This PDF file contains the front matter associated with SPIE Proceedings Volume 11380 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Shape morphing is one of the most appealing applications of adaptive structures. Among the various means of achieving shape morphing, origami-inspired folding is particularly advantageous, because folding is a powerful approach to induce three-dimensional and sophisticated shape changes. However, attaining large-amplitude folding is still a challenge in origami engineering. While promising, the use of active materials as a folding activation strategy is limited due to the constant voltage supply that is required to maintain the desired configuration of the structure. One possible solution is to embed bi-stability into the structure. Bi-stability can play two significant roles here: first, it can significantly reduce the actuation requirement to induce shape morphing, and second, it can maintain the shape change without demanding sustained energy supply. In a previous study by the authors, a unique shape morphing (or self-folding) method using harmonic excitation has been proposed for a bi-stable water-bomb base. However, this approach has some drawbacks because the nonlinear dynamic behaviors of origami are quite sensitive to different design parameters, such as initial conditions, excitation parameters, and inaccuracies in manufacturing. In this study, via numerical simulations, we show that by harnessing the intra-well resonance of the water-bomb structure and incorporating a relatively simple feedback control strategy, one can achieve a rapid and robust morphing using relatively low actuation magnitude. The results of this study can lay the foundation of a new category of morphing origami mechanisms with efficient and reliable embedded actuation.

Vibration is an available source of energy to supply electrical power demand of the freight wagons as it is one the most important challenges in railway engineering. Here we propose an efficient bistable mechanism with linear power take-off and nonlinear stiffness for energy harvesting of freight wagon vibrations. Design parameters of the bitable systems is optimized by genetic algorithm (GA) and simulated annealing (SA) to extract maximum power. It is shown that remarkable enhancement can be achieved in comparison with conventional linear energy harvesters. The reason for this enhancement is harmonic oscillation between stable equilibrium points of the system which is very well matched with the nature of random excitation exerted by the rail irregularities.

Location and identification of subterranean infrastructure is crucial for managing and maintaining urban infrastructure and utility, and locating subsurface hazards. Low-frequency oscillating magnetic fields suffer less attenuation due to propagating media than ground penetrating radar. Here, electronically-geared, rotating neodymium magnets project oscillating magnetic fields which are manipulated to provide object identification from rapid analysis of dynamic magnetometer data. Ferromagnetic materials interact directly with the rotating magnetic field. Eddy currents, which induce a counter-propagating magnetic field, are generated in conductive, non-ferromagnetic materials. Two applications are highlighted by preliminary experiments: discrimination between copper, aluminum and steel pipes, and improved detection of buried explosive devices.

Cracking of concrete structures such as highway bridges is commonly observed in the U.S. and around the world, which can be attributed to one or many damage mechanisms. The inability of visual inspection for determining crack depth has a detrimental effect on its reliability. With the use of nondestructive evaluation (NDE) techniques such as microwave and radar sensors, subsurface sensing can be achieved in concrete structures. The objective of this paper is to investigate the performance of a commercially available ground penetrating radar (GPR) sensor on artificially-cracked concrete panels in the laboratory and real concrete structures with cracks in the field. Three artificially-cracked concrete panels (30x30x4 cm³) with different crack dimensions were manufactured with one pristine concrete panel without any crack as the control sample. Three different crack dimensions were introduced in concrete panels, including panel CNC with a 10x0.5x0.5 cm³ crack, panel CNCD with a 10x0.5x1.5 cm³ crack, panel CNCW with a 10x2x0.5 cm³ crack. An L-band GPR sensor (carrier frequency = 1.6GHz) was used in all experimental measurements. From our result, it was found that the use of a 1.6GHz GPR sensor can detect the presence of an artificial crack, as well as detecting crack dimensions (e.g., width, depth). Empirical models were developed from the B-scan GPR images for crack quantification

Additive manufacturing systems are becoming progressively more capable of printing geometrically complex structures from a wide range of materials. To ensure the print quality of these materials over the duration of the build process, there is a need for in-situ diagnostics which can provide real-time information during fabrication, as well as information that can be processed after print completion. Here we present an in-situ radio frequency diagnostic for liquid metal jetting, which employs a millimeter-wave waveguide device to monitor the impedance changes caused by moving droplets. Experimental results indicate promise for the characterization of size, timing, and motion of metal droplets in an advanced manufacturing system.

