Preface Acknowledgments 1. Introduction 2. Dispersion principles 3. Unbounded isotropic and anisotropic media 4. Reflection and refraction 5. Oblique incidence 6. Waves in plates 7. Surface and subsurface waves 8. Finite element method for guided wave mechanics 9. The semi-analytical finite element method (SAFE) 10. Guided waves in hollow cylinders 11. Circumferential guided waves 12. Guided waves in layered structures 13. Source influence on guided wave excitation 14. Horizontal shear 15. Guided waves in anisotropic media 16. Guided wave phased arrays in piping 17. Guided waves in viscoelastic media 18. Ultrasonic vibrations 19. Guided wave array transducers 20. Introduction to guided wave nonlinear methods 21. Guided wave imaging methods Appendix A: ultrasonic nondestructive testing principles, analysis and display technology Appendix B: basic formulas and concepts in the theory of elasticity Appendix C: physically based signal processing concepts for guided waves Appendix D: guided wave mode and frequency selection tips.

Ultrasonic Guided Waves in Solid Media

The paper provides a state of the art review of guided wave based structural health monitoring (SHM). First, the fundamental concepts of guided wave propagation and its implementation for SHM is explained. Following sections present the different modeling schemes adopted, developments in the area of transducers for generation, and sensing of wave, signal processing and imaging technique, statistical and machine learning schemes for feature extraction. Next, a section is presented on the recent advancements in nonlinear guided wave for SHM. This is followed by section on Rayleigh and SH waves. Next is a section on real-life implementation of guided wave for industrial problems. The paper, though briefly talks about the early development for completeness,. is primarily focussed on the recent progress made in the last decade. The paper ends by discussing and highlighting the future directions and open areas of research in guided wave based SHM.

https://iopscience.iop.org/article/10.1088/0964-1726/25/5/053001/pdf

Guided wave based structural health monitoring: A review

Ultrasonic guided wave inspection is expanding rapidly to many different areas of manufacturing and in-service inspection. The purpose of this paper is to provide a vision of ultrasonic guided wave inspection potential aswe move forward into the new millennium. An increased understanding of the basic physics and wave mechanics associated with guided wave inspection has led to an increase in practical nondestructive evaluation and inspection problems. Some fundamental concepts and a number of different applications that are currently being considered will be presented in the paper along with a brief description of the sensor and software technology that will make ultrasonic guided wave inspection commonplace in the next century.

A Baseline and Vision of Ultrasonic Guided Wave Inspection Potential

Neural networks

BACKGROUND The tight integration of sensing, actuation, and computation that biological systems exhibit to achieve shape and appearance changes (like the cuttlefish and birds in flight), adaptive load support (like the banyan tree), or tactile sensing at very high dynamic range (such as the human skin) has long served as inspiration for engineered systems. Artificial materials with such capabilities could enable airplane wings and vehicles with the ability to adapt their aerodynamic profile or camouflage in the environment, bridges and other civil structures that could detect and repair damages, or robotic skin and prosthetics with the ability to sense touch and subtle textures. The vision for such materials has been articulated repeatedly in science and fiction (“programmable matter”) and periodically has undergone a renaissance with the advent of new enabling technology such as fast digital electronics in the 1970s and microelectromechanical systems in the 1990s. ADVANCES Recent advances in manufacturing, combined with the miniaturization of electronics that has culminated in providing the power of a desktop computer of the 1990s on the head of a pin, is enabling a new class of “robotic” materials that transcend classical composite materials in functionality. Whereas state-of-the-art composites are increasingly integrating sensors and actuators at high densities, the availability of cheap and small microprocessors will allow these materials to function autonomously. Yet, this vision requires the tight integration of material science, computer science, and other related disciplines to make fundamental advances in distributed algorithms and manufacturing processes. Advances are currently being made in individual disciplines rather than system integration, which has become increasingly possible in recent years. For example, the composite materials community has made tremendous advances in composites that integrate sensing for nondestructive evaluation, and actuation (for example, for shape-changing airfoils), as well as their manufacturing. At the same time, computer science has created an entire field concerned with distributed algorithms to collect, process, and act upon vast collections of information in the field of sensor networks. Similarly, manufacturing has been revolutionized by advances in three-dimensional (3D) printing, as well as entirely new methods for creating complex structures from unfolding or stretching of patterned 2D composites. Finally, robotics and controls have made advances in controlling robots with multiple actuators, continuum dynamics, and large numbers of distributed sensors. Only a few systems have taken advantage of these advances, however, to create materials that tightly integrate sensing, actuation, computation, and communication in a way that allows them to be mass-produced cheaply and easily. OUTLOOK Robotic materials can enable smart composites that autonomously change their shape, stiffness, or physical appearance in a fully programmable way, extending the functionality of classical “smart materials.” If mass-produced economically and available as a commodity, robotic materials have the potential to add unprecedented functionality to everyday objects and surfaces, enabling a vast array of applications ranging from more efficient aircraft and vehicles, to sensorial robotics and prosthetics, to everyday objects like clothing and furniture. Realizing this vision requires not only a new level of interdisciplinary collaboration between the engineering disciplines and the sciences, but also a new model of interdisciplinary education that captures both the disciplinary breadth of robotic materials and the depth of individual disciplines.

