Significant research effort has been carried out in the detection of chatter, which is one of the main barriers against titanium milling. State-of-the-art techniques are unable to satisfy requirements of industry in terms of in-process chatter detection. The present study reports the use of sensor-signal driven reconstructed phase space attractors combined with image correlation as a solution of chatter prediction during milling of titanium in industry. The method uses Poincaré sections of reconstructed phase space attractor as patterns to identify the onset of chatter in the apparently random behavior of vibrations in the milling process. Image correlation of Poincaré sections indicates the onset of chatter in the milling process.
This research is to parameterize the variation in reconstructed phase space attractor Poincaré sections during the milling process in order to identify the transition of system from stable to unstable condition. Vibration is continuously acquired during the milling process and converted to the form of reconstructed time series. A regression model is developed to compute the trend of changes in the reconstructed phase space attractor Poincaré sections and output a numerical value indicating the level of stability. A threshold value of the trend value defines the boundary of stable and unstable states of milling process. The method monitors the state of system without the necessity to have analytical relationship between cutting parameters and milling dynamics. It can also be used as an online monitoring process to detect the onset of chatter.
Self-excited vibration or chatter is the main barrier against milling process. Many techniques have been proposed in order to detect chatter during milling. However, they have some limitations in detection of chatter or using in industry.
This paper addresses if can detect chatter during milling process using image correlation. Image correlation is a method of tracking and image registration for 2D and 3D measurements of changes in images. This method is often used to measure any deformation, displacement, or define any changes during an engineering process.
At this research, Poincaré sections are plotted for milling system by reconstruction of phase space. Then, variation of Poincaré maps is measured and parameterized by image correlation technique using Pearson coefficient.
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