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FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.
Miguel Trejo-Hernandez1, Roque Alfredo Osornio-Rios1, Rene de Jesus Romero-Troncoso1
1HSPdigital-CA Mecatronica, Facultad de Ingenieria Campus San Juan del Rio, Universidad Autonoma de Queretaro, Rio Moctezuma 249, San Cayetano, C.P. 76807, San Juan del Rio, Qro., Mexico.
Sensors (Basel, Switzerland)
|February 10, 2012
Summary
This study developed a smart-sensor using FPGA to estimate flank wear in CNC machine inserts. Fusing servoamplifier current and accelerometer data achieved three times better accuracy than individual sensors.
Area of Science:
- Manufacturing Engineering
- Sensor Technology
- Machine Condition Monitoring
Background:
- Manufacturing demands increased productivity, quality, and cost-efficiency.
- Accurate monitoring of cutting tool wear is crucial for process optimization.
- Existing methods for flank wear estimation have limitations in real-time accuracy.
Purpose of the Study:
- To develop a fused smart-sensor system for online quantitative estimation of flank wear area.
- To leverage FPGA technology for enhanced sensor data processing.
- To improve the accuracy of flank wear estimation in CNC machining.
Main Methods:
- Development of a fused smart-sensor system.
- Integration of FPGA for real-time data processing.
- Utilizing servoamplifier current and 3-axis accelerometer data.
- Experimental validation of the sensor fusion approach.
Main Results:
- The fused smart-sensor effectively estimates flank wear area online.
- Sensor fusion significantly improves accuracy compared to individual sensor data.
- Achieved three times better accuracy by combining current and vibration signals.
Conclusions:
- The developed FPGA-based fused smart-sensor offers a superior method for flank wear estimation.
- This technology enhances CNC machining efficiency and quality.
- Sensor fusion is a promising approach for advanced machine condition monitoring.
