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Monitoring of the Ceramic Kerf During the Laser Cutting Process through Piezoelectric Transducer
1 , 2 , * 2 , 2 , 2 , 2
1  São Paulo State University – UNESP – Faculty of Engineering, Department of Mechanical Engineering
2  São Paulo State University – UNESP – Faculty of Engineering, Department of Electrical Engineering

Abstract:

Advanced ceramics are widely used in industry due to their unique properties. However, the machining of ceramic components by conventional methods is difficult due to their high hardness and brittleness. In this sense, laser beam machining (LBM) is presented as an alternative to conventional methods, enabling the machining of workpieces through more accurate and less invasive techniques. Despite the advantages of laser machining, the process still needs to be studied in detail, as advanced ceramic machining is considered a stochastic process. Thus, real-time monitoring systems are required in order to optimize the ceramic laser machining. Therefore, this paper proposes a novel method for monitoring the cutting kerf in the laser cutting process of ceramic components using low-cost piezoelectric transducer (PZT) and digital signal processing. Tests were performed on the surface of an alumina ceramic workpiece under different machining conditions. The cutting kerf was measured by a digital microscope and the raw signals from the PZT transducer were collected at a sampling rate of 2 MHz. Time domain and frequency domain analyzes were performed in order to find a frequency band that best correlates with the process conditions. Finally, a linear regression was calculated in order to correlate the PZT signal and the measured kerf. The results showed that the piezoelectric transducer was sensitive to the acoustic activity generated during the process, allowing the real-time monitoring of the cutting kerf. Thus, the approach proposed in this paper can be used efficiently in the monitoring of the laser cutting process.

Keywords: laser machining; ceramic; piezoelectric transducer; monitoring; digital signal processing
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