We propose a model assisted method to identify damage types and severity based on mode converted wave strength. Machine learning techniques are employed to develop classification models complemented by the finite element simulation models. Finite element simulation models provide the training data for various cases of damage and severity involving common types of damages in composites. Damage classification models are based on mode conversion strength versus frequency curves of participating four wave modes. For damage recognition and classification, a multi-layer Convoluted Neural Network (CNN) has been trained using the back-propagation paradigm on the generated dataset.

The main purpose of Structural Health Monitoring (SHM) is to determine the integrity of a structure or component during their operational life. This is done, in order to schedule proper and effective actions to remove or mitigate any damage/defect that could affect the integrity of the system. Composite materials, widely used in aerospace applications, are characterized by low out-of-plane mechanical properties. An impulsive event such as low velocity impact (LVI) on this class of materials could cause barely visible impact damage (BVID) that is not detectable by a simple visual inspection, reducing the strength of the structure. This research work proposes an improved damage detection technique overcoming the limitations of the methods presented in literature (knowledge of the mechanical properties, the direction dependency of the wave speed, the attenuation and dispersion effects). The damage detection and localization technique is based on an active approach, using an array of sparse piezo sensors. One transducer is used as an acoustic actuator, inducing ultrasonic waves which propagate through the component, and the others are used as receiving sensors. The routine is based on the signal power of the response in the sensor’s location and their interpolation by the radial basis function, from which the location of the damage is determined. The experimental campaign was performed on a simple carbon fiber reinforced plate fitted with eight piezo transducers, with multiple configurations of sending-receiving pairs. Good results were obtained with a good level of accuracy in damage localization estimation.

In this research, we report a new fault identification algorithm utilizing multi-objective optimization. Fault identification problem is commonly under-determined, as measurement information may not be sufficient to facilitate a direct inversion. We formulate an optimization problem, aiming at minimizing the discrepancy between model prediction and measurement. This yields multiple possible fault scenarios, which lays down foundation for further inspection.

For performance improvement and failure prediction, numerical models are necessary to describe the modal behavior of GFRP rotors as a function of their damage state and rotational speed. Model validation requires in-process measurements. We show that the diffraction grating method enables simultaneous strain and tilt measurements with precisions <20 με and <4’’ and a spatial resolution <5 mm at surface speeds >250 m/s. An in-situ determination of the damage state by strain field analysis and vibration measurements are performed on a moving rotor and compared with the results of piezoelectric strain gauges, a vibrometer and a distance sensor.

This paper presents solutions for guided wave motion (Lamb and shear horizontal) due to tensile and shear cracks in an isotropic plate using elastodynamic reciprocity. Finite-length through-thickness cracks are considered via Huygens’ principle by representing them as a superposition of point cracks. Far-field solutions are then derived in order to simplify the results and facilitate a direct comparison of guided mode excitability due to various cracking modes. Relatively short- and long-length line cracking are compared to point cracking for the fundamental modes S₀, A₀, and SH₀. It is shown that the A₀ modal response is the most sensitive to crack length, with S₀ and SH₀ being relatively insensitive. Additionally, the radiation patterns of S₀, A₀, and SH₀ are relatively insensitive to crack length. The results have applications in acoustic emission monitoring of plate-like structures, where modal responses may be used to characterize crack growth.

