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Chaotic characteristics of tool wear signal during metal cutting process |
GUAN Shan,PENG Chang |
Northeast DianLi University, School of Mechanical Engineering, Jilin 132012, China |
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Abstract Aiming at the nonlinear characteristics of acoustic emission signal from tool wear, a method of signal analyzing and feature extracting based on chaos theory is presented. In this paper, the following two research work are firstly finished, the phase space reconstruction of denoised time series by delay time method and the analysis of the variation of delay time and embedding dimension with tool wear. Then, the variation of the three chaotic characteristic parameters including correlation dimension, the maximum Lyapunov exponent and Kolmogorov entropy with the increase of the amount of tool wear under different cutting conditions is analysed. The results show that the acoustic emission signal from tool wear has obvious chaos character, moreover the above three chaotic characteristic parameters, delay time and embedding dimension have significant corresponding relationship with the state of tool wear so that they can be used as parameters for condition monitoring and prediction of the amount of tool wear.
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Received: 19 March 2014
Published: 25 May 2015
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[1] 关贞珍,郑海起,杨支涛,等. 基于非线性几何不变量的轴承故障诊断方法研究[J]. 振动与冲击,2009, 28(11):130-133.
GUAN Zhen-zhen, ZHENG Hai-qi, YANG Zhi-tao,
et al. Fault diagnosis of bearing based on nonlinear time series of geometrical invariants[J].Journal of Vibration and Shock, 2009, 28(11): 130-133.
[2] 张雨. 柴油机活塞环胶结信息的符号李指数含噪辨识[J]. 内燃机学报, 2010,28(1): 90-95.
ZHANG Yu. Identification of information of diesel piston ring sticking with noise based on symboilic-lyapunov index[J]. Transactions of CSICE, 2010,28(1):90-95.
[3] 马晋, 江志农,高金吉. 基于混沌分形理论的特征提取技术在气阀故障诊断中应用[J]. 振动与冲击,2012, 31(19):26-30.
MA Jin, JIANG Zhi-nong, GAO Jin-ji. Feature extraction method based on chaotic fractal theory and its application in fault diagnosis of gas valves[J]. Journal of Vibration and Shock, 2012, 31(19): 26-30.
[4] Xue Jie-ni, Shi Zhong-ke. Short-time traffic flow prediction based on chaos time series theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2008,8(5): 68-72.
[5] 史丽晨, 段志善. 基于混沌-分形理论的往复式活塞隔膜泵磨损故障分析[J]. 农业机械学报,2010, 41(4): 222-226.
SHI Li-chen, DUAN Zhi-shan. Wearing fault diagnosis of reciprocating membrane pump based on chaos and fractal theory[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010,41(4):222-226.
[6] Guo Jun, Zhou Jian-zhong, Qin Hui,et al. Monthly streamflow forecasting based on improved support vector machine model[J]. Expert Systems with Application, 2011, 38(10): 13073-13081.
[7] 张蕾. 非线性时间序列的高阶统计特征提取和趋势分析[D]. 沈阳:沈阳航空航天大学, 2013.
[8] 张锴锋,袁惠群,聂鹏. 基于广义分形维数的刀具磨损状态监测[J]. 振动与冲击, 2014,33(1):162-164.
ZHANG Kai-feng,YUAN Hui-qun,NIE Peng.Tool wear condition monitoring based on generalized fractal dimensions[J].Journal of Vibration and Shock, 2014, 33(1):162-164.
[9] Shi Jing-zhuo, Zhao Fu-jie, Shen Xiao-xi,et al. Chaotic operation and chaos control of traveling wave ultrasonic montor[J]. Ultrasonics, 2013,53(6):1112- 1123.
[10] Ma Hui-zhu, Li Cheng-xiang. Research on parameters estimation of sea clutter in data preprocessing[J]. Optik-International Journal for Light and Electron Optics, 2013,124(5):901-905.
[11] Nie Zhen-hua, Hao Hong, Ma Hong-wei. Structural damage detection based on the reconstructed phase space for reinforced concrete slab: Experimental study[J]. Journal of Sound and Vibration, 2013, 332(4):1061-1078.
[12] Patel V N, Tandon N, Pandey P K. Defect detection in deep groove ball bearing in presence of external vibration using envelope analysis and duffing oscillator[J]. Measurement, 2012, 45(5):960-970.
[13] 于大鹏,赵德有. 螺旋桨鸣音的混沌动力特性研究[J]. 振动与冲击,2009,28(12): 47-52.
YU Da-peng, ZHAO De-you. Chaotic dynamics of propeller singing[J]. Journal of Vibration and Shock, 2009, 28(12): 47-52.
[14] Shayegh F, Sadri S, Amirfattahi R, et al. A model- based method for computation of correlation dimension, Lyapunov exponents and symchronization from depth-EEG signals[J]. Computer methods and programs in biomedicine, 2014,113(1):323-337.
[15] 修妍. 混沌时序分析中的若干问题及其应用研究[D]. 天津:天津大学, 2007.
[16] 张英堂,任国全,李国璋. 柴油机振动信号分形特征诊断的改进算法[J].内燃机学报,2006,24(5):459- 464.
ZHANG Ying-tang, REN Guo-quan, LI Guo-zhang. Improved algorithm of diesel engine diagnosis based on fractal dimension of vibration signals[J]. Transactions of CSICE,2006,24(5):459-464.
[17] 杨永锋,仵敏娟,高喆,等.小数据量法计算最大Lyapunov指数的参数选择[J].振动、测试与诊断,2012, 32(3):371-374.
YANG Yong-feng, WU Min-juan, GAO Zhe, et al. Parameters selection for calculating largest lyapunov exponent from small data sets[J]. Journal of Vibration, Measurement & Diagnosis, 2012,32(3):371-374.
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