Development of moire fringe recognition system using artificial neural network for 2 d displacement measurement
| dc.contributor.author | Woo Wing Hon | |
| dc.date.accessioned | 2021-11-10T08:16:56Z | |
| dc.date.available | 2021-11-10T08:16:56Z | |
| dc.date.issued | 2018-04-01 | |
| dc.description.abstract | Various methods have been proposed in the analysis of moiré pattern. These methods can be categorized into manual inspection by human inspector, computational methods and image analysis based methods. Manual interpretation of moiré patterns is prone to human errors as it is highly dependent on the decision of the human inspector. The computational methods are lack of flexibility as they are limited to high frequency gratings which are sinusoidal in the transmittance of grating. As for the image analysis based methods, complex algorithms can unintentionally remove the fine details in the moiré patterns and cause uncertainty in the analysis. To overcome the above mentioned drawbacks, an artificial neural network (ANN) approach is proposed for a moiré fringe recognition system in 2-D displacement measurement. The moiré fringe recognition system consists of two ANNs with two different tasks : (i) the determination of moiré fringe centers of the circular grating moiré patterns and (ii) the determination of eccentricity