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Unformatted text preview: imitations on accuracy [Hocken et al., 1993] [Hopp, 1993] and on stability. It is also very sensitive to number and location of the measured points. Minimization of the deviation zone, for sculptured and parametric surfaces, is highly non-linear. Since the analytical derivatives of the objective function are not usually available, a direct search method is required to solve the problem and its success is very dependent on the initial conditions [ElMaraghy et al., 2004]. The least square best fit is the most likelihood estimation used to fit the substitute geometry onto a set of discrete data. Since all the measurement points contribute to the best-fit result, the substitute geometry is more stable and less sensitive to the local deviations, asperities and local surface effects. However, least square best fit is a statistical estimation rather than an exact solution and some concerns always exist regarding interpretation of its fitting results. In this work, the advantages of both minimum deviation zone and least square fitting methods are exploited. 2.2. Data Sampling Research o...
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This note was uploaded on 08/03/2010 for the course DD 1234 taught by Professor Zczxc during the Spring '10 term at Magnolia Bible.
- Spring '10
- The Land