SENSORLESS DETECTION OF TOOL BREAKAGE IN MILLING

One of the most important research topics in the area of Intelligent Manufacture Systems (IMS) is the automatic detection of tool breakage, wear of chipping during the cutting process. Sensor-based techniques are available for cutting force measurements, but there are drawbacks in this approach in cost and idle times. This work proposes a sensorless monitoring system for tool monitoring in order to detect breakage and chipping by exploiting the wavelet transform and a neural network. Previous works have made use of these tools for monitoring several machining parameters, but we propose an integrated low-cost approach to detect quickly the changes in the tool integrity for monitoring. The system output produces an accurate detection of the tool integrity that enables the system to prevent damage due to tool breakage. This approach allows for an industrial solution to be developed.     

SENSORLESS DETECTION OF TOOL BREAKAGE IN MILLING

One of the most important research topics in the area of Intelligent Manufacture Systems (IMS) is the automatic detection of tool breakage, wear of chipping during the cutting process. Sensor-based techniques are available for cutting force measurements, but there are drawbacks in this approach in cost and idle times. This work proposes a sensorless monitoring system for tool monitoring in order to detect breakage and chipping by exploiting the wavelet transform and a neural network. Previous works have made use of these tools for monitoring several machining parameters, but we propose an integrated low-cost approach to detect quickly the changes in the tool integrity for monitoring. The system output produces an accurate detection of the tool integrity that enables the system to prevent damage due to tool breakage. This approach allows for an industrial solution to be developed.