Acoustic Emission Monitoring of Diamond Wheel Wearwith Grinding Alumina Ceramics Grinding

GUO Li, DENG YU, HUO Keke

Abstract

Research progress of monitoring engineering ceramics grinding by acoustic emission (AE) is firstly described. It is found that the study of grinding diamond wheel wear monitoring is normally based on the analysis of the root mean square of acoustic emission signal, and the accuracy of acoustic emission monitoring is not high. In order to promote the accuracy of acoustic emission monitoring for wear states of grinding diamond wheel, support vector machine is applied to establish the classification model of grinding diamond wheel wear states. Through the analysis of acoustic emission signals, it is found that the strongest spectral energy of alumina ceramic acoustic emission signal under precision grinding is in 30~40 kHz band. The AE signal spectrum of the diamond grinding wheel wear states including mild wear, serious wear and after dressing are significantly different. The wavelet decomposition coefficient variances of the grinding acoustic emission signal can well reflect the wear states of the grinding diamond wheel. Therefore, the wavelet decomposition coefficient variances of grinding acoustic emission signal is applied as the input characteristics of support vector machine to identify grinding diamond wheel wear states, and the accuracy of classification test is 100%.

 

Keywords: alumina grinding,  grinding diamond wheel wear,  acoustic emission monitoring,  wavelet analysis,  support vector machine


Full Text:

PDF


References


GUO Li, YIN Shaohui.LI Bo et al. Investigation of acoustic e-mission signals under a simulative environment of grinding burn [ J ]. China Mechanical Engineering, 2009 , 20 ( 4 ) : 413 - 416. (In Chinese)

MOHAMED Arif, FOLKES Janet, CHEN Xun. Detection of grinding temperature using laser irradiation and acoustic emission sensing technique [ J]. Materials and Manufacturing Processes, 2012,27:1 - 6.

AKBARI Javad. STAITO Yoshio, HANAOKA Tadaaki.,et al. Effect of grinding parameters on acoustic emission signals while grinding ceramics [J]. Journal of Materials Processing Technology, 1996,62; 403 - 407.

HWANG T W, WHITENTON E P. HSU N N. et al. Acoustic emission monitoring of high speed grinding of silicon nitride [J]. Ultrasonics, 2000, 38:614 - 619.

SUS1C Egon, GRABEC Igor. Characterization of the grinding process by acoustic emission [J] . International Journal of Machine Tools & Manufacture,2000,40:225 - 238.

WEBSTER J, DONG W P, LINDSAY R. Raw acoustic emission signal analysis of grinding process [J]. Annals of the CIRP'1996, 45(1); 335-340.

LIU Guijie, WANG Qiang. KANG Renke. Study on the wavelet transform based monitor signal processing method for grinding wheel dull [J] . Key Engineering Materials,2008(375/ 376) ;598 -602.

MOKBEL Amin A. MAKSOUD T M A. Monitoring of the condition of diamond grinding wheels using acoustic emission technique [j]. Journal of Materials Processing Technology. 2000, 101:292 - 297.

LIAO T W, TING Ñ F, QU J, et al. A wavelet-based methodology for grinding wheel condition monitoring J]. International Journal of Machine Tools & Manufacture, 2007,47;580-592.

LIAO T W. Feature extraction and selection from acoustic e-mission signals with an application in grinding wheel condition monitoring[J . Engineering Applications of Artificial Intelligence, 2010, 23;74 - 84.

YANG Zhensheng, YU Zhonghua. Grinding wheel wear monitoring based on wavelet analysis and support vector machine JJ. International Journal of Advanced Manufacture Technology,2012, 62: 107- 121.

TAWAKOLZ Taghi. Developments in grinding process monitoring and evaluation of results [J]. Int J Mechatronics and Manufacturing Systems,2008.1(4) :307 - 320.


Refbacks

  • There are currently no refbacks.