Development of a novel online chatter monitoring system for flexible milling process

Abstract Regenerative chatter, a kind of undesirable self-excited vibration, has been widely found in the milling of flexible parts due to the weak rigidity, which imposes a major limitation on workpiece quality and processing efficiency. To achieve the goal of high-performance machining, online chatter detection attracts the attention of many researchers. Nevertheless, few works related to the online chatter frequency estimation are reported. Online chatter frequency estimation is of great importance for some chatter suppression operations, where the processing parameters can be adjusted adaptively based on the estimated dominant chatter frequency to stabilize chatter cutting. The contribution of this study is the development of a novel online chatter monitoring system consisting of chatter detection and chatter frequency estimation. According to the characteristic analysis of the milling signal, the cyclostationarity energy ratio between the chatter component and the total vibration is presented for the rapid chatter detection. Compared with entropy or statistic indicators in existing works, the proposed chatter indicator has an explicit physical meaning that the value reflects the chatter level directly. Moreover, it is convenient and intuitive to set a detection threshold independent of cutting conditions. After the chatter state is timely detected, an improved advanced subspace-based technique is proposed for spectral estimation of the chatter component, which not only automatically determines the number of dominant chatter harmonics, but obtains the superhigh frequency-resolution even in the condition of a small number of data samples. The effectiveness and applicability of the proposed chatter monitoring system have been successfully verified through the simulation signal and milling experiments with different configurations.