Abstract
Thin web parts are widely used in the aerospace industry; however, serious machining errors may happen due to their low rigidity. In this study, a highly automatic method that integrates machining status monitoring, on-machine measurement (OMM) inspection, machining error modeling and real time compensation is proposed and developed. The OMM inspection is firstly applied to measure the comprehensive machining errors, the Hampel filtering, the triangulation-based cubic interpolation and a machine learning algorithm are then used to train the machining error model. Finally, the real time compensation of high-density cutting points is realized by developing the compensation system based on External Machine Zero Point Shift (EMZPS) function of machine tool. The proposed method was validated through three sets of compensation experiment of a thin web part. The results revealed that 58.1%, 68.4% and 62.6% of the machining error ranges were decreased, respectively. This method demonstrates immense potential for further applications in efficiency and accuracy improvement of thin-walled freeform surface parts.
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