An intelligent sensor fusion system for tool monitoring on a machining center

The objective of this paper is to construct an intelligent sensor fusion monitoring system for tool breakage on a machining center. Since none of the sensing and diagnosis techniques have proven to be completely reliable during practical operations. An intelligent tool monitoring system consisting of a neural-network-based algorithm and a sensor fusion system is proposed. The dual sensing signals of cutting force and acoustic emission are simultaneously used in the proposed system due to a good correlation existing between them. And, a self-learning neural-network algorithm is used to integrate multiple sensing information to make a proper decision of tool condition. The results show a good performance in tool breakage detection by the proposed monitoring system, especially, if there were higher interference existent.