition data collected from in-service inspections or online health monitoring became an important tool for reliability prediction and maintenance planning of highly reliable engineering systems. Over the past decades, a large number of degradation models have been developed to characterize and quantify the underlying degradation mechanism using direct and indirect measurements. Recent advancements in artificial intelligence, remote sensing, big data analytics, and Internet of things are making far-reaching impacts on almost every aspect of our lives. The effect of these changes on the degradation modeling, prognosis, and safety management is interesting questions to explore. This paper presents a comprehensive, forward-looking review of the various degradation models and their practical applications to damage prognosis and management of critical infrastructure. The degradation models are classified into four categories: physics-based, knowledge-based, data-driven, and hybrid approaches.

This paper presents a non-contact air-coupled Lamb wave imaging technique using a two-dimensional (2D) cross-correlation method that not only detects the damage but also precisely quantifies for orientations and sizes. The air-coupled transducers (ACT) is used together with a scanning laser Doppler vibrometer (SLDV) for sensing, making a fully non-contact Lamb wave system used for this study. We first show that single-mode Lamb wave actuation can be achieved by the ACT-based on Snell's law. Detailed study and characterization of the directional ACT Lamb waves are conducted. For damage detection, a 2D cross-correlation imaging technique that uses the damage introduced scattered waves of all directions is proposed for correlating with the incident waves. The frequency-wavenumber filtering technique is used to implement the acquisition of the scatted waves and incident waves, respectively. In the end application to notches with various orientations and various sizes in terms of depth and length is given. The results show the proposed technique can precisely imaging the damages and can quantitatively evaluate the damage size in terms of length and depth.

Timber poles are widely used in electricity transmission and telecommunication sectors throughout the world. The stress wave propagation for the condition assessment of timber poles is identified as a promising non-destructive testing (NDT) technique due to its simplicity and cost-effectiveness compared to other traditional methods. In this paper, a novel damage severity evaluation criterion for timber poles is proposed on the basis of short-time wavelet entropy of the reflected stress waves. The stress waves are generated by transverse impacts close to the ground level of the pole. The reflected stress waves are recorded and processed in the time frequency domain using the discrete wavelet transform. The decomposed signal components using discrete wavelet analysis are used to determine the wavelet entropy. The wavelet entropies of intact and damaged poles are compared to obtain the relative wavelet entropy (RWE) for damage severity estimation. Further, a numerical model for an in situ pole system is developed to simulate the transverse stress wave propagation and to evaluate the capability of the proposed defect severity estimation method. The developed numerical model is validated with experimental data from controlled testing and the data from field tests. The validated numerical model is then used to simulate different defect scenarios. The wavelet entropy is sensitive to the damage severity in timber poles and can be used as an effective tool to evaluate the severity of damages.

Nonlinear ultrasonic (NLU) techniques have emerged as a potential solution to improve the resolution of nondestructive measurements to detect microstructural changes of cyclically loaded materials. However, current NLU methods need power-demanding instrumentation that is useful only in the laboratory settings. On the other hand, phased array systems provide the capability of sensing such changes when the later portion of the elastic waveforms, called diffuse field, is analyzed. Moreover, phased array systems are an excellent solution for field test measurement and imaging of material damage. This study explores the use of NLU metrics based on ratios of harmonic amplitudes and frequencies to map the buildup of damage precursors, such as crystal dislocations, under cyclic loading within the microstructure of fatigued 2024-T3 aluminum specimens. The results show that these metrics are highly sensitive to microstructural fatigue damage making them significantly important to measure mechanical properties, such as fracture toughness, that are extremely useful in predicting the remaining useful life of a studied material. A nonlinear metric of elastic energy that encapsulates the nonlinear effects of subharmonic and higher-harmonic generations and frequency ratio is proposed. These effects of spectral energy shifts are combined making this metric highly sensitive to nano- and micro-scale damage within the fatigued medium.

Ultrasonic phased array (UPA) provides a powerful tool for nondestructive testing (NDT) of carbon fiber-reinforced plastic (CFRP). By the aid of full matrix capture (FMC) technique, the optimum resolution of anisotropic CFRP inspection could be achieved by the total focusing method (TFM). The directional dependence of ultrasonic velocity is one of the biggest challenges due to the anisotropy of CFRP. The objective of this research is to establish a joint method to estimate direction-dependent velocity and damage location of CFRP. To obtain group velocity without prior knowledge of neither theoretical calculation nor experimental determination, a limited angle range of the anisotropic velocity is first obtained by backwall reflection method (BRM), which is then extended by analyzing the relation between the time delay of backwall and side drilled hole (SDH) reflection. The effectiveness of the proposed method is experimentally demonstrated with UPA imaging of SDH in composite laminates.

