Acoustic Emission Method for Diagnostics and Structural Health Monitoring of Critical Structures During Operation

Acoustic Emission (AE) Structural Health Monitoring (SHM) is an emerging field of modern engineering that deals with diagnosis and monitoring of structures during their operation. Increasing requirements for safety, development of tools and criteria for condition based maintenance (CBM), cost reduction are all driving development of AE SHM methods in different industries. The primary goal of AE SHM is detection, identification, assessment and monitoring of flaws or faults/conditions that affect or may affect in a future safety or performance of structures. AE SHM combines elements of AE testing, AE condition/process monitoring, statistical pattern recognition and physical modelling. In this work, the concept, definitions and principles of AE SHM are presented including fundamental assumptions regarding development of new AE SHM procedures, selection of equipment and methods of data acquisition and analysis, diagnosis, monitoring and prediction by AE SHM. Several important industrial examples are provided to demonstrate unique capabilities of AE SHM and their contribution to safety of critical structures. Particularly it is shown application of AE SHM for detection, assessment and long-term monitoring of flaws during normal operation of different industrial systems. It is also demonstrated how AE SHM is useful for identification of risk factors and causes of flaw origination and development thereby providing valuable information for predictive maintenance

Acoustic Emission Method for Diagnostics and Structural Health Monitoring of Critical Structures During Operation

Acoustic Emission (AE) Structural Health Monitoring (SHM) is an emerging field of modern engineering that deals with diagnosis and monitoring of structures during their operation. Increasing requirements for safety, development of tools and criteria for condition based maintenance (CBM), cost reduction are all driving development of AE SHM methods in different industries. The primary goal of AE SHM is detection, identification, assessment and monitoring of flaws or faults/conditions that affect or may affect in a future safety or performance of structures. AE SHM combines elements of AE testing, AE condition/process monitoring, statistical pattern recognition and physical modelling. In this work, the concept, definitions and principles of AE SHM are presented including fundamental assumptions regarding development of new AE SHM procedures, selection of equipment and methods of data acquisition and analysis, diagnosis, monitoring and prediction by AE SHM. Several important industrial examples are provided to demonstrate unique capabilities of AE SHM and their contribution to safety of critical structures. Particularly it is shown application of AE SHM for detection, assessment and long-term monitoring of flaws during normal operation of different industrial systems. It is also demonstrated how AE SHM is useful for identification of risk factors and causes of flaw origination and development thereby providing valuable information for predictive maintenance

Spiral Weight for Modeling Cracks in Meshless Numerical Methods" Computational Mechanics, Springer-Verlag, accepted for publication

In the last decade several different approaches have been developed to study arbitrary static and dynamic cracks. Among these methods meshless techniques play an important role. These methods provide an accurate solution of a wide range of fracture mechanics problems while traditional methods such as finite element and boundary element have limitations. We wish to increase the accuracy of the meshless approximations without increasing the nodal density. This is done by an appropriate modification of the weight function near crack tips. Earlier attempts still had limitations that result in a lack of accuracy, especially in the case when a linear basis is used. In this work a new technique, the spiral weight, is introduced that minimizes the drawbacks of existing methods. Numerical examples show that the spiral weight method is more efficient than existing methods, when using a linear basis, for the solution of crack problems