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All Outputs (68)

A wireless instrumented milling cutter system with embedded PVDF sensors (2018)
Journal Article
Luo, M., Luo, H., Axinte, D., Liu, D., Mei, J., & Liao, Z. (2018). A wireless instrumented milling cutter system with embedded PVDF sensors. Mechanical Systems and Signal Processing, 110, https://doi.org/10.1016/j.ymssp.2018.03.040

Among all the monitoring data which could be captured in a machining process, the cutting forces could convey key knowledge on the conditions of the process. When the machining involves a single cutting edge the relationship between the output forces... Read More about A wireless instrumented milling cutter system with embedded PVDF sensors.

A novel cutting tool design to avoid surface damage in bone machining (2017)
Journal Article
Liao, Z., Axinte, D. A., & Gao, D. (2017). A novel cutting tool design to avoid surface damage in bone machining. International Journal of Machine Tools and Manufacture, 116, 52-59. https://doi.org/10.1016/j.ijmachtools.2017.01.003

With its anisotropic structure, bone machining occurs as shear/serrated cutting mechanisms at low values of uncut chip thickness while at high values it results in fracture cutting mechanisms which lead to significant tissues damages; hence, utilisin... Read More about A novel cutting tool design to avoid surface damage in bone machining.

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. https://doi.org/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.

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.

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.

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.