Lamb Wave Scattering Analysis for Interface Damage Detection between a Surface-Mounted Block and Elastic Plate.

The use of mechanic waves for assessing structural integrity is a well-known non-destructive technique (NDT). The ultrasound applied in the guided wave in particular requires significant effort in order to understand the complexities of the propagation so as to develop new methods in damage detection, in this case, knowing the interaction between the wave propagation and the geometry of the waveguides is mandatory. In the present work, the wave propagation in rectangular steel rod is presented. In this study, the section dimensions were fixed as 5 × 15 [mm], a typical element of the flexible riser structural amour commonly used in the offshore oil industry. The studies here presented were restricted to [0, 100 KHz] frequencies. This frequency interval is in the range of commercial waveguide equipment commonly applied in ducts in NDT applications. The computation of the dispersion curves is performed by using three different methodologies: (i) analytical solutions, (ii) a method that combines analytical approaches with finite element methods (SAFE), and (iii) experimental method that extracted information from the rod using laser vibrometers and piezoelectric actuators. Finally, two applications based on the dispersion curves determined in the rectangular waveguide are presented to illustrate the possibilities of the curve dispersion knowledge related to the specific geometry in the development and application linked to NDT. The first application consists on showing the possibilities of the techniques that use a fiber grating Bragg cell (FGB) to measure the wave displacement and the second application involves the simulation of pre-fissured prismatic waveguide aimed at searching to induce three characteristic acoustic events. The model was built combining the finite element method and a version of the discrete element method.

Underwater target acoustic scattering is an important aspect of underwater acoustic research. Research on the elastic scattering wave is related to the wave dispersion curves and the exit angle, but the excited condition of a Lamb wave is rarely discussed in the context of elastic plates. The energy distribution for the reflected Lamb waves of several modes when Lamb waves of other anti-symmetric modes are formed by reflection at the end face of an elastic plate is also rarely discussed. However, the research concentrating on the excitation condition of Lamb waves and mode conversion at the end face of a submerged elastic plate can be the basis for target recognition. Based on R.D. Mindlin Hamilton's principle and using an orthogonal complete feature, the frequency dispersion equation of a Lamb wave is derived for an elastic plate in a vacuum; and water, phase velocity, attenuation coefficients and group velocity dispersion curves are obtained. Analysis of the energy ratio between each of two anti-symmetric mode backward Lamb waves resulting from mode conversion when an anti-symmetric Lamb wave is incident at the end face of the plate in single mode is derived. The scattering wave of a submerged elastic plate is measured experimentally, which shows that only the incident anti-symmetric Lamb wave at the critical angle of one mode can directly excite a Lamb wave of this mode in the elastic plate, Lamb waves of other anti-symmetric modes are formed by reflection at the end face of the elastic plate. There is also no energy change between a symmetric Lamb wave and an anti-symmetric Lamb wave, even with mode conversion, if the waves are reflected at the end of the elastic plate. Combined with radiation efficiency of submerged elastic plate energy ratio between each two anti-symmetric mode backward lamb waves resulted from mode conversion when anti-symmetric lamb wave incident at the end face of plate in single mode confirmed validity of the analysis results.

As one of the most common structural forms in port engineering, the operation environment of high-pile wharf is quite harsh and complex, and its pile foundation often produces structural damage of different degrees. Until now, there is a lack of efficient, safe and economic damage detection methods. A novel and precise real-time structural damage detection (SDD) method using both finite element modelling (FEM) and 1D convolutional neural networks (CNNs) is established in this study. The results indicate that the proposed method could accurately identify the presence and location of damage in real time. The results also demonstrated that the proposed 1D CNNs based model are more sensitive to the longitudinal and lateral displacement responses of the high-pile wharf structure.

