Improving the dressing accuracy and efficiency of profile grinding wheels has been increasingly demanded. The significance is addressed in the practical application of precision engineering. In this study, an online dressing system of profile grinding wheels is introduced. A special feature of the system is the application of the non-contact image measuring method used to evaluate deviation of the grinding wheel’s edge in determining the timing and amount of dressing. Diamond form rollers were selected to generate the profile grinding wheels with steep profile flanks by taking advantage of their high flexibility, short dressing times, and low wear rate. A series of grinding and dressing tests were carried out to investigate the dressing accuracy and surface quality for the profile grinding wheels with the proposed system. Through repeated experimental investigations, it was found that the dressing force is a key parameter in determining the number of passes needed in achieving high efficiency dressing. This is to assure that the length of the dressing time, and waste of the dresser and grinding wheel can be minimized. Other main dressing conditions that influence the grinding wheel and workpiece roughness include speed ratio, cross feed and roller profile radius.
[1]
E. Brinksmeier,et al.
Characterization of Dressing Processes by Determination of the Collision Number of the Abrasive Grits
,
1995
.
[2]
E. Saljé,et al.
Dressing of Conventional and CBN Grinding Wheels with Diamond Form Rollers
,
1984
.
[3]
Ichiro Inasaki.
Monitoring and Optimization of Internal Grinding Process
,
1991
.
[4]
Tabatabai Yazdi,et al.
EDGE LOCATION AND DATA COMPRESSION FOR DIGITAL IMAGERY
,
1981
.
[5]
Junji Shibata,et al.
Characteristics of Air Flow Around a Grinding Wheel and Their Availability for Assessing the Wheel Wear
,
1982
.
[6]
Kuang-Chao Fan,et al.
On-Line Non-Contact System for Grinding Wheel Wear Measurement
,
2002
.
[7]
João Fernando Gomes de Oliveira,et al.
Dimensional Characterization of Grinding Wheel Surface through Acoustic Emission
,
1994
.
[8]
K. Okamura,et al.
Monitoring of Dressing and Grinding Processes with Acoustic Emission Signals
,
1985
.