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采用离心精密铸造方法,初步研究了铸造大尺寸薄壁钛合金筒体(直径660 mm,高750 mm,壁厚4 mm)的可行性。结果表明:离心转速较小时,Ti-6Al-4V筒体无法完整充型,而较大的转速可实现完整充型。对于完整充型的筒体,其内部疏松缺陷数量随转速提高而减少。对于给定转速和具有均匀温度场的型壳,筒体中疏松缺陷数量随熔液路径增长而增加。采用Y2O3面层型壳可获得无α壳层的表面质量良好的精密铸件,其内部疏松可通过热等静压消除。铸件的晶粒度随铸件截面厚度变化改变较大,需通过微合金化和后续热处理等措施加以调整。 相似文献
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《中国航空学报》2021,34(6):162-177
In the manufacturing of thin wall components for aerospace industry, apart from the side wall contour error, the Remaining Bottom Thickness Error (RBTE) for the thin-wall pocket component (e.g. rocket shell) is of the same importance but overlooked in current research. If the RBTE reduces by 30%, the weight reduction of the entire component will reach up to tens of kilograms while improving the dynamic balance performance of the large component. Current RBTE control requires the off-process measurement of limited discrete points on the component bottom to provide the reference value for compensation. This leads to incompleteness in the remaining bottom thickness control and redundant measurement in manufacturing. In this paper, the framework of data-driven physics based model is proposed and developed for the real-time prediction of critical quality for large components, which enables accurate prediction and compensation of RBTE value for the thin wall components. The physics based model considers the primary root cause, in terms of tool deflection and clamping stiffness induced Axial Material Removal Thickness (AMRT) variation, for the RBTE formation. And to incorporate the dynamic and inherent coupling of the complicated manufacturing system, the multi-feature fusion and machine learning algorithm, i.e. kernel Principal Component Analysis (kPCA) and kernel Support Vector Regression (kSVR), are incorporated with the physics based model. Therefore, the proposed data-driven physics based model combines both process mechanism and the system disturbance to achieve better prediction accuracy. The final verification experiment is implemented to validate the effectiveness of the proposed method for dimensional accuracy prediction in pocket milling, and the prediction accuracy of AMRT achieves 0.014 mm and 0.019 mm for straight and corner milling, respectively. 相似文献
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智能控制的真空变压反重力铸造薄壁铸件充型机理的研究 总被引:1,自引:0,他引:1
本文研究了一种新型的反重力铸造法--智能控制的真空变压反重力铸造薄壁铸件的充型机理,并对智能控制的真空变压反重力铸造和重力铸造分别铸造0.8mm、1.5mm、2mm的铝合金薄壁铸件的充型能力进行了比较。研究结果表明,真空变压反重力铸造能实现金属液平稳充型,具有良好的充型流体力学条件;真空变压反重力铸造0.8mm、1.5mm、2mm的铝合金薄壁件全部充填完整,具有良好的充型能力。 相似文献
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As a promising numerical tool of structural dynamics in mid-and high frequencies, the wave and finite element method (WFEM) is receiving increasingly attention and applications. In this paper, an enhanced WFEM has been developed with a reduced model and a new eigenvalue scheme. The reduced model is applicable for structures with piezoelectric shunts or local dampers;the new eigenvalue scheme can mitigate the ill-conditioning when the wave basis is calculated. The enhanced WFEM is applied to a thin-wall structure with periodically distributed piezoelectric mate-rials (PZT). Both free wave characteristics and forced response are analyzed and the influences of the suggested enhancements are presented. It is shown that if the control factors are properly cho-sen, these enhancements can improve the accuracy while accelerating the calculation. Resulting from the complexity of the application, these enhancements are not optional but imperative. 相似文献
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