This paper starts at first describes in detail the analytical model developed by (Seneviratne et al.,1992; Ngemoh,1997; Seneviratne et al., 2001) and shows experimental setup for measuring torque vs insertion depth signature signals , then, justified by the good correspondence between model and experimental data, shows an integrated approach developed by the authors (Klingajay & Giannoccaro, 2003) Klingajay et al.,2003), for estimating some physical parameters of screw insertion. This approach is developed in Matlab development creating a Graphic User Interface (GUI) that manage signals from the sensors, estimates these required parameters of the insertion, with the aim of driving automatically screw insertion. Test results about the possibility of estimating four parameters of this model are shown in this paper using a non-linear optimization technique (Least Square optimisation technique). This technique works well considering the complexity of the model equations (Appendix 1) like shown by the authors (Klingajay & Giannoccaro, 2003) for this particular kind of estimation.

Calibration on internal thread gauge on a coordinate measuring machine

GIANNOCCARO, NICOLA IVAN;
2004-01-01

Abstract

This paper starts at first describes in detail the analytical model developed by (Seneviratne et al.,1992; Ngemoh,1997; Seneviratne et al., 2001) and shows experimental setup for measuring torque vs insertion depth signature signals , then, justified by the good correspondence between model and experimental data, shows an integrated approach developed by the authors (Klingajay & Giannoccaro, 2003) Klingajay et al.,2003), for estimating some physical parameters of screw insertion. This approach is developed in Matlab development creating a Graphic User Interface (GUI) that manage signals from the sensors, estimates these required parameters of the insertion, with the aim of driving automatically screw insertion. Test results about the possibility of estimating four parameters of this model are shown in this paper using a non-linear optimization technique (Least Square optimisation technique). This technique works well considering the complexity of the model equations (Appendix 1) like shown by the authors (Klingajay & Giannoccaro, 2003) for this particular kind of estimation.
2004
9783901509384
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/327380
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