Abstract
Real-time wear monitoring of hob cutters is of great significance to the quality and efficiency of gear hobbing. To achieve this goal, a strategy based on statistical analysis is proposed in this paper. First, vibration signals during the entire life cycle of a hob cutter are collected. Then, a feature iterative integration method is proposed to integrate the initial features of vibration signals. The integrated features have obvious stages, reflecting the different wear status of hob cutters. Next, a probability tabular cumulative sum control chart method is established to monitor the wear status of hob cutters in real time. Finally, the verification results of two different data sets prove the effectiveness and transferability of the proposed methods.
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