Chatter prediction using merged wavelet denoising and ANFIS

被引:16
作者
Kumar, Shailendra [1 ]
Singh, Bhagat [1 ]
机构
[1] Jaypee Univ Engn & Technol, Dept Mech Engn, AB Rd, Raghogarh, Guna, India
关键词
Chatter; Wavelet denoising; ANFIS; Chatter index; SURFACE-ROUGHNESS PREDICTION; FUZZY INFERENCE SYSTEM; IDENTIFICATION; OPTIMIZATION; STABILITY; MODEL;
D O I
10.1007/s00500-018-3099-8
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
Inexpedient vibration between cutting tool and work piece promotes regenerative chatter in turning process. Generally, acquired chatter signals are contaminated with ambient noise. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform. Further, in order to quantify the chatter severity a new parameter called chatter index has been evaluated considering aforesaid denoised signals at different levels of cutting parameters as inputs. Moreover, these input and output parameters have been considered to train the chatter phenomenon using adaptive neuro-fuzzy inference system. Developed technique has been validated by performing more experiments. Hence, a new idea for identification and quantification of chatter has been proposed which will be very efficient in suppression of chatter.
引用
收藏
页码:4439 / 4458
页数:20
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