Bars are significant load-carrying components in engineering structures. In particular, L-bars are typical structural components commonly used in truss structures and have typical irregular asymmetric cross-sections. To ensure the safety of load-carrying bars, much research has been done for non-destructive testing (NDT). Ultrasonic guided waves have been widely applied in various NDT techniques for bars as a result of the long-range propagation, low attenuation, and high sensitivity to damages. Though good for inspection of ultrasonic guided waves in symmetric cross-section bar-like structures, the application in asymmetric ones lacks further research. Moreover, traditional damage detection in bars using ultrasonic guided waves usually depends on a single-mode at a lower frequency with lower sensitivity and accuracy. To make full use of all frequencies and modes, a multi-mode characteristic-based damage detection method is presented with the sum of multiple signals (SoM) strategy for L-bars with asymmetric cross-section. To control the desired mode in multi-mode ultrasonic guided waves, excitation optimization and weighted gathering are carried out by the analysis of the semi-analytical finite element (SAFE) method and the normal mode expansion (NME) method. An L-bar example with the asymmetric cross-section of 35 mm × 20 mm × 3 mm is used to specialize the proposed method, and some finite element (FE) models have been simulated to validate the mode control. In addition, one PZT is applied as a contrast in order to validate the multielement mode control. Then, more FE simulations experiments for damage detection have been performed to validate the damage detection method and verify the improvement in detection accuracy and damage sensitivity.

Damage detection in beams using vibratory power estimated from the measured accelerations

In order to identify the effect of crack depth and opening on the girder, finite element method (FEM) has been used in this paper. In FE analysis, six nodded two dimensional plane elements (PLANE-2) are considered. Each node has two degree of freedom such as UX and UY. For the plane elements, a plane stress width/thickness option is chosen. For analytical model of crack of the concrete bridge girder, crack opening was increased from 0.2 mm to 1mm at an interval 0.2 mm and crack depth also increased from 30 mm to 150 mm at an interval 30 mm. The models were discreatized by a triangular mesh and convergence test was executed to obtain satisfactory results from the Plane-2 element. From the numerical result, it is seen that the principal stress become a higher with increased the crack depth and also crack opening with respect to load increasing. But the crack depth at 90 mm and crack opening at 0.6 mm, it has more effect on the girder because the stress concentration is higher than other crack depth and opening.

Filament wound pressure vessels have been extensively used in industry and engineering. The existing damage detection and health monitoring methods for these vessels, such as X-ray and ultrasonic scan, can not meet the requirement of online damage detection; moreover optical grating fibre can only sense the local damage, but not the damage far away from the location of sensors. Vibration-based damage detection methods have the potential to meet such requirements. There methods are based on the fact that damages in a structure results in a change in structural dynamic characteristics. A damage detection method based on a residual associated with output-only subspace-based modal identification and global or focused chi^2-tests built on that residual has been proposed and successfully experimented on a variety of test cases. The purpose of this work is to describe the damage detection method and apply this method to assess the composite structure filled with fluid. The results of identification and damage detection will be presented.

Multivariate statistical analysis for early damage detection

Square steel tube, which is widely used in civil engineering, can suffer from a wide variety of damages and aging defects, thus its nondestructive testing (NDT) has attracted wide attention. This work proposes an ultrasonic guided wave (UGW)-based damage detection method for square steel tubes using structure symmetry. Firstly, the dispersion characteristics of square steel tubes are obtained using the semi-analytical finite element (SAFE) method, after which the optimal guided wave modes for damage located on the long and short edges of the steel tube are selected by modal analysis. Then, using the symmetry of the square steel tube’s section, the symmetric layout scheme of the transmitters and the receivers is designed; on this basis, a signal processing strategy for damage detection is proposed by subtracting the receiving signals obtained from symmetric positions. Finally, the effectiveness of the proposed damage detection method is verified by numerical simulations and laboratory experiments. The results show that the proposed method has good inspection accuracy for crack and hole damages on both the long and short edges of square steel tube because the dispersion effect and clutters can be reduced utilizing structure symmetry. It is worth mentioning that the inspection effect for corner holes can be enhanced by modifying the position of the receivers.

A constant challenge for the design and operation of CFRP primary structures is their sensitivity towards impact loading. This can lead to the formation of externally invisible delaminations which endanger the structural integrity. In practice, this circumstance is encountered with elaborate inspections or conservative design. Structural Heath Monitoring (SHM) systems offer the potential for permanent monitoring and represent an alternative approach that has drawn more attention in the last decade. The biggest barriers to market entry for this technology are system costs and reliability. This study is dedicated to these two points with the development of a low-cost system with which representative acoustic emission sources can be located reliably in a complex CFRP structure. The implementation is carried out using acoustic emission analysis, which represents a promising solution for the integral monitoring of primary structures. It is based on the detection of acoustic waves that are released during crack initiation and growth and propagate over large areas in thin-walled structures as Lamb waves. The challenges of source localization in thin-walled CFRP structures lie in the consideration of wave dispersion, anisotropic material properties, variable component geometry and interfaces. In this thesis, this complexity is captured by training a neural network. For this purpose, artificial sources are used which imitate acoustic emissions of typical damaging events in the material in frequency and mode content. The demonstrating component is an omega profile equipped with a network of piezoelectric sensors that is designed for reliable localization within a defined window. Signal processing takes place on a single-board computer which, together with a digital oscilloscope, completes the measurement chain. The system represents a modular, low-cost approach that can be transferred to other applications by adapting the hardware and training.

