科研之友
微信
新浪微博
Facebook
分享链接
摘要
Tool condition monitoring (TCM) systems employed in industry are mostly used to detect tool fracture, although the prevention of it should be the principal aim. This would not only allow for the avoidance of any fracture-related damage to both the workpiece and machine tool, but also for recondition the tool for further use. This paper presents a strategy, which utilises several features extracted from the spindle power and acoustic emission (AE-RMS) signals recorded when drilling small deep holes using twist drills in order to predict an imminent tool failure. A key to achieving this is the subdivision of the drilling cycle into sections and only monitoring those sections in which the most significant change occurs over the tool life. By doing this it is possible to identify the final (i.e. tertiary) tool life stage and replace the worn out tool shortly before fracture occurs, thus improving the overall tool utilisation to. Of 24 drills tested, the TCM system was able to utilise an average of 84% of the tool life: in only one case it failed to detect tool breakage.
- 出版日期2012-1
