Consistency evaluation of hole series surface quality using vibration signal

Surface roughness assessment on hole drilled through the identification and clustering of relevant external and internal signal statistical features

“…Partitional Around Medoids (PAM) algorithm was used by Li et al [34] for tool wear state clustering in milling operations showing its superiority over k means and fuzzy c means algorithms based on cutting force signal. Zhou et al [35] used vibration signal time-frequency features and fuzzy c means algorithm to classify 3 roughness Ra ranges in the drilling operation. Kubišová et al [36] used hierarchical clustering to compare original surface roughness with replicated surface roughness based on Euclidean distances of various roughness parameters showing that it can be a good tool for replicability measurements of obtained surface profiles.…”