Impacts between birds and aircraft, referred to as bird strikes, are remarkably common and present a major issue with flight safety as a single incident can cause catastrophic damage. The Federal Aviation Administration requires that aircraft must withstand these impacts through testing using euthanized birds. This process is unethical, inefficient, costly and unreliable. Previous research has validated gelatin as a replacement material and hydrodynamic modeling as a computational approach. A great variation in results remains due to a lack of standardization in the experimental and computational testing methodologies. Authorities agree that a standard approach will better facilitate testing and reduce the threat that bird strikes pose. We hypothesized that further testing of gelatin substitutes and numerical approaches using advanced processing would facilitate impactful results and aid in introducing a new global bird strike testing standard. High-speed impacts on a Hopkinson bar and dynamic impacts using a pendulum serve to identify a valid setup and design that best represents impact behavior. Smoothed particle hydrodynamics (SPH) is used to create a numerical model representing the fluid nature of the collision. By performing various impacts through various techniques, we hypothesize that the numerical SPH model will validate the material behavior by yielding accurate force-time profiles. Implementing this model will allow for reliable prediction of material response and damage evolution following bird strike impacts.

DIC-Wavelet technique for vibration based structural damage identification in dragonfly wing structure is reported. A bio-mimicked dragonfly wing, stiffened and unstiffened plate made of MWCNT-PP nanocomposite wing skin and Carbon-fibre epoxy composite stiffener are developed. Modal frequencies and vibration mode shapes of intact samples are obtained using well known Digital image correlation technique. Artificial cracks are created in plates and wings at stigma and nodus. Wavelet analysis is applied on displacement data obtained at discretized wing surface using DIC technique. Symlet function of order 4 is selected as mother wavelet function. The spikes in amplitude of wavelet coefficients corresponds to the damage region. Effect of scaling function in wavelet transform is studied for efficient identification of damages. The study indicates that the proposed DIC-Wavelet technique is efficient in predicting the damage zones in plates and wings.

Guided wave tomography is a very promising technique for evaluating remaining strength and durability of damaged structures. This paper evaluates the accuracy of three guided wave tomography algorithms, straight ray tomography, bent ray tomography, and full waveform inversion (FWI), to detect defects like corrosion in numerical simulations. The numerical simulations are conducted in a 1000 × 1000 × 10 mm aluminum plate with various defects. By comparing the numerical results of the three algorithms, it is demonstrated that guided wave tomography based on FWI has the highest resolution for thickness inversion. The presented study may provide a useful insight to choose appropriate guided wave tomography algorithms for nondestructive testing of plate-like structures.

Dielectric Elastomers (DEs) represent a class of soft electro-mechanical transducers, which is promising compared to conventional actuation technologies due to features such as lightweight, high energy efficiency, and low operational noise. Despite several prototypes have been proposed in the recent literature, only very few of them have been commercialized yet. To further DE technology towards real-life applications, it is of great importance to quantify the long-term performance of theses transducers in terms of electrical and mechanical fatigue under controllable environmental conditions. In order to investigate these properties, this paper introduces a modular electro-mechanical testing device that is designed in order to determine the long-term and fatigue characteristics of rectangular shaped DE actuator (DEA) membranes working under in-plane loading conditions. Each module permits to arbitrarily program mechanical stroke and applied voltage, and also enables simultaneous testing of five samples. Quantities of measurement are force and current. The modules are placed inside of a climate chamber which provides testing environments with constant temperature and humidity. To ensure uninterrupted 24/7-operation, the setup provides safety-equipment with remote control and remote monitoring. First test results are presented in this work.

