Papers by Author: Xiao Yan Huang

Abstract: Structural damage is too difficult to identification. In this paper, a new method using grey forecasting model to identification the structural damage with past and present data is proposed. Based on the last few years of modal parameters, structural parameters including stiffness and mass of the structural were further predicted the trend using grey forecasting model. Here proposed large structure systems with natural decay and unnatural decay. Natural decay modal parameter can be get from the grey forecasting model, compare with the modal parameter identify currently, by a set value to analysis structural damage. Experimental results verify the theoretical analysis.

Abstract: In injection mold, design of gate location is among the most critical factors in achieving dimensionally accurate parts and high productivity of the molding process, since it influences the manner in which the plastic flows into the mold cavity. To automatically predict the optimal gate location of injection molds based on injection-molding simulation, a new and practical method: empirical search method according to the analysis of common optimization methods has been presented in this article. In this method, the gate location scope is initiated by the practical experience of mold designer so that the core for the gate location optimization is construction of empirical library. In order to build the empirical library, in terms of shape and function characteristic of injection-molding part, all the parts are classified six kinds: shell, container, plate, structural part, ornamental part and transparent part, and the corresponding design rules are kept in the empirical library. In addition, this article combines the empirical search method and numerical simulation technique, builds the mathematics model for the gate location optimization of plate part in empirical library and obtains the gate location optimization scheme for this kind of part through one concrete numerical example. The analysis and verification by adopting the software Moldflow testify the optimization mathematics model is effective.