Baseline free structural health monitoring using modified time reversal method and wavelet spectral finite element models

The Lamb wave based, non-contact damage detection techniques are developed using the Modified Time Reversal (MTR) method and the model based inverse problem approach. In the first part of this work, the Lamb wave-based MTR method along with the non-contacting sensors is used for structural damage detection. The use of non-contact measurements for MTR method is validated through experimental results and finite element simulations. A novel technique in frequency-time domain is developed to detect linear damages using the MTR method. The technique is highly suitable for the detection of damages in large metallic structures, even when the damage is superficial, and the severity is low. In this technique, no baseline data are used, and all the wave motion measurements are made remotely using a laser vibrometer. Additionally, this novel MTR based technique is not affected due to changes in the material properties of a structure, environmental conditions, or structural loading conditions. Further, the MTR method is improved for two-dimensional damage imaging. The damage imaging technique is successfully tested through experimental results and finite element simulations. In the second part of this work, an inverse problem approach is developed for the detection and estimation of major damage types experienced in adhesive joints. The inverse problem solution is obtained through an optimization algorithm wherein the objective function is formulated using the Lamb wave propagation data. The technique is successfully used for the detection/estimation of cohesive damages, micro-voids, debonds, and weak bonds. Further, the inverse problem solution is separately obtained through a fully connected artificial neural network. The neural network is trained using the Lamb wave propagation data generated from Wavelet Spectral Finite Element (WSFE) model which is computationally much faster than a conventional finite element model. This inverse problem approach technique requires a single point measurement for the inspection of the entire width of the adhesive joint. The proposed technique can be used as an automated quality assurance tool during the manufacturing process, and as an inspection tool during the operational life of adhesively bonded structures

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part B-Defects Imaging and Recognition Techniques

The wavefield of Lamb waves is yielded by the feature of plate-like structures. And many defects imaging techniques and intelligent recognition algorithms have been developed for defects location, sizing and recognition through analyzing the parameters of received Lamb waves signals including the arrival time, attenuation, amplitude and phase, etc. In this chapter, we give a briefly review about the defects imaging techniques and the intelligent recognition algorithms. Considering the available parameters of Lamb waves signals and the setting of detection/monitoring systems, we roughly divide the defect location and sizing techniques into four categories, including the sparse array imaging techniques, the tomography techniques, the compact array techniques, and full wavefield imaging techniques. The principle of them is introduced. Meanwhile, the intelligent recognition techniques based on various of intelligent recognition algorithms that have been widely used to analyze Lamb waves signals in the research of defect recognition are reviewed, including the support vector machine, Bayesian methodology, and the neural networks

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part A-Lamb Waves Signals Emitting and Optimization Techniques

Lamb waves have been widely studied in structural integrity evaluation during the past decades with their low-attenuation and multi-defects sensitive nature. The performance of the evaluation has close relationship with the vibration property and the frequency of Lamb waves signals. Influenced by the nature of Lamb waves and the environment, the received signals may be difficult to interpret that limits the performance of the detection. So pure Lamb waves mode emitting and high-resolution signals acquisition play important roles in Lamb waves structural integrity evaluation. In this chapter, the basic theory of Lamb waves nature and some environment factors that should be considered in structural integrity evaluation are introduced. Three kinds of typical transduces used for specific Lamb waves mode emitting and sensing are briefly introduced. Then the development of techniques to improve the interpretability of signals are discussed, including the waveform modulation techniques, multi-scale analysis techniques and the temperature effect compensation techniques are summarized

A modified damage index probability imaging algorithm based on delay-and-sum imaging for synthesizing time-reversed Lamb waves

Imaging for damage in plate structure by Lamb waves is one of the most effective methods in the field of structural health monitoring. In order to improve the accuracy of damage localization, a novel method is proposed to modify damage exponent probability imaging algorithm based on delay-and-sum imaging by using time reversal Lamb waves. A new probability distribution function is introduced to improve the damage index probability method and is combined with delay-and-sum method for damage localization. Experimental results on aluminum plate show that the hybrid algorithm achieves better accuracy of damage location and imaging quality than the conventional delay-and-sum method