Electromechanical behavior of carbon-fiber-reinforced plastics (CFRPs) was investigated by monitoring the electrical resistance changes with respect to mechanical loading to utilize its self-sensing capability for real-time non-destructive evaluation (NDE). Electrical resistance changed as mechanical deformations occurred in CFRPs. CFRP consists of polymer matrix and carbon fiber consisting of several thousands of carbon fiber monofilaments. The intrinsic piezoresistive behavior of a carbon fiber monofilament was characterized by an increase in electrical resistance when subjected to tensile elongation. A carbon fiber tow, essentially a bundle of monofilaments, also displayed a similar electromechanical behavior. In addition, the electrical resistance was affected by the interaction between adjacent tows and plies, known as “inter-tow” and “inter-ply” interactions, respectively. These interactions can be modeled as electrically equivalent circuits with variable electrical resistors. The developed model aids in the design of self-sensing CFRPs, which holds real-time NDE ability. Variable electrical resistors were parameterized by both empirical results and numerical analysis, decoupling each factor containing the stacking sequence as well as orientation of carbon fiber plies. The proof-of-concept of self-sensing CFRP was demonstrated using a 3D-printed miniaturized bridge. CFRP strips were attached under the bridge, and electrical resistances were monitored real-time with respect to the deflection. The acquired resistance changes were converted using the in-house developed algorithm, and deflections were calculated. It was shown that the proposed method can detect both the locations and magnitudes of deflections in the bridge real-time even when moving loads are applied.

Ultrasonic testing and acoustic emission are acknowledged non-destructive testing methods for pipeline inspection; however, attenuation is a significant issue in long-range structures such as pipelines. A gradient-index metamaterial lens composed of subbed unit cells is proposed to address the energy loss by amplifying the signal through wave focusing. A prototype is tested actively (ultrasonic testing) and passively (acoustic emission) in the laboratory, and significant amplification of the signal is observed. The reciprocity between the two methods is validated.

Differential settlement of underground pipelines is one of the major causes responsible for pipeline failures in the U.S. Due to the invisibility of underground pipeline deformation and the requirement for long-range monitoring of underground pipelines, most of the underground pipeline motions are currently undetected. In this paper, a novel long-range sensing technique using fiber optic sensors is proposed for the structural health monitoring (SHM) the deformation and motion of underground pipelines. Two laboratory 304.8x1.7cm HDPE (high-density polyethylene) pipe specimens were manufactured and tested under four-point bending for damage detection. Single mode optical fibers (10.4 ± 0.8 μm) were installed on the surface of these two HDPE pipes for distributed sensing. Four-point bending test was carried out on two HDPE pipes in the range of 445 N to 2670 N at an increment of 445 N. A BOTDR (Brillouin Optical Time Domain Reflectometer) system was applied in collecting distributed strain measurements (spatial resolution =1m, sampling interval =0.5m) from the two HDPE pipes. Fourteen conventional coil-type strain gauges (gauge factor: 2) were also instrumented on each HDPE pipe for validation purpose. From our laboratory results, it was found that the longitudinal BOTDR strain measurements near the neutral axis of the HDPE pipes can be used for detecting pipe rotation. It was also found that the longitudinal BOTDR strains at the bottom of the pipes can be used to detect pipe bending and damage detection.

The article reports a study carried out on metallic samples extracted from a cladded pipe (API5 X65 steel-Inconel 825 alloy) for industrial use in the transport of hydrocarbons, which were subjected to a solubilization treatment at 1200°C and a subsequently aging treatment at 650°C for different times in order to promote microstructural changes in both materials. To monitor these microstructural changes due to the aging process, the thermoelectric potential (TEP) nondestructive technique was used. In addition, microhardness tests were carried out on the metallic materials and micrographs were obtained by means of an optical microscope (OM) images.

Despite having a vast structural application, Composites are not exempt from limitations and are also susceptible to deforming during operations. Therefore, it is essential to develop in-situ monitoring systems and sensors to avoid their catastrophic failure, especially for dynamic failure. So, the objective of this study was to investigate and monitor the dynamic behavior of composites in real-time using a Nylon/Ag fiber sensor under the low-velocity impact. Nylon/Ag fiber sensors were integrated at different directions and positions within the composite specimens which were tested under low-velocity impact on the Taylor cannon gun apparatus. Three sets of tests were performed at 2.5m/s, 3m/s and 6.5m/s respectively to demonstrate the detection signal of the fiber sensors when there is no damage, some micro damage and overall breakage of the sample. The results confirmed that each Nylon/Ag fiber sensor showed a specific resistance behavior in all three specimens because of their respective position and direction and detected the deformation, damage initiation, damage propagation, type of damage and quantification of the amount of damage induced.

