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.

Multi-stage gearboxes are vulnerable to failures often due to the extreme operating conditions, which may result in long downtimes. The current investigation is intended to examine the fault diagnostic capabilities of the integrated vibro-acoustic condition monitoring scheme while diagnosing the local/lumped defects exist at different speed stages of a multi-stage gearbox subjected to fluctuating/varying speeds. Experiments are performed, and the raw vibration and acoustic signatures are acquired simultaneously from the three-stage spur gearbox. Later, the raw data signatures are processed individually through discrete wavelet transform, and various descriptive statistics are extracted. Further, feature-level fusion is executed to obtain the integrated vibro-acoustic feature vector set for various speed stages of the gearbox. Finally, the obtained integrated feature vector set is classified using principal component analysis (PCA). It is observed that PCA performed using the integrated vibro-acoustic scheme clearly distinguishes among the various damage severity levels of pinion tooth exist at different speed stages of the gearbox.

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.

Forecasting and detection of fatigue cracks play a key role in damage mitigation of mechanical structures (e.g., those made of polycrystalline alloys) to enhance their service life, and ultrasonic testing (UT) has emerged as a powerful tool for detection of fatigue cracks at early stages of damage evolution. Along this line, the work reported in this paper aims to improve the performance of fatigue crack forecasting and detection based on a synergistic combination of discrete wavelet transform (DWT) and Hilbert transform (HT) of UT data, collected from a computer-instrumented and computer-controlled fatigue-testing apparatus. Performance of the proposed method is evaluated by comparison with the images generated from a digital microscope, which are treated as the ground truth in this paper. The results of comparison reveal that forthcoming fatigue cracks can be detected ahead of their appearance on the surface of test specimens. The proposed method apparently outperforms both HT and conventional DWT, when they are applied individually, because the synergistic combination of DWT and HT provides a better characterization of UT signal attenuation for detection of fatigue crack damage.

A guided wave-based structural health monitoring (GW-SHM) system aims at determining the integrity of a wide variety of plate-like structures such as aircraft fuselages, pipes, and fuel tanks. It is often based on a sparse grid of piezoelectric transducers for exciting and sensing GWs that under certain conditions interact with damage while propagating. In recent years, various defect imaging algorithms have been proposed for processing GWs signals and, particularly, for computing an image representing the integrity of the studied structure. The performance of the GW-SHM system highly depends on a signal processing methodology. This paper compares defect localization accuracy of the three state-of-art defect imaging algorithms (delay-and-sum, minimum variance, and excitelet) applied to an extensive simulated database of GWs propagation and GWs-defect interaction in aluminum plate under varying temperature and transducers degradation. This study is conducted in order to provide statistical inferences, essential for SHM system performance demonstration.

Electronics operating at cryogenic temperatures play a critical role in future science experiments and space exploration programs. The Deep Underground Neutrino Experiment (DUNE) uses a cold electronics system for data taking. Specifically, it utilizes custom-designed Application Specific Integrated Circuits (ASICs). The main challenge is that these circuits will be immersed in liquid Argon and that they need to function for 20+ years without any access. Ensuring quality is critical, and issues may arise due to thermal stress, packaging, and manufacturing-related defects: if undetected, these could lead to long-term reliability and performance problems. This paper reports an investigation into non-destructive evaluation techniques to assess their potential use in a comprehensive quality control process during prototyping, testing, and commissioning of the DUNE cold electronics system. Scanning acoustic microscopy (SAM) was used to investigate permanent structural changes in the ASICs associated with thermal cycling between room and cryogenic temperatures. Data are assessed using a correlation analysis, which can detect even minimal changes happening inside the ASICs.

Accelerometers, used as vibration pickups in machine health monitoring systems, need physical connection to the machine tool through cables, complicating physical systems. A non-contact laser based vibration sensor has been developed and used for bearing health monitoring in this article. The vibration data have been acquired under speed and load variation. Hilbert transform (HT) has been applied for denoising the vibration signal. An extraction of condition monitoring indicators from both raw and envelope signals has been made, and the dimensionality of these extracted indicators was deducted with principal component analysis (PCA). Sequential floating forward selection (SFFS) method has been implemented for ranking the selected indicators in order of significance for reduction in the input vector size and for finalizing the most optimal indicator set. Finally, the selected indicators are passed to k-nearest neighbor (kNN) and weighted kNN (WkNN) for diagnosing the bearing defects. The comparative analysis of the effectiveness of kNN and WkNN has been executed. It is evident from the experimental results that the vibration signals obtained from developed non-contact sensor compare adequately with the accelerometer data obtained under similar conditions. The performance of WkNN has been found to be slower compared to kNN. The proposed fault detection methodology compares very well with the other reported methods in the literature. The non-contact fault detection methodology has an enormous potential for automatic recognition of defects in the machine, which can provide early signals to avoid catastrophic failure and unplanned equipment shutdowns.

X-ray phase contrast imaging (XPCI) is a nondestructive evaluation technique that enables high-contrast detection of low-attenuation materials that are largely transparent in traditional radiography. Extending a grating-based Talbot-Lau XPCI system to three-dimensional imaging with computed tomography (CT) imposes two motion requirements: the analyzer grating must translate transverse to the optical axis to capture image sets for XPCI reconstruction, and the sample must rotate to capture angular data for CT reconstruction. The acquisition algorithm choice determines the order of movement and positioning of the two stages. The choice of the image acquisition algorithm for XPCI CT is instrumental to collecting high fidelity data for reconstruction. We investigate how data acquisition influences XPCI CT by comparing two simple data acquisition algorithms and determine that capturing a full phase-stepping image set for a CT projection before rotating the sample results in higher quality data.

