A Remaining useful life prediction method considering the dimension optimization and the iterative speed

Abstract

Tool life prediction is critical to workpiece quality and machining costs. In this paper, a remaining useful life prediction method was proposed, which considering the dimension optimization accuracy of vibration features and the iterative speed of industrial models. Firstly, an optimization method for extracting spatial information of vibration signals was found. The spatial topology of high dimensional vibration information was preserved, when achieving dimension reduction of high dimensional feature. Secondly, a determination method of loss function was proposed to ensure the extraction effects of spatial information. Meanwhile, the k value selection method was proposed which considered to balance the time efficiency factor by using the extraction effect of spatial information. Thirdly, an optimal strategy and model for the remaining useful life prediction of the tool which is suitable for industry was determined, in order to ensure the accuracy and increase the speed. Finally, the superiority and effectiveness of the proposed method were verified by using the processing data of practical tool life cycle.