Research Progress on Optimization Method of Magnetic Grinding Process for Inner Surface of Aircraft Engine Bend Pipe

The level of magnetic grinding technology determines the accuracy and efficiency of magnetic grinding on the inner surface of aircraft engine bend pipes. This article analyzes the optimization methods of magnetic grinding process parameters for the inner surface of aircraft engine bent pipes, such as the multiple regression prediction method, the response surface method, and the grey relational analysis method. It is pointed out that the current optimization methods for magnetic grinding technology on the inner surface of aircraft engine bent pipes do not consider the nonlinear characteristics between various grinding process parameters, resulting in defects such as low precision and efficiency of magnetic particle grinding technology. An optimization approach was proposed to accurately predict the optimal magnetic grinding process parameters for the inner surface of aircraft engine bent pipes, establish a nonlinear mapping relationship that reflects the roughness of the inner surface of the bent pipe and the main process parameters, optimize the BP neural network model based on the genetic algorithm, design magnetic grinding experiments on the inner surface of aircraft engine bend pipes, and explore the magnetic grinding process that is beneficial for improving the accuracy and efficiency of magnetic grinding on the inner surface of aircraft engine bend pipes. It can achieve efficient and accurate prediction of magnetic grinding of the inner surface of aircraft engine bend pipes. It provides a basis for the manufacturing and maintenance of high-precision aircraft engine bend pipes.