The Research And Implementation Of Quality-Ortiented Process And System For Differential Pressure Vacuum Casting

Vacuum Casting (VC) is one of Rapid Tooling (RT) technologies. With ability of new products development being strengthen, VC products has been used widely and quality requirements of VC products are higher, so the quality control is imperative. At present, VC technology has some problems which hinder it to develop, such as the quality of VC products depends on the experience of operators, VC process researches are still in the theoretical study phase, and VC equipments are low automatization, poor flexibility and high rejection rate. Therefore, the research and development of numerical control VC equipment oriented to quality will be focus and difficulties in the future which are urgent to be solved, so it has high research value and practical significance.In order to improve quality of VC products and automation level of VC equipments, this dissertation applies theories and technologies which are vacuum casting, hydrodynamics, optimization design, computer graphics and images, automatic control, and intelligent control. The VC process mechanism is researched. The methods, strategies and model of quality control are researched. The whole structure of numerical control VC equipment is analyzed. The research emphasis include VC bubbles detection and elimination based on image processing technology, VC products quality control method based on Fuzzy Neural Network (FNN), and development differential pressure numerical control VC equipment (V450N-VD).The main research contents and contributions are described as following.(1) Based on detailed analysis of original VC process, for resolving quality problems of VC products, combining VC, differential pressure injection and gravity injection three processes, the differential pressure VC process is proposed. According to the process and mechanism of differential pressure VC, process parameters that influence products quality are analyzed in detailed. Aiming to the defects of existing VC equipments, this paper adopts Numerical Control (NC) technology to develop VC equipments and constructs differential pressure numerical control VC equipment (V450N-VD).(2) Based on the molding mechanism analysis of thermosetting plastic and the hydrodynamics rules research of VC process, the reaction kinetics model, reaction molding viscosity model and chemical rheological model are introduced. This paper adopts design of orthogonal experiment technology and Computer Aided Engineering (CAE) technology to design simulation orthogonal experiments which are executed though MPI software according to the reaction analysis process. The results of simulation experiments reflected the relation between process parameters and products quality. The optimized process parameters are obtained by analyzing experiments results. It can act as theoretical basis for VC products quality control.(3) This paper adopts machine vision and image processing technologies to realized real-time monitoring of bubbles for resolving defection of traditional bubbles detection and elimination methods on the basis of the analysis of generation reason, features and detection requirements of bubbles. Firstly, the Direct Image (DI) method based on CCD digital cameras is used to detect VC bubbles in real time, and the continuous collection of bubbles images is achieved through thread technology of VC++. Secondly, the image processing algorithms are determined on the basis of relative algorithms comparison, which mainly involves median filtering, adaptive threshold binary, and Canny edge detection. Especially, the bubble edge pixel proportion algorithm is put forward to extract feature of deformation and overlapping bubbles. It can better resolve information loss problem of bubbles.(4) Because of nonlinear and multivariable of VC process, they are proposed that the prediction models and method based on combination of Artificial Neural Network (ANN) and Fuzzy Logic Control (FLC). According to the structure and learning algorithm of FNN based on Takagi-Sugeno model, the quality prediction model of VC products is established. The recommendation and adjustment of VC process parameters are realized using these models.(5) On the support of above theories and methods, a physical prototype (V450N-VD) is developed. Some functional testing and engineering application testing are carried out to verify feasibility and advanced of system.