An adaptive grinding method for precision-cast blades with geometric deviation

Abstract

Precision-cast blades are core components in aeroengines, and their machining precision has a considerable effect on the performance of the aeroengine. In this paper, an adaptive grinding method for precision-cast blades with geometric deviation is proposed to improve the machining precision, machining efficiency, and automation level of precision-cast blade grinding. A scheme for adaptive grinding of precision-cast blades with geometric deviation is developed, a grinding process for precision-cast blades is formulated, and a robotic grinding system is constructed. An optimal model to match the blade measurement data to the design model is then established, and a corresponding optimal matching matrix is solved to determine a position reference for precision-cast blades. Further, the theoretical cutter contacts are extracted, and the machining allowance of the precision-cast blade profile is measured. An estimation model of grinding material removal (MR) of precision-cast blades based on a neural network algorithm is established, and the correctness of the model is verified. Finally, an adaptive grinding experiment is performed on the concave surface (CC) of a precision-cast blade to verify the accuracy of the proposed grinding method. The experimental results show that, after adaptive grinding, the machining allowance of CC is distributed in the range of − 0.05 mm to 0.05 mm, which meets the machining precision requirements of the blade.