Monitoring and diagnosis of civil structures has become a popular topic in the last years, especially through the use of non-invasive tests and techniques. Moreover, the spread of operational modal analysis, that exploit ambient excitations of structures to estimate their modal parameters, allowed to reduce the costs associated to the dynamic identification. In this paper, a technique for the diagnosis of common civil structures, such as residential buildings or warehouses, is presented in order to identify local stiffness decreases that can potentially be associated to structural failures. The technique has been tested on a real warehouse built in 1960 and the results have been analyzed demonstrating the effectiveness of the methodology.

Modal analysis based structural health monitoring (SHM) is required now more than ever due to many factors such as aging infrastructure, loading incidents likely earthquakes, over loading etc. Although the continuous monitoring of structures is a full-fledged commercial sector, its high cost makes it infeasible for large structures as the number of sensors required is large. Accelerometers, widely used as sensors in SHM, in addition to high cost, possess some other challenges such as damage vulnerability in environmental and operational conditions. In this research, low cost lead-zirconate-zitanate (PZT) sensors are proposed as replacement of costly and fragile accelerometers as sensors for SHM. PZT patches, which cost less than one-tenth of the accelerometers, can also be embedded in the reinforced concrete structures to protect from the harsh operational conditions. In this paper, PZT patches are studied by technique of experimental modal analysis (EMA) on a steel beam specimen and the results are compared with the traditionally used accelerometers. Single input single output (SISO) approach is adopted for EMA of the rectangular steel beam. PZT sensors are able to capture modal data in terms of natural frequencies and mode shapes in good agreement with accelerometer. The fundamental natural frequency of the beam is obtained with the error of less than 1 % as compared to the accelerometer. The signal to noise ratio is of same order as accelerometer. The strain mode shape from the PZT sensors is well correlated to displacement mode shapes from the accelerometer by a modal assurance criteria (MAC) values greater than 0.9 for observed experimentally.

The use of additively manufactured metal parts has increased dramatically in the past few years. This has drawn considerable attention to the as-built mechanical properties of these parts and their ultimate durability. Additive manufactured parts have a wider variation in properties than parts made with classical techniques. These variations are dependent on several parameters including the specific additive manufacturing technique used, the material, build variables, part orientation during the build, and secondary operations required to remove support structures required for the additive build. Non-destructively verifying the quality of these parts is especially important to aerospace, automotive and defense applications where failure can be catastrophic. This paper describes an ongoing research project that utilizes nondestructive techniques to detect defects, damage, and other variations of mechanical properties in additively manufactured metal parts that could reduce the quality of the part. The dynamic properties (frequencies and modes of vibration) provide a characteristic “signature” for all parts. If a part has any significant variations in elastic modulus, density, dimensions, microstructure, internal flaws or defects, the vibrational “signature” will change, and this variation can be detected. The monitoring process used combines Laser Doppler Vibrometry with acoustical resonance spectroscopy. Multiple spectra measured for different excitation and testing conditions are combined into a single spectrum, which is then compared with finite element analysis predictions. Any variation in the spectrum pattern is an indicator of damage. This non-destructive technique was used to successfully detect damage in a series of metal parts manufactured with predefined defects using a Selective Laser Melting (SLM) technique with two 400-watt lasers to microweld the metal powders at 30-micron layers.