Honeycomb sandwich structures (HSS) are widely used in the aerospace industry due to their high strength-to-stiffness ratio. However, these materials are susceptible to damage during manufacturing or service that can cause great loss in the load bearing capacity or even failure. Thus, periodic or continuous nondestructive evaluation (NDE) of HSS is essential for safe operation. Development of effective NDE technique is challenging due to the geometric complexity of the honeycomb core. Guided ultrasonic waves are ideal for large-scale testing because of their large propagation range and high sensitivity to defects in their path. In this paper, an improved NDE method for detecting disbonds at the top and bottom interfaces between the core and facesheets is proposed based on experimental studies. By applying excitation signals at different frequencies, the responses at the top and bottom surface of plate-like HSS component are compared and analyzed. The response in a specific frequency range is further studied by introducing disbonds at the top interface. It is shown that some components of the recorded signal in a specific frequency range are more sensitive for detecting the disbond. In addition, an improvement of the conventional damage index based on the damage feature is proposed, and a systematic procedure for detecting damage inside HSS is conducted on an elevator section of an Airbus 330. The results show that the optimized damage index greatly improves the resolution and adaptability of damage detection in the structures.

Characterization of barely visible impact damage (BVID) in polymer matrix composites (PMCs) is necessary to use slow crack growth damage tolerance models and evaluate remaining life of PMC components. Azimuthally scanned angled-beam pulse-echo ultrasound is investigated as a complimentary technique to normal incidence ultrasound inspection of BVID in PMCs to characterize delamination fields. It is found that there is a correlation between signals present in the azimuthally scanned angled-beam pulse-echo ultrasound C-scans and transverse cracks seen in X-ray computed tomography inspection. These transverse cracks are not readily identifiable as transverse cracks in normal incidence C-scan inspection.

The use of eddy current (EC) arrays to detect damage in sandwich panels, such as disbonding of the carbon fiber reinforced polymer (CFRP) face-sheet to the core, is investigated. It is shown that the array is very sensitive to slight core crush and can readily find small dents and disbonds. At the same time, the eddy current array can look much deeper into the honeycomb to detect defects such as tears. The phase map of the EC signal can be used in some cases to distinguish between different types of damage. EC arrays offer the ability to rapidly scan large areas of CFRP panels.

Cyclic loading of mechanical components promotes the formation of dislocation substructures in metals as precursors to crack nucleation leading to final failure of the metallic components. It is well known within the ultrasonic community that the acoustic nonlinearity parameter is a meaningful indicator of the microstructural damage accumulation. However, current nonlinear ultrasonic techniques suffer from response saturation and limited resolution after 50% fatigue life of the metallic medium. The present study investigates the feasibility of incorporating collinear wave mixing interactions into second harmonic assessments to improve the sensitivity of the nonlinear parameter to a microstructural accumulation of damage precursors (DP). To this end, a decomposition technique was explored to obtain higher harmonics from short time-domain pulses propagating through thin metallic components such as jet engine turbine blades. The results demonstrate the effectiveness of the decomposition technique to measure the acoustic nonlinearity parameter as an early and continuous indicator of fatigue damage precursors throughout the service life of critical aircraft components. A micrographic study showed a strong correlation between the nonlinearity parameter and the increase in damage precursors throughout the life of the specimens.

The understanding of strength recovery behavior under a dynamic loading environment provides a guidance for optimizing the design of composite structures for in-service applications. Although established for metals, the quantification of strength recovery in carbon fiber-reinforced viscoelastic composites is still an area under active research. This study aims to understand the effects of fatigue loading rates on the damage behaviors of stress-relaxed carbon fiber-based composites. Hence, the time-dependent strength recovery in woven composites is quantified experimentally using two mutually exclusive approaches under identical fatigue loading environments. In the first approach, the strength recovery is quantified by the dissipated non-linearity in Lamb wave propagation due to the damage state of the composite materials. This is quantified and shown coupled with second- and third-order non-linear parameters. In the second approach, ultrasonic acoustic pressure waves are utilized to quantify the fatigue-induced internal stress and the damage accumulation. A comparison of these two approaches leads to the assessment of strength reduction which is experimentally validated with the remaining strength of the specimens.