Materials that couple sensing, actuation, computation, and communication

This work focuses on an ultrasonic guided wave structural health monitoring (SHM) system development for aircraft wing inspection. In part I of the study, a detailed description of a real aluminum wing specimen and some preliminary wave propagation tests on the wing panel are presented. Unfortunately, strong attenuation and scattering impede guided waves for large-area inspection. Nevertheless, small, low-cost and light-weight piezoelectric (PZT) discs were bonded to various parts of the aircraft wing, in a form of relatively sparse arrays, for simulated cracks and corrosion monitoring. The PZT discs take turns generating and receiving ultrasonic guided waves. Pair-wise through-transmission waveforms collected at normal conditions served as baselines, and subsequent signals collected at defected conditions such as rivet cracks or corrosion detected the presence of a defect and its location with a novel correlation analysis based technique called RAPID (reconstruction algorithm for probabilistic inspection of defects). The effectiveness of the algorithm was tested with several case studies in a laboratory environment. It showed good performance for defect detection, size estimation and localization in complex aircraft wing structures.

https://iopscience.iop.org/article/10.1088/0964-1726/16/4/032/pdf

Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring

The objective of this study is to develop a wireless ultrasonic structural health monitoring (SHM) system for aircraft wing inspection. In part I of the study (Zhao et al 2007 Smart?Mater.?Struct. 16 1208?17), small, low cost and light weight piezoelectric (PZT) disc transducers were bonded to various parts of an aircraft wing for detection, localization and growth monitoring of defects. In this part, two approaches for wirelessly interrogating the sensor/actuator network were developed and tested. The first one utilizes a pair of reactive coupling monopoles to deliver 350?kHz RF tone-burst interrogation pulses directly to the PZT transducers for generating ultrasonic guided waves and to receive the response signals from the PZTs. It couples enough energy to and from the PZT transducers for the wing panel inspection, but the signal is quite noisy and the monopoles need to be in close proximity to each other for efficient coupling. In the second approach, a small local diagnostic device was developed that can be embedded into the wing and transmit the digital signals FM-modulated on a 915?MHz carrier. The device has an ultrasonic pulser that can generate 350?kHz, 70?V tone-burst signals, a multiplexed A/D board with a programmable gain amplifier for multi-channel data acquisition, a microprocessor for circuit control and data processing, and a wireless module for data transmission. Power to the electronics is delivered wirelessly at X-band with an antenna?rectifier (rectenna) array conformed to the aircraft body, eliminating the need for batteries and their replacement. It can effectively deliver at least 100?mW of DC power continuously from a transmitter at a range of 1?m. The wireless system was tested with the PZT sensor array on the wing panel and compared well with the wire connection case.

http://ecee.colorado.edu/microwave/docs/publications/2007/Paper-piezo-2007.pdf

Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches

Guided time-harmonic shear horizontal (SH) waves propagating in the circumferential direction of an isotropic hollow cylinder are studied. The dispersion equation as well as the displacement and stress field across the wall thickness is derived analytically. Compared with the SH waves in a plate, a quantitative guideline of how well a plate model can approximate a pipe in the circumferential direction is given for defect characterization purpose. The work is also crucial for initiating work efforts on three-dimensional wave scattering for pipeline inspection.

Guided circumferential shear horizontal waves in an isotropic hollow cylinder

To minimize the number of birdstrikes, a common method is to use microphone arrays to monitor and identify dangerous birds near the airport or some critical locations in the airspace. However, it was recognized that the range of existing ground-based acoustic monitoring devices is only limited to a few hundred meters. Moreover, the bird classification performance in low signal-to-noise environments such as airports is not very satisfactory. This paper summarizes the development of a high performance bird classification system using a hidden Markov model (HMM) and Gaussian mixture model (GMM). Experimental results verified the classification performance.

Bird classification algorithms: theory and experimental results

Ship-motion prediction is very useful for several naval operations such as aircraft landing, cargo transfer, off-loading of small boats, and ship "mating" between a big transport ship and some small ships. The prediction information is extremely useful in sea states above 3. Five to ten seconds of ship motion prediction can give the operator ample time to avoid serious collisions. The paper summarizes the development of a high performance ship-motion prediction algorithm using minor component analysis (MCA). Simulation results show that this method can predict ship motion a long time ahead with consistent accuracy. That is, the prediction error is almost the same for the 5 second and 20 second predictions. Other conventional algorithms, such as neural networks (NN), autoregressive methods (AR), and Wiener prediction, were also studied for comparative purposes.

Xiaoliang Zhao

Papers

Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring

Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches

Guided circumferential shear horizontal waves in an isotropic hollow cylinder

Bird classification algorithms: theory and experimental results

Ship-motion prediction: algorithms and simulation results