Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing

被引:16
作者
de Agustina, Beatriz [1 ]
Maria Marin, Marta [1 ]
Teti, Roberto [2 ]
Maria Rubio, Eva [1 ]
机构
[1] Univ Nacl Educ Distancia, Dept Mfg Engn, Sch Ind Engn, E-28040 Madrid, Spain
[2] Univ Naples Federico II, Dept Mat & Prod Engn, I-80125 Naples, Italy
关键词
robot assisted polishing; surface roughness; acoustic emission signals; contact force; monitoring; PREDICTION; SYSTEM;
D O I
10.3390/s141121514
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The polishing process is the most common technology used in applications where a high level of surface quality is demanded. The automation of polishing processes is especially difficult due to the high level of skill and dexterity that is required. Much of this difficulty arises because of the lack of reliable data on the effect of the polishing parameters on the resulting surface roughness. An experimental study was developed to evaluate the surface roughness obtained during Robot Assisted Polishing processes by the analysis of acoustic emission signals in the frequency domain. The aim is to find out a trend of a feature or features calculated from the acoustic emission signals detected along the process. Such an evaluation was made with the objective of collecting valuable information for the establishment of the end point detection of polishing process. As a main conclusion, it can be affirmed that acoustic emission (AE) signals can be considered useful to monitor the polishing process state.
引用
收藏
页码:21514 / 21522
页数:9
相关论文
共 24 条
[11]   Automated polishing of die steel surfaces [J].
Huissoon, JP ;
Ismail, F ;
Jafari, A ;
Bedi, S .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2002, 19 (04) :285-290
[12]   Multi-sensor monitoring system in chemical mechanical planarization (CMP) for correlations with process issues [J].
Jeong, H. ;
Kim, H. ;
Lee, S. ;
Dornfeld, D. .
CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2006, 55 (01) :325-328
[14]   Signal analysis of the end point detection method based on motor current [J].
Kim, SY ;
Park, CJ ;
Seo, YJ .
MICROELECTRONIC ENGINEERING, 2003, 66 (1-4) :472-479
[15]   Computer-based monitoring of the polishing processes using LabView [J].
Klocke, F. ;
Dambon, O. ;
Schneider, U. ;
Zunke, R. ;
Waechter, D. .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2009, 209 (20) :6039-6047
[16]  
Lazarev R., 2012, THESIS U SO DENMARK
[17]   Precision manufacturing process monitoring with acoustic emission [J].
Lee, DE ;
Hwang, I ;
Valente, CMO ;
Oliveira, JFG ;
Dornfeld, DA .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2006, 46 (02) :176-188
[18]   A time-frequency acoustic emission-based monitoring technique to identify workpiece surface malfunctions in milling with multiple teeth cutting simultaneously [J].
Marinescu, Iulian ;
Axinte, Dragos .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2009, 49 (01) :53-65
[19]   Surface roughness characterisation using cutting force analysis, regression and neural network prediction models [J].
Nunez, P. J. ;
Simao, J. ;
Arenas, J. M. ;
de la Cruz, C. .
ADVANCES IN MATERIALS PROCESSING TECHNOLOGIE, 2006, 526 :211-216
[20]  
Pilny L., 2013, P 11 INT S MEAS TECH