TY - GEN
T1 - Inspecting LED micro structure by piezo servo system
AU - Huang, Yi-Cheng
AU - Chuang, Kai Chu
AU - Lin, Mou Sheng
AU - Chen, Chi Fan
PY - 2005/12/1
Y1 - 2005/12/1
N2 - The aim of this paper is to develop the detection system for present fast-developing LED (Light Emitted Diode) photoelectric Industry. To cope with the processing size of next generation dwindles, the gear of the inspection equipment in ultra precision and fast inspection specifications will become one of the important research keys. This paper presents a machine vision to inspect LED micro-structure by piezo actuation stage, while implemented vision system is used for feedback control of the planar motor. Ultra precision and fast positioning for searching the LED Pad/Die is achieved by using the features of piezoelectric actuator (PEA) that is embedded In the probing stage. Such piezo-actuated probing stage is controlled by using feed-forward neural network (FFNN) learning algorithm to compensate for the nonlinear and hysteresis properties of piezoelectricity. Experimental results show each LED Pad/Die can be finished lighting within the rate of 4 pieces per second of one probe. This work validates a new inspection machine structure and demonstrates the feasibility on future multi probes for next manufacturing in lower dimensions.
AB - The aim of this paper is to develop the detection system for present fast-developing LED (Light Emitted Diode) photoelectric Industry. To cope with the processing size of next generation dwindles, the gear of the inspection equipment in ultra precision and fast inspection specifications will become one of the important research keys. This paper presents a machine vision to inspect LED micro-structure by piezo actuation stage, while implemented vision system is used for feedback control of the planar motor. Ultra precision and fast positioning for searching the LED Pad/Die is achieved by using the features of piezoelectric actuator (PEA) that is embedded In the probing stage. Such piezo-actuated probing stage is controlled by using feed-forward neural network (FFNN) learning algorithm to compensate for the nonlinear and hysteresis properties of piezoelectricity. Experimental results show each LED Pad/Die can be finished lighting within the rate of 4 pieces per second of one probe. This work validates a new inspection machine structure and demonstrates the feasibility on future multi probes for next manufacturing in lower dimensions.
UR - http://www.scopus.com/inward/record.url?scp=33748907188&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33748907188&partnerID=8YFLogxK
U2 - 10.1109/ICMECH.2005.1529244
DO - 10.1109/ICMECH.2005.1529244
M3 - Conference contribution
AN - SCOPUS:33748907188
SN - 0780389980
SN - 9780780389984
T3 - Proceedings of the 2005 IEEE International Conference on Mechatronics, ICM '05
SP - 151
EP - 156
BT - Proceedings of the 2005 IEEE International Conference on Mechatronics, ICM '05
T2 - 2005 IEEE International Conference on Mechatronics, ICM '05
Y2 - 10 July 2005 through 12 July 2005
ER -