This study aims to detect, localize, and assess the severity of barely visible indentation damage in a composite sandwich structure using ultrasonic guided waves. A quasistatic loading was gradually applied on a specimen of carbon fiber reinforced epoxy resulting in dents on the surface. Lamb-wave measurements, from a sensor network mounted on the panel's surface, were taken for the intact condition and three damage cases (0.2, 0.5, and 2.7-mm dents). Three approaches were adopted to define the damage indices (DIs) toward anomaly detection, namely, amplitude variation, symbolic dynamics, and root mean square deviation. Data fusion was performed between measurements from multiple excitation frequencies for single and multiple DIs, where the anomaly combination between all the frequencies and the DIs was called a total anomaly. An imaging algorithm was implemented for damage localization in conjunction with single and combined DIs. It was shown that combining the effects of different frequencies and/or different DIs increases the robustness and consistency of the damage detection and localization process. Moreover, a distance-based classification technique was applied using features from single DIs and the combined anomaly measure. Accuracies higher than 91% were attained for the majority of the cases tested.

Fiber-reinforced metal laminate (FRML) composites are currently used as a structural material in the aerospace industry. A common FRML, glass layered aluminum reinforced epoxy (Glare), possesses a set of mechanical properties which was achieved by designing its layup structure to combine metal alloy and fiber-reinforced polymer phases. Beyond static and dynamic mechanical properties at the material characterization phase, however, the need exists to develop methods that could assess the evolving material state of Glare, especially in a progressive failure context. This paper presents a nondestructive approach to monitor the damage at the material scale and combine such information with characterization and postmortem evaluation methods, as well as data postprocessing to provide an assessment of the failure process during monotonic loading conditions. The approach is based on multiscale sensing using the acoustic emission (AE) method, which was augmented in this paper in two ways. First, by applying it to all material components separately in addition to actual Glare specimens. Second, by performing testing and evaluation at both the laboratory scale as well as at the scale defined inside the scanning electron microscopy. Such elaborate testing and nondestructive evaluation results provided the basis for the application of digital signal processing and machine learning methods which were capable to identify data trends that are shown to be correlated with the evolution of failure modes in Glare.

In this paper, the time-varying autoregressive (TVAR) model is integrated with the K-means—clustering technique to detect the damage in the steel moment-resisting frame. The damage is detected in the frame using nonstationary acceleration response of the structure excited using ambient white noise. The proposed technique identifies and quantifies the damage in the beam-to-column connection and column-to-column splice plate connection caused due to loosening of the connecting bolts. The algorithm models the nonstationary acceleration time history and evaluates the TVAR coefficients (TVARCs) for pristine and damage states. These coefficients are represented as a cluster in the TVARC subspace and segregated and classified using K-means—segmentation technique. The K-means—approach is adapted to simultaneously perform partition clustering and remove outliers. Eigenstructure evaluation of the segregated TVARC cluster is performed to detect the temporal damage. The topological and statistical parameters of the TVARC clusters are used to quantify the magnitude of the damage. The damage is quantified using the Mahalanobis distance (MD) and the Itakura distance (ID) serving as the statistical distance between the healthy and damage TVARC clusters. MD calculates a multidimensional statistical distance between two clusters using the covariance between the state vectors, whereas ID measures the dissimilarity of the autoregressive (AR) parameter between reference state and unknown states. These statistical distances are used as damage-sensitive feature (DSF) to detect and quantify the initiation and progression of the damage in the structure under ambient vibrations. The outcome of both the DSFs corroborate with the experimental investigation, thereby improving the robustness of the algorithm by avoiding false damage alarms.

The objective of this work is to assess to which extent the interaction of antisymmetric ultrasonic guided waves with impact damage can be captured with an experimental model consisting of a single artificial delamination in composite structures. The structures of interest are composed of unidirectional prepreg carbon fiber-reinforced polymer (CFRP) with a quasi-isotropic layup. The artificial delamination is introduced into the laminate using two circular Teflon tapes during manufacturing and the realistic damage is simulated by impacting the samples at two energy levels. Two colocalized rectangular piezoceramics are used to generate an antisymmetric mode and noncontact measurement is performed using a three-dimensional (3D) laser Doppler vibrometer (3D-LDV) to extract the required information for evaluation of the reflection, transmission, as well as the scattering behavior of the antisymmetric mode. The corresponding coefficients as a function of frequency, incident angle, and type of damage are extracted. It is found that the amplitude of the coefficients and directivity patterns of scattered waves are barely affected by incident angle but significantly by the impact energy. In light of the results, design guidelines are proposed for efficient guided wave inspection of composite structures submitted to impacts.