Abstract
There are many tool condition monitoring solutions that use a variety of sensors. This paper presents a self-powering wireless sensor node for shank-type rotating tools and a method for real-time end mill wear monitoring. The novelty of the developed and patented sensor node is that the longitudinal oscillations, which directly affect the intensity of the energy harvesting, are significantly intensified due to the helical grooves cut onto the conical surface of the tool holder horn. A wireless transmission of electrical impulses from the capacitor is proposed, where the collected electrical energy is charged and discharged when a defined potential is reached. The frequency of the discharge pulses is directly proportional to the wear level of the tool and, at the same time, to the surface roughness of the workpiece. By employing these measures, we investigate the support vector machine (SVM) approach for wear level prediction.
Highlights
During the machining process, severe tool wear can lead to quality degradation of the workpiece or to the breakage of the tool itself, resulting in unexpected production downtime, or even in damage to the equipment or injuries to the operator [1]
The results show that the transducer, when embedded together with the tool holder with helical slots on its surface, generates a significantly higher output power over frequency range where the longitudinal and torsional (L&T) mode coupling effect is present, compared to the case where a tool holder without helical grooves is used instead
This study presents the design of a sensor node employing piezoelectric energy harvesting for wear detection in rotating shank-type tools
Summary
Severe tool wear can lead to quality degradation of the workpiece or to the breakage of the tool itself, resulting in unexpected production downtime, or even in damage to the equipment or injuries to the operator [1]. During milling operation, when lubrication is applied, tool life is estimated to last 75 min, while the process of milling without lubrication cutter tool lifespan is expected to end after 45 min [3]. Sensors are deployed in order to directly or indirectly measure physical signals such as: cutting force, torque, vibration, acoustic emission, current and power, sound and temperature. These physical signals are evaluated for detection of tool wear, chatter or breakage conditions in real-time
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