Inversion Of Material Properties Of Functionally Graded Materials Using Ultrasonic Guided Wave

Material is the material basis for the human survival and development. With the continuous progress of human society, many walks put forward more and more stringent requirements for materials. However, for a new material, the corresponding detection techniques must be developed before it can be safely, effectively and widely used. We must study the characteristic of materials, as well as to understand, grasp the characteristics of the material itself. Therefore, research on fluctuation characteristics and mechanical properties of the material and the corresponding detection, technologies of inversing material properties become the key to the effectiveness of new materials and expanding applications. Advanced detection methods of the mechanical properties of composite materials usually use the complex relationship between the structural dynamic response and material properties.When this relationship is represented by a mathematical model, called the forward problem. Then, if we has a series of precise measurement of structural response data, combined with a large number of forward calculation, then the composite material properties can be achieved by properly build inversion model identification.Functionally graded material,referred to as FGM, is a kind of composite materials, whose components or structures have a continuous and regular change along a direction, eliminating or weakening interface between materials as much as possible, so as to avoid or reduce the changes of material properties at the interface, while the performance also shows a continuous change in this direction to meet the specific requirements. FGM material itself and the wave characteristics of its structure have been carried out in many of the studies, however, there are still a lot of work needing to be further studied, such as influence of initial stress on wave propagation characteristics in the structure. In this paper, the guided wave propagation in the multilayer of FGM under initial stress are studied based on the “Mechanics of Incremental Deformations” and the Legendre orthogonal polynomial series expansion approach, in which initial stress is separately exerted in board thickness and in the wave propagation direction. And we studied the effect of initial stress on dispersion curves.In addition, when inversing the component distribution and the properties of FGM materials using intelligent algorithms. A single algorithm itself has many defects, but there is complementarity between various algorithms. In this paper, we not only determine material properties of functionally graded materials using neural network inversion, but also determine material properties of functionally graded materials using Auto-adapted nerve fuzzy system inversion, which is the combination of neural networks and fuzzy logic. And analyzes the advantages and disadvantages of two kind of networks in the inversion. Meanwhile, studied noise reduction capability of two types of network.