论文信息 - Sensor Fusion Strategy in the Monitoring of Cutting Tool Wear

Sensor Fusion Strategy in the Monitoring of Cutting Tool Wear

Cutting tool wear is a major problem in machining processes. It has a great effect on the quality of a workpiece. Thus, monitoring cutting tool wear is very important in order to maintain the workpiece quality as well to reduce production rate and production time. The use of a single sensor in a monitoring system may not be accurate to detect cutting tool wear. In this paper, sensor fusion technology is introduced for monitoring cutting tool wear.

Hideki Aoyama | Zahari Taha | Djoko Suharto | Kimiyuki Mitsui | Muslim Mahardika

[1] Laura Ignizio Burke,et al. Automated identification of tool wear states in machining processes: an application of self-organizing neural networks , 1989 .

[2] Ranga Komanduri,et al. Frequency and time domain analyses of sensor signals in drilling—II. Investigation on some problems associated with sensor integration , 1995 .

[3] D. E. Dimla,et al. Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods , 2000 .

[4] D. E. Dimla,et al. On-line metal cutting tool condition monitoring.: II: tool-state classification using multi-layer perceptron neural networks , 2000 .

[5] Tae Jo Ko,et al. Cutting state monitoring in milling by a neural network , 1994 .

[6] R. Krishnamurthy,et al. Modelling of tool wear based on cutting forces in turning , 1993 .

[7] Ralph Tanner,et al. A toxonomy of multi-sensor fusion , 1992 .

[8] M. F. DeVries,et al. Neural Network Sensor Fusion for Tool Condition Monitoring , 1990 .