With increasing requirements on the efficiency of aircraft engines and the application of advanced materials, the non-contact evaluation of the deformation and the vibration behaviour is of increasing interest. For optical deformation measurements at high surface speeds, motion blur becomes a critical uncertainty factor. A full-field measurement method for rotating components is proposed, in which in-situ high-resolution images can be acquired for digital image correlation. The measurements are carried out through an optical derotator, which allows rotational motion blur to be largely avoided. Optical image distortions due to the use of a dove-prism are considered and the effects are attempted to be minimized by an angle-precise triggering of the digital single-lens reflex camera. The measured deformations on a generic bladed disc under different rotational speeds up to 2500 RPM show a good correlation compared both to 3D digital image correlation measurements from ARAMIS as well as to numerical predictions. The results demonstrate that the approach is sound for measuring the deformation, whereas measurements at the circumference reveal the image distortion effects, posing that further steps are necessary for an investigation of the vibration behavior.

Fiber reinforced polymers (FRP) strengthening has been demonstrated as an effective method to reinforce or repair the structural elements in the application of civil engineering. One issue that affects the effectiveness of FRP bonded system is the interfacial integrity between FRP and bonded substrate. The interfacial defect can cause the deterioration of the performance of strengthened/repaired structures, which should be identified as early as possible. Compared with conventional non-destructive techniques (NDTs), image acquisition method, such as high-speed camera, has received increasing attention due to the advantages of its non-sensor/wiring requirements. Coupled with proper video processing techniques, the high-speed camera has been reported as an effective tool in the interfacial defect detection for FRP bonded system. Moreover, the accuracy of results from high-speed camera is sensitive to the excitation resources applied on the FRP bonded system, since the vibration response of FRP varies under different excitation methods. In this research, three typical excitation methods for FRP bonded system, i.e. mechanical impact excitation, air pressure excitation and acoustic excitation, were tested to evaluate their effects on the detection accuracy using high-speed camera in FRP bonded system. The findings provide practical recommendations on the selection of proper excitation methods for the applications of high-speed cameras in the defect detection of FRP bonded system.

Ultrasonic sensors have been proposed for monitoring nuclear fuel performance during transient irradiation tests. A specific need is to monitor strain or deformation of the fuel rods during irradiation. However, challenges associated with designing sensors that can operate under typical in-core conditions while providing the necessary sensitivity have limited their application. This paper describes ultrasonic sensor concepts for measurements during transient irradiation tests and results of laboratory tests to quantify their performance. Challenges associated with designing sensors for in-core deployment and potential solutions are also discussed.

Structural health monitoring (SHM) of components is becoming an important part of maintenance and component evaluation throughout many engineering industries. Evaluation of defects and damage plays an important role in reducing maintenance and testing costs, and thus has become an important part of the costs of businesses. In this work a nonlinear ultrasound subtraction techniques is proposed which looks to evaluate barely visible impact damage (BVID) in a composite structure using a sparse array of piezoelectric transducers. Evaluation of the elastic responses of composite structures can become difficult due to the complexity of these types of structures, with variations is attenuation, dispersion and fibre orientation. The method proposed looks to simplify damage detection without the calculation of time-of-arrival (TOA), dispersion curves and the frequency dependence of damage. The method relies on the excitation of the structure with three separate signals at both 0° and 180° degree phases. The three signals used are a single frequency, swept frequency and combination of both. The novelty of the method relies on a delay which is added between the signals, this delay is used to promote nonlinear ultrasonic interactions within the material. A hybrid modulation subtraction (HMS) method is then used to filter out linear components and retain the nonlinear modulated components in the signal. A sparse array of transducers and sensors are used to investigate a region with barely visible impact damage. The method does not rely on the a priori knowledge of wave velocity or the dispersion curves. The results show that it is possible to identify the defect region using the modulated nonlinear responses of the structure.

