In this paper, a new type of composite gradient sandwich plate structure is proposed, which embeds the pre-strained shape memory alloy (SMA) into the surface layer and the core layer composed of epoxy resin and graphite-reinforced materials. In the core layer, graphite-reinforced material has a continuous gradient distribution along the thickness direction of the sandwich plate. Dynamic behavior of composite gradient sandwich plate in thermal environment is investigated. The equations of motion and frequency equation are derived based on the Reddy shear deformation theory and the constitutive equation for a composite sandwich plate, via the Hamilton principle. Some analytical study is depicted to provide an insight into the effects of volume fraction of material composition, gradient distribution of graphite in the core layer, and pre-strain of SMA in the surface layer on the dynamic behavior of a sandwich composite plate. This study investigates the modal performance of a sandwich composite plate with two aspects, a gradient core layer of graphite-reinforced material and surface layer-embedded SMA wires, which provide a new design idea for dynamic behavior of sandwich plates.

Aiming at the lack of method on noise diagnosis for sweeping vehicle, this paper proposes a vehicle noise diagnosis scheme based on adaptive fuzzy neural inference system (ANFIS). The paper explains the principle of ANFIS in the field of noise diagnosis, and performs a noise test on a sweeping vehicle. The spectrum analysis is utilized to obtain the data for ANFIS network training, inference and verification. Combined with ANFIS theory, the noise source distribution of the sweeping vehicle is inferred and verified. The results show that the noise source diagnosis method based on ANFIS is feasible and effective for the sweeping vehicle. Furthermore, the method can provide a reference for the similar situation where only parts of the noise sources are known.