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ANFIS based model to forecast the Wire-EDM parameters for machining an Ultra High Temperature Ceramic composite

机译:基于ANFIS的模型预测加工超高温陶瓷复合材料的线EDM参数

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In this work,a ZrB2 based ceramic composites with 25 wt.% B4C sintered in spark plasma sintering furnace at 2000°C for 10 min under 50 MPa pressure has been machined with Wire electrical discharge machine(WEDM)and can readily be cut to intricate shapes to meet the requirements of industry.The adaptive neuro fuzzy inference systems(ANFIS)has been used to generate mapping relation between input parameters and output responses.ANFIS is a neuro fuzzy technique where the fusion is made between the neural network and the fuzzy inference system.Also the ANFIS models have been tested by a confirmative test and the results shows minimum root mean square error(RMSE)as 0.0416 for kerf width and 0.9605 for machining speed.This verification indicates that ANFIS modeling can be used to forecast the responses.
机译:在这项工作中,基于ZrB2的陶瓷复合材料,其中25重量%。在火花等离子体烧结炉中烧结在2000℃下,在50MPa压力下加工10分钟,用电线电放电机(WEDM)加工,并且可以容易地切割复杂以满足行业要求的形状。自适应神经模糊推理系统(ANFIS)已被用于在输入参数和输出响应之间产生映射关系.ANFIS是一种神经模糊技术,其中融合在神经网络和模糊推理之间进行融合System.ALSO通过确认测试测试了ANFIS模型,结果显示了KERF宽度的最小根均方误差(RMSE),为0.0416,用于加工速度为0.9605.这验证表明ANFIS建模可用于预测响应。

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