Review on condition monitoring of Abrasive Water Jet Machining system
Condition monitoring of any machining system has become inevitable in order to achieve flexibility and automation. This work reviews on the research aspects in the condition monitoring of Abrasive Water Jet Machining (AWJM) system. Condition monitoring of the AWJM system helps to achieve an effectiv...
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Published in | 2015 International Conference on Robotics, Automation, Control and Embedded Systems (RACE) pp. 1 - 7 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
Hindustan University
01.02.2015
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Subjects | |
Online Access | Get full text |
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Summary: | Condition monitoring of any machining system has become inevitable in order to achieve flexibility and automation. This work reviews on the research aspects in the condition monitoring of Abrasive Water Jet Machining (AWJM) system. Condition monitoring of the AWJM system helps to achieve an effective utilization of the machine in order to increase productivity. AWJM is one of the non-traditional machining processes used to machine difficult-to-machine materials. It works on the principles of erosion of material by the action of high velocity water jet mixed with abrasive particles and air. The input parameters involved in the AWJM system are water jet pressure, abrasive flow rate, orifice diameter, nozzle diameter, particle size of the abrasive, abrasive type, etc. Researchers have carried out condition monitoring of AWJM system using different sensors such as Acoustic Emission (AE), accelerometer, cutting force dynamometer, sound, thermograms, etc. Among the sensors, it is observed that the AE sensor is widely used in AWJM system for monitoring. From the review, it is observed that the acquired sensor signals are correlated with output parameters such as nozzle wear, depth of cut, surface texture, jet energy, jet penetration, stand-off distance, etc. The future work recommends the condition monitoring of AWJM system using multi-sensory approach with suitable sensors. |
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DOI: | 10.1109/RACE.2015.7097254 |