The aim of this study is to develop a reliable monitoring system for cutting tools in end milling. In this research, cutting force sensor and a vision system are used to monitor milling operations. ...The fundamental challenge to research is to develop a single-sensor monitoring system, reliable as a commercially available system, but much cheaper than the multi-sensor approaches. The cutting forces are measured with piezoelectric table dynamometer. Optical visual system is used to observe the actual tool conditions after the machining tests. The force sensor signals are then sent to the neuro-fuzzy algorithm, which is trained to determine the tool condition and the amount of tool wear. A neuro-fuzzy algorithm is investigated, to identify the parameters of membership functions, the set of rules and the output weights. The trained adaptive neuro-inference system is also used to discriminate different malfunction states from measured signals. By developed tool condition monitoring system, the machining process can be on-line monitored and stopped for tool change based on a pre-set tool-wear limit. The developed system is used to monitor milling operations and provide warnings to operator, to minimize tool breakage. The effectiveness of tool condition monitoring in ball end milling is investigated through several cutting experiments.
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