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Multi-scale hybrid HMM for tool wear condition monitoring (2015)
Journal Article
Liao, Z., Gao, D., Lu, Y., & Lv, Z. (2016). Multi-scale hybrid HMM for tool wear condition monitoring. International Journal of Advanced Manufacturing Technology, 84(9-12), 2437-2448. doi:10.1007/s00170-015-7895-3

In a machining system, accurate tool wear condition monitoring is paramount for guaranteeing the quality of the workpiece and tool life. Cutting force signal is the most commonly used signal to depict the tool wear variation during the machining proc... Read More about Multi-scale hybrid HMM for tool wear condition monitoring.

On monitoring chip formation, penetration depth and cutting malfunctions in bone micro-drilling via acoustic emission (2015)
Journal Article
Liao, Z., & Axinte, D. A. (2016). On monitoring chip formation, penetration depth and cutting malfunctions in bone micro-drilling via acoustic emission. Journal of Materials Processing Technology, 229, 82-93. https://doi.org/10.1016/j.jmatprotec.2015.09.016

Micro-drilling of bone is increasing demanded in many kinds of surgery operations recently. One of the mainly challenges in this procedure is to control the drilling process and avoid the surrounding tissue damage. Monitoring the cutting condition is... Read More about On monitoring chip formation, penetration depth and cutting malfunctions in bone micro-drilling via acoustic emission.

Tool Wear Identification in Turning Titanium Alloy Based on SVM (2014)
Journal Article
Liao, Z. R., Li, S. M., Lu, Y., & Gao, D. (2014). Tool Wear Identification in Turning Titanium Alloy Based on SVM. Materials Science Forum, 800-801, 446-450. https://doi.org/10.4028/www.scientific.net/MSF.800-801.446

Titanium alloy is difficult cutting materials, the samples of toolwear features are hard to acquire because of short tool life. In terms of the characteristic, Support Vector Machine (SVM) is proposed in this paper to monitor tool condition, the ener... Read More about Tool Wear Identification in Turning Titanium Alloy Based on SVM.

Cutting Force Analysis in Tool Condition Monitoring of Difficult to Cut Materials (2014)
Journal Article
Liao, Z. R., Gao, D., & Lu, Y. (2014). Cutting Force Analysis in Tool Condition Monitoring of Difficult to Cut Materials. Materials Science Forum, 800-801, 175-179. https://doi.org/10.4028/www.scientific.net/MSF.800-801.175

Tool wear condition monitoring has been an effective method in improving the production efficiency and process automation. In this paper, to analysis the cutting force features in tool wear condition monitoring of difficult to cut materials, we first... Read More about Cutting Force Analysis in Tool Condition Monitoring of Difficult to Cut Materials.

Research of Detection and Control System for Lunar Dust Effects Simulator (2012)
Journal Article
Liao, Z. R., Zhou, L., Gao, D., Zhang, X. L., & Yin, M. L. (2012). Research of Detection and Control System for Lunar Dust Effects Simulator. Advanced Materials Research, 426, 126-130. https://doi.org/10.4028/www.scientific.net/AMR.426.126

To simluate the effects of lunar dust environment veritably by using lunar dust effects simulator, a detection and control system based on singlechip microcomputer was developed. In this system, peripheral circuits with stepper motor driver, temperat... Read More about Research of Detection and Control System for Lunar Dust Effects Simulator.