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Process Parameter Optimization and Experiment Study of Aero-engine Blade in Electrochemical Machining

机译:电化学加工空气发动机叶片的过程参数优化与实验研究

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摘要

Because the process of blade in electrochemical machining(EMC) can be effected by many factors, such as blade shapes, machining electrical field, electrolyte fluid field and anode electrochemical dissolution, different ECM machining parameters maybe result in great affections on blade machining accuracy. Regard some type of aero-engine blade as research object, five main machining parameters, applied voltage, initial machining gap, cathode feed rate, electrolyte temperature and pressure difference between electrolyte inlet and outlet, have been evaluated and optimized based on BP neural network technique. From 3125 possible machining parameter combinations, 657 optimized parameter combinations are discovered. Furthermore, the final optimized ECM process parameters have been obtained. To verify the validity of the optimized ECM parameter combination, a serial of machining experiments have been conducted on an industrial scale ECM machine, and the experiment results demonstrates that the optimized ECM parameter combination not only can satisfy the manufacturing requirements of blade fully but has excellent ECM process stability.
机译:由于电化学加工(EMC)中的叶片的过程可以通过许多因素进行,例如叶片形状,加工电场,电解质流体场和阳极电化学溶解,不同的ECM加工参数可能导致叶片加工精度的巨大情感。根据BP神经网络技术评估并优化了一些类型的航空发动机刀片作为研究对象,其中五个主加工参数,施加的电压,初始加工间隙,阴极进料,电解质入口和出口之间的电解质温度和压力差。从3125可能的加工参数组合,发现657个优化参数组合。此外,已经获得了最终优化的ECM工艺参数。为了验证优化的ECM参数组合的有效性,已经在工业规模ECM机上进行了一系列加工实验,实验结果表明优化的ECM参数组合不仅可以完全满足刀片的制造要求,但具有优异的ECM过程稳定性。

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