With the rapid growth of the demand for structural health monitoring in the aerospace field, especially under complex and changeable structural and damage cases, damage detection methods are facing the challenges of insufficient detection accuracy. To solve this problem, this paper proposes a detection method of damage location of composite stiffened plates based on Lamb wave and multi-task deep learning. In this paper, experiments are carried out on a composite stiffened plate with two stiffeners. Firstly, the damage monitoring area is divided into four sub-areas, each sub-area is further subdivided into nine grids, and five damage signals with different damage sizes are collected at the center of each grid. Through the differential operation between the baseline signal and the damaged signal, the damage scattering signal is extracted as the input of the deep learning model. The model training is only based on the data of the first sub-area, and its generalization ability is evaluated through two test sets: one test set contains the random signals of the non-center location of the first sub-area, and the other test set comes from the random signals of the other three sub-areas. Then, the Inception module and BiLSTM is used to extract the multi-level and multi-scale features of the damage signal, which effectively captures the features of the signal, thus significantly improving the accuracy of damage location. Finally, two output branches are designed to realize the multi-task learning target model, which can predict the x and y coordinates of the damage location at the same time. The experimental results show that this method can accurately identify the damage at any location in the monitoring area. In the tests of different sub-areas, the model still shows good robustness and generalization ability, showing a certain application potential.

A damage detection method using BP neural network based on a novel damage index, the correlation characteristic of the acceleration response, is proposed, and is evaluated through the FEM simulation and experiment verification. On the basis of achievements in existence, the feasibility of using the correlation characteristic as damage index is validated theoretically. The damage detection for a simple-supported beam using the proposed method was FEM simulated. The results showed that the trained BP neural network can correctly detect the location and extent of damages in both single damage case and multi-damage case. A model test of a reinforced concrete simple-supported beam was performed to verify the validity and efficiency of the damage detection method. From the results of the model test, it is shown that the trained BP neural network can correctly locate the damage mostly detect the extent of damage. A conclusion is given that the novel damage detection method using the correlation characteristic of the acceleration response as damage index is feasible and efficient.

Chapter 10 - Structural health monitoring and nondestructive evaluation applications of the stress, vibration, and wave analysis in aerospace composites

This paper deals with damage detection using active Lamb waves. The wavelet transform and empirical mode decomposition methods are discussed for measuring the Lamb wave's arrival time of the group velocity. An experimental system to diagnose the damage in the composite plate is developed. A method to optimize this system is also given for practical applications of active Lamb waves, which involve optimal arrangement of the piezoelectric elements to produce single mode Lamb waves. In the paper, the single mode Lamb wave means that there exists no overlapping among different Lamb wave modes and the original Lamb wave signal with the boundary reflection signals. Based on this optimized PZT arrangement method, five damage localizations on different plates are completed and the results using wavelet transform and empirical mode decomposition methods are compared.

Structural health monitoring (SHM) plays a significant role in terms of fatigue life and damage accumulation prognostics. SHM for structures with complex geometry are much more practical in engineering applications. In this paper, complex aluminium alloy structures with “U” shape section were evaluated in terms of both finite element method (FEM)- and experiment-based Lamb wave analysis for the purpose of damage detection and identification. In the FEM-based analysis, three-dimensional finite element model was established to simulate the propagation behavior of Lamb wave in the structures. On the other hand, in the experiments, piezoelectric (PZT) wafers, functioning as both actuator and sensor, were used to generate Lamb waves propagating in the structures and collect the Lamb wave signals from the complex structures. Quantitative relationship between crack location and the reflection coefficient was constructed by taking advantage of continuous wavelet transform (CWT) and Hilbert transform (HT), which are based on the collected Lamb wave signals. Furthermore, the differences between simulated and experimental results in respect of crack severity evaluation and the reasons were discussed.