This work focuses on non-destructive examinations using array probe ultrasonic waves on complex materials generating a high structural noise on the examined area. During an ultrasonic examination, multiple scattering of the ultrasonic waves at the grain boundaries makes the distinction between this structurally induced noise and a potential defect challenging. The difficulty of the interpretation can moreover be increased in the near surface area because of the subsurface wave. In order to ease the analysis of these acquisitions, some numerical processing methods are proposed. Statistical properties of the imaging results (for instance, total focusing method or plane wave imaging) are first calculated on several sensor positions. These statistical properties are then used to post-process the imaging results and enhance any signal values that do not belong to the structural noise expected statistics. The method, called “CORUS,” has been successfully tested on cast austenoferritic stainless steel coarse-grained mock-ups, with several dB gain compared to the classical total focusing method. It is now integrated in a civa software plugin and in a prototype version of the real-time PANTHER-phased-array acquisition system from Eddyfi Technologies.

In a reliability assessment of ultrasonic time-of-flight diffraction (TOFD) inspection, probability of detection (POD) and sizing (POS) curves are developed. Experiments are performed on a complex geometry specimen with the grooved inspection surface simulating the gland seal area of a steam turbine rotor. In the reliability experiment, it is assumed and confirmed that the distribution of signal responses is normal. The effects of probe center spacing on detection and sizing are observed. The PODs developed here have a decreasing trend with flaw size which is in contrary to the generally observed increasing trend in conventional ultrasonic amplitude-based flaw sizing techniques. The reason for this decreasing POD with crack height is explained in the present study. The curves developed in this work are specific to the geometry and dimensions of the specimen with the set of notches and the probes used in the experiment. Hence, these curves can only be used under similar conditions. In TOFD inspection of similar type of complex shaped structures, e.g., turbine, the POD and POS curves developed here can be used in taking an appropriate engineering decision with respect to run, repair, or replace.

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.

Corrosion of carbon steel rebar in concrete structures, such as highway bridges and buildings, has a direct impact on their structural integrity since the rebar provides the tensile strength within the structure. Rebar strength depends on the remaining effective radius of a given rod. Long-time decay up to 0.1 s, in the transient response of pulsed eddy current (PEC), was examined as a potential method to quantify general corrosion in ferromagnetic rebar. The transient response of a coaxial solenoidal drive–receive coil pair, oriented parallel to the rebar axis, was analyzed over a range of distances into the concrete (liftoff) and rebar radii. At long times, the single exponential decay constant was largely independent of liftoff. A power law relationship for the characteristic decay time, consistent with long-time diffusion of electromagnetic fields into a rod, was observed. The intercept of a best-fit line to measured voltage decay decreased exponentially with liftoff and maintained a measurable response up to 110 mm distance for a 25 mm (1 in.) diameter rebar. This exponential decay was present in 22 mm (7/8 in.), 19 mm (3/4 in.), and 15 mm (5/8 in.) samples as well. Reported results demonstrate the potential for PEC to quantify remaining cross-sectional area of rebar in concrete structures.

Owing to the frequency of occurrence and high risk associated with bearings, identification, and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, among which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance, or bearing faults. Such anomalies may not only pose risks to UAV’s internal circuitry, components, or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

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.

Steel structures with bolted joints are easily dismantled and repurposed. However, maintaining joint integrity is a challenge. This paper reports a non-destructive methodology to monitor steel bolted joints. Piezoelectric ceramic patches have been surface bonded in the joint for transmission and reception of guided ultrasonic waves. Both single and multiple bolted joints have been investigated. It has been demonstrated that the variation in acoustic impedance due at the bolt interface can be discerned and calibrated with bolt torque level. The recorded reflections from interfaces are used as inputs for a newly developed imaging algorithm. The proposed method has the potential to be a reference-free and fully automated method.

Pipelines are the primary means of land transportation of oil and gas globally, and pipeline integrity is, therefore, of high importance. Failures in pipelines may occur due to internal and external stresses that produce stress concentration zones, which may cause failure by stress corrosion cracking. Early detection of stress concentration zones could facilitate the identification of potential failure sites. Conventional non-destructive testing (NDT) methods, such as magnetic flux leakage, have been used to detect defects in pipelines; however, these methods cannot be effectively used to detect zones of stress concentration. In addition, these methods require direct contact, with access to the buried pipe. Metal magnetic memory (MMM) is an emerging technology, which has the potential to characterize the stress state of underground pipelines from above ground. The present paper describes magnetic measurements performed on steel components, such as bars and tubes, which have undergone changing stress conditions. It was observed that plastic deformation resulted in the modification of measured residual magnetization in steels. In addition, an exponential decrease in signal with the distance of the sensor from the sample was observed. Results are attributed to changes in the local magnetic domain structure in the presence of stress but in the absence of an applied field.

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.

Thickness measurements using an ultrasonic contact test is a well-known nondestructive evaluation technique. However, its implementation in a robotic system with a closed-loop feedback control for artificial intelligent measurements requires precise information of positioning and force of the ultrasonic probe. In this work, we describe an ultrasonic probe developed in our lab that uses a semispherical soft membrane made from an elastomer. The aim is to develop a methodology for precise positioning and force control of a dry contact ultrasonic probe based on the ultrasonic signal information processed using sparse matrix optimization and Fourier analysis techniques. The results show that the proposed methodology makes easy to achieve a fine tuning of the probe orientation with high sensitivity to load and misalignment in order to perform accurate thickness measurements.