Structural Health Monitoring of Bolted Joints Using Guided Waves: A Review

Bolted joints are widely applied in engineering structures. Significant advantages of bolted joints are that they can be easily disassembled and the possibility to design for bearing large working load. However, in practical applications, preload loss in pre-tensioned bolts is inevitable. Reliable detection of bolt loosening is significant to ensure structural reliability and safety. In the past decades, the guided wave-based structural health monitoring (SHM) methods have been developed for the detection of bolt loosening, and considerable advancements have been made in this area. This chapter presents a review of the existing studies on bolt preload monitoring method based on guided wave. The basic principle and characteristics of the typical methods are discussed, which involve wave energy dissipation, time reversal guided wave, contact acoustic nonlinearity, and active chaotic ultrasonic excitation-based methods. In addition, this chapter presents an experimental comparison of the detection sensitivity of wave energy dissipation and time reversal method. The results show that the TR method is more sensitive to bolt loosening

Guided Lamb Wave Based 2-D Spiral Phased Array for Structural Health Monitoring of Thin Panel Structures

In almost all industries of mechanical, aerospace, and civil engineering fields, structural health monitoring (SHM) technology is essentially required for providing the reliable information of structural integrity of safety-critical structures, which can help reduce the risk of unexpected and sometimes catastrophic failures, and also offer cost-effective inspection and maintenance of the structures. State of the art SHM research on structural damage diagnosis is focused on developing global and real-time technologies to identify the existence, location, extent, and type of damage. In order to detect and monitor the structural damage in plate-like structures, SHM technology based on guided Lamb wave (GLW) interrogation is becoming more attractive due to its potential benefits such as large inspection area coverage in short time, simple inspection mechanism, and sensitivity to small damage. However, the GLW method has a few critical issues such as dispersion nature, mode conversion and separation, and multiple-mode existence. Phased array technique widely used in all aspects of civil, military, science, and medical industry fields may be employed to resolve the drawbacks of the GLW method. The GLW-based phased array approach is able to effectively examine and analyze complicated structural vibration responses in thin plate structures. Because the phased sensor array operates as a spatial filter for the GLW signals, the array signal processing method can enhance a desired signal component at a specific direction while eliminating other signal components from other directions. This dissertation presents the development, the experimental validation, and the damage detection applications of an innovative signal processing algorithm based on two-dimensional (2-D) spiral phased array in conjunction with the GLW interrogation technique. It starts with general backgrounds of SHM and the associated technology including the GLW interrogation method. Then, it is focused on the fundamentals of the GLW-based phased array approach and the development of an innovative signal processing algorithm associated with the 2-D spiral phased sensor array. The SHM approach based on array responses determined by the proposed phased array algorithm implementation is addressed. The experimental validation of the GLW-based 2-D spiral phased array technology and the associated damage detection applications to thin isotropic plate and anisotropic composite plate structures are presented

Master of Science

thesisCarbon fiber-reinforced composite materials have been increasingly used in aerospace and aeronautics industries due to their superior strength over metals, low fatigue life, high corrosion resistance, and temperature resistance. Since most damage, such as delaminations, manifest inside the composite material, we often cannot detect damage through visual inspection. As a replacement for visual inspection, ultrasonic guided waves have been widely researched to remotely detect, locate, and characterize damage in structures due to their unique capability to travel long distances and inspect inaccessible locations for damage. Yet the anisotropic nature of composites makes it difficult to identify the velocity characteristics of the guided waves and utilize them for damage localization. To address this challenge, we use sparse wavenumber analysis to determine anisotropic multimodal and dispersive frequency-wavenumber characteristics of guided waves. We then use these multimodal and dispersive properties to predict how guided waves propagate in the anisotropic plate through sparse wavenumber synthesis. Finally, these predictions, which form a wave propagation model for the composite, are integrated with matched field processing, a model-based localization framework, to locate damage on the composite

Structural Health Monitoring for Composite Materials

Computer networking & communication