In the last two decades, the emphasis in aircraft maintenance has been on developing online structural health monitoring systems to replace conventional non destructive inspection techniques which require considerable down-time, human effort and cost. Vibration based damage detection is one of the most promising techniques for implementation in Structural Health Monitoring (SHM). In vibration based methods, the presence of damage is detected by monitoring changes in one of the dynamic parameters of the structure, resonant frequencies, modeshapes or damping characteristics. Compared to modeshape based methods, frequency based methods have the advantage that measurements need to be taken only at a single location. Previous developments on frequency based techniques have relied on Finite Element Model updating; analytical techniques have hitherto been restricted to beams due to the complexity in developing equations for cracked two dimensional structures. In this thesis the analytical approach using an energy formulation is extended to plates with through-thickness cracks, where modeshapes from either numerical modelling or experimental measurements can be employed to determine the energy of vibration. It is demonstrated that by using a hybrid approach, incorporating experimentally measured modeshapes along with measured changes in frequencies, the damage parameters can be estimated without resorting to theoretical modelling or numerical analysis. The inverse problem of finding the crack location, size and orientation from measured changes in frequencies is addressed using minimisation techniques. The forward problem and the inverse algorithm is first validated using numerical simulation and experimental testing of beams with edge cracks and centre cracks. The application of the methodology to the two dimensional case is then validated by numerical simulation and experimental modal analysis of plates with through thickness cracks. A statistical procedure is developed for determination of the 90/95 probability of crack detection and the minimum detectable crack size in both cases. It is demonstrated that the measurement of frequency changes can be successfully employed to detect and assess the location and size of cracks in beams and plates, using modeshapes from theory, Finite Element Analysis (FEA) or measurements.

In the oil and gas industries, large companies are endeavoring to find and utilize efficient structural health monitoring methods in order to reduce maintenance costs and time. Through an examination of the vibration-based techniques, this title addresses theoretical, computational and experimental methods used within this trend.By providing comprehensive and up-to-date coverage of established and emerging processes, this book enables the reader to draw their own conclusions about the field of vibration-controlled damage detection in comparison with other available techniques. The chapters offer a balance between laboratory and practical applications, in addition to detailed case studies, strengths and weakness are drawn from a broad spectrum of information.

All the steps involved in planning, executing, interpreting and applying the results from a modal test are described in straightforward terms. This edition has brought the previous book up to date by including all the new and improved techniques that have emerged during the 15 years since the first edition was written, especially those of signal processing and modal analysis. New topics are introduced, notable amongst them are the application of modal testing to rotating machinery and the use of scanning laser vibrometer.

Non destructive testing aimed at monitoring, structural identification and di- nostics is of strategic importance in many branches of civil and mechanical - gineering. This type of tests is widely practiced and directly affects topical issues regarding the design of new buildings and the repair and monitoring of existing ones. The load bearing capacity of a structure can now be evaluated using well established mechanical modelling methods aided by computing facilities of great capability. However, to ensure reliable results, models must be calibrated with - curate information on the characteristics of materials and structural components. To this end, non destructive techniques are a useful tool from several points of view. Particularly, by measuring structural response, they provide guidance on the validation of structural descriptions or of the mathematical models of material behaviour. Diagnostic engineering is a crucial area for the application of non destructive testing methods. Repeated tests over time can indicate the emergence of p- sible damage occurring during the structure's lifetime and provide quantitative estimates of the level of residual safety.

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Finite element models can be used to discern the location and severity of damage in structures. This is frequently pursued by using the differences in measured and computed natural frequencies, in conjunction with the sensitivities calculated using the FE model. Given that a modal test produced a limited number of natural frequencies for a structure, the concept of Artificial Boundary Conditions (ABC) was developed, which yields additional natural frequency information for a structure. This is accomplished by artificially imposing additional boundary conditions to the measured data. In this thesis, the use of ABC to produce an improved set of structural sensitivities is explored. It is shown that the selection of ABC sets is best guided by the strain energy distribution in the structure.