Research and implementation of quality oriented di
Time：2023-04-02
Casting VC (Vacuum) technology is the most widely used technology in Tooling RT (Rapid) technology. With the continuous strengthening of new product development capabilities, the use of VC casting parts is more and more extensive, the customer demand for VC casting parts quality is also getting higher and higher, so the quality control is imperative. At present, the quality of VC products mostly rely on the experience of the operator, VC technology is still in the stage of theoretical research, the degree of automation of VC equipment, low processing flexibility, high reject rate, these problems have become the bottleneck of the development of VC technology. Therefore, the development of digital control VC equipment for quality is the future development direction, and it is the key to improve the quality of VC casting parts. It is also a difficult problem to be solved by scholars at home and abroad, which has high research value and practical significance. This thesis is to study design for rapid manufacturing as the main line to the vacuum casting, fluid mechanics, optimization design, graphic image, automatic control and intelligent control theory, to improve the VC casting quality, to enhance the level of automation equipment for the purpose of VC, discussed the mechanism of VC. This paper according to the quality control method and strategy and model of VC; on this basis, the structure of VC digital control equipment are analyzed, which focuses on the VC bubble monitoring, image processing based on fuzzy neural network casting quality control method is studied based on the development of the digital control of vacuum differential pressure note the physical prototype of ---V450N-VD type vacuum casting machine. In this paper, the VC technology and casting parts quality control requirements are discussed, and the relevant research development at home and abroad and the status of the research are reviewed. The main research contents and achievements of the dissertation are as follows: (1) based on the detailed analysis of the traditional VC technology, in order to solve the quality problems of VC products, combined with VC, differential pressure injection and gravity injection three processes, put forward the technical method of differential pressure VC. According to the process and mechanism of differential pressure VC, the influence of process parameters of casting quality analysis. Finally, aiming at the defects of the existing VC equipment, the digital control technology is introduced into the VC process control, and the differential pressure digital control VC system is constructed. (2) on the basis of in-depth analysis of the reaction mechanism of the thermosetting plastic molding process, study the VC law of fluid mechanics, introduces reaction kinetics, viscosity and chemical reaction forming model of rheological model, and the application of orthogonal design technology and computer aided engineering technology, according to the analysis process of the reaction forming simulation orthogonal experiment by MPI and to study the influence of process parameters on the casting quality and the degree of influence is given based on optimal process parameters, provides a theoretical basis for the research and implementation of quality control. (3) in the analysis of the bubble causes, VC process characteristics and detection on the basis of the requirements, according to the method of defects and eliminate existing bubble detection, machine vision and image processing technology combined to realize the real-time monitoring of the bubble. By using the direct image (DI) method using CCD digital camera for the VC bubble detection, and realizes the continuous image acquisition bubble thread through the VC++ technology; based on the image processing algorithm is to determine the suitable VC bubble image processing algorithms, mainly involved in adaptive threshold value filtering, binarization, edge detection Canny the algorithm, especially for large deformation of high overlap bubble feature extraction, presents a bubble edge pixel ratio algorithm, solves the problem of information loss of overlapping bubbles. (4) according to the nonlinear and multi variable characteristics of VC process, a model and method of VC quality prediction based on artificial neural network and fuzzy logic control is presented. According to the structure of fuzzy neural network and its learning algorithm based on Takagi-Sugeno model, the establishment of quality casting model and differential pressure VC process is recommended and adjusted by the model, the casting quality control. (5) in the basic research on the theory and methods on the development of a physical prototype of V450N-VD type vacuum casting machine, and the physical prototype of a series of system function testing and engineering application testing, to verify the feasibility of the system and advanced
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