The practical application of MEMS sensors in the nondestructive testing of equipment is presented in the paper. The prospects of application and research are described. Among the existing methods of nondestructive testing (magnetic, thermal, eddy current, ultrasonic, radiation, visual, optical, acoustic emission control), vibration diagnostics is a complementary method for evaluating the functioning of mechanical systems. Monitoring and control of the vibration characteristics of equipment at the site of operation is necessary for ensuring the safe operation of complex engineering structures and facilities. When applying the method of vibration diagnostics at frequencies from 1 Hz to 30 Hz, the method of free and forced oscillations is used. The method of free and forced oscillations is applied to determine the natural resonant frequencies of the investigated equipment and damping decrement of this equipment at resonant frequencies. It is known that the frequency of seismic events from 3 to 12 degrees on the Medvedev–Sponheuer–Karnik scale (MSK 64) is in the range from 1 Hz to 30 Hz. This method has successfully proven itself in the testing of equipment weighing up to 100 kg. Important vibrational characteristics of complex engineering facilities and structures are their natural frequencies and damping decrement. The natural frequencies and damping decrement of the equipment can be determined by the free oscillation method. The free oscillation method (FOM) is to analyze the damping acoustic oscillations excited in the test equipment. The method has successfully proven itself in the testing of equipment that does not have a rigid attachment to the building structure (floor, wall, ceiling), does not require expensive materials for surface preparation. For a long time, FOM was mainly used in fault analyzers for layered media. Until recently, the available acoustic-to-electrical signal transducers, analog spectral analyzers, indicators of measurement results did not provide the necessary accuracy of measurements and did not allow to distinguish a stable informative component in the complex signal obtained by the transducing of the damped wave. The development of modern vibration sensor technologies, in particular, based on Micro-Electro Mechanical Systems (MEMS), has made it possible to use FOM with greater efficiency. Free oscillations were created by means of a basket with weights or by tension through a system of steel cables to a dynamometer. Forced oscillations (sinusoidal mechanical oscillations) were created by the portable generator BM-100, which excited sinusoidal mechanical oscillations in the specified coordinate areas of the equipment. Measurements of the accelerations of the specified coordinate areas of the equipment weighting up to 100 kg were performed by the MEMS sensor with the software-technical complex developed in the NSC “Institute of Metrology”. The processing of the obtained information was in determining the resonant frequencies, the relative power levels of the equipment oscillations, and their corresponding damping decrements. The prospective areas of application of accelerometers, developed on the basis of MEMS technology, are the works on the study and calculation of vibration state of systems of main steam lines of turbine-generators with determination of measures for reduction of vibration; use in systems of vibration diagnostics at nondestructive testing.

The present study investigates the influence of degradation effects due to natural aging of a pine wood by using acoustic birefringence measurements. In the present study, the acoustic anisotropy parameter for aged and un-aged Mexican pine (Pinus strobus) wood was calculated by the ultrasonic emission-transmission technique. The experimental measurements were carried out using a shear wave ultrasonic transducer with a central frequency of 0.5MHz. Ultrasonic velocity data and scanning electron microscopy (SEM) were performed, establishing a direct correlation with the shear wave velocity and the acoustic anisotropy parameter developed on the naturally aged and un-aged wood.

This study presents a structural health monitoring (SHM) method for self-sensing CFRPs based on the “probabilistic sensing cloud” with the aim of minimizing the number of electrodes. Electrical resistances measured within various electrode pairs provide the information on potential damaged areas. Subsequently, the most overlapped probabilistic clouds localize the damaged location, which was verified by the experimental results. This technique was optimized by investigating the inter-electrode distances, electrical current density prediction using finite element analysis. The probabilistic sensing cloud method yields improved SHM performance and efficiency for CFRPs through electrode optimization and reduction in data complexity.

Adhesively bonded composites have been widely used in aerospace engineering, renewable energies, and automotive industries. However, the potential weak bonding of the composite structures, which exhibits a low cohesion interface between the adhesive and the composite substrate, greatly threatens the reliability of these structures. The occurrence of weak bonding has yet to be well understood and has posed new challenges for the evaluation of weak bonding in composite structures. Ultrasonic Lamb waves have been shown useful for nondestructive evaluation (NDE) due to their ability to propagate a long distance with less energy loss and their sensitivity to small defects. Among various ultrasonic transducers, air-coupled transducers (ACT) eliminate the need for couplant/adhesive and provide a noncontact actuation method. In this study, a hybrid noncontact system was constructed using an ACT for actuation and a scanning laser Doppler vibrometer (SLDV) for sensing. The ACT provided a narrowband wave actuation, while SLDV provided high-quality wavefield signals for damage detection and evaluation. An adhesively bonded composite structure containing good and weak bond quality areas was manufactured using simulated contamination. Then the composite bond quality inspection was conducted using the ACT-SLDV system. To validate the ACT Lamb wave inspection, a second noncontact inspection by a pulsed laser-SLDV method was carried out.

The focus of this paper will be on the challenges and opportunities posed by use of wave active sensors for structural health monitoring of metamaterial as different from that of the metallic structures. Metamaterial exhibits application prospects in vibration control, wave manipulation and noise reduction due to their unique dynamic properties. Metamaterial has great potential in structural health monitoring and non-destructive testing. This paper presents modeling, analysis techniques and experiment of for Acoustic metamaterial Structure for knowing waves. For a unit cell of an infinite Acoustic metamaterial Structure, governing equations are derived using the extended Hamilton principle. The concepts of negative effective mass and how the spring-mass-damper subsystems create a stopband are explained in detail. Numerical simulations reveal that the actual working mechanism of the proposed acoustic metamaterial structure is based on the concept of conventional mechanical vibration absorbers. It uses the incoming wave in the structure to resonate the integrated mass-damper absorbers to vibrate in their optical mode at frequencies close to but above their local resonance frequencies to create shear forces and bending moments to straighten the panel and stop the wave propagation. And the stopband signal shows the structure characteristic. Moreover, It shows that metamaterial can be use in health monitoring and non-destructive testing.

Rolling element bearings perform an essential role in most rotating machinery. Bearing fault diagnosis and prognosis can detect degradation to bearing performance, preventing the costs of unexpeceted system failure. Acoustic Emission (AE) introduces high sensitivity, early and rapid detection of cracking, and real time monitoring that can provide an alarm once cracking is noticed. This paper discusses the nondestructive monitoring of crack growth in rolling element bearings in a marine environment and the determination of acoustic emission parameters which indicate crack initiation and propagation. The paper’s intellectual merit lies in the signal alarm developed from an AE data pattern recognition method, and the specially made rotating machinery test bed that simulates a bearing used on board a ship. Four rolling element bearings were tested in the test bed at various loads and rotation cycles. All AE data was clustered using k-means unsupervised method, and the lowest correlated features were selected for pattern recognition. Useful AE parameters for classifying crack initiation and propagation were determined. Acoustic emission proved to be suitable for remote monitoring of bearing degradation. With the use of signal alarms based upon the clustering method and parameters discussed, one can be notified when a crack has been initiated and is propagating. This will allow the user to avoid a costly unexpected system failure and plan to perform a less costly bearing replacement.

Quality assurance and structural integrity evaluation are the crucial parts of the successful design and service of additively manufactured (AM) components. Discontinuities and flaws in AM parts can affect the mechanical properties of a component during manufacturing and service. It is very important to identify the discontinuities in AM parts in terms of location, size, and geometrical properties using nondestructive testing (NDT) techniques. Existing research in both mechanical testing and nondestructive evaluation involves developing methods for characterizing and inspecting AM components as the use of such materials continues to rise. Although there exist relatively mature ultrasonic inspection techniques for defect detection, AM polymer components face the challenge of considerable internal inhomogeneities caused by the design and printing strategies. It has been shown that the ultrasonic signals are very sensitive to the material inhomogeneities, consequently the reflection/diffractions from the defects will be significantly influenced and defect detection will be very challenging. This work aims to present the potentials and challenges in ultrasonic detection of defects in polymer AM parts. Air-coupled ultrasonic tests to be demonstrated and followed by results and discussions. The role of porosity on detectability in the ultrasonic NDT tests is described and a possible way for attenuation assessment is demonstrated. Finally, the effect of AM part inhomogeneities on detection probability of seeded defects with different sizes and locations in AM parts is presented.