Investigation of kerf deviations and process parameters during laser machining of basalt-glass hybrid composite

被引:22
作者
Jain, Akshay [1 ]
Singh, Bhagat [1 ]
Shrivastava, Yogesh [1 ]
机构
[1] Jaypee Univ Engn & Technol, Mech Engn Dept, AB Rd, Raghogarh, Guna, India
关键词
basalt fiber; glass fiber; hybrid composite; ANN; ARTIFICIAL NEURAL-NETWORK; CUTTING ZONE PREDICTION; CUT QUALITY; FIBER; OPTIMIZATION; MACHINABILITY; METHODOLOGY; STRENGTH; ROPES; RODS;
D O I
10.2351/1.5111369
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the present work, basalt and glass layered hybrid composite has been fabricated and thereafter its various mechanical properties have been tested. It has been observed that this hybrid fiber composite has better mechanical properties as compared to basalt fiber reinforced plastic and glass fiber reinforced plastic. Conventional machining methods have various limitations such as delamination, burr formation, fiber pullout, etc., which result in poor cut surface quality and degraded mechanical performance. Laser beam machining can be one of the alternatives because of its noncontact nature and requirement of low specific energy with higher production rate. However, in order to achieve better cut quality with high precision and accuracy during laser beam machining, selection of favorable range and levels of cutting parameters is quite pertinent. In the present study, an artificial neural network has been used to develop the mathematical models of kerf deviations in terms of input cutting, viz., lamp current, pulse frequency, cutting speed, pulse width, and compressed air pressure. Well correlation between the predicted and experimental values validates the proposed methodology of ascertaining favorable process parameters during laser machining of basalt-glass hybrid composite.
引用
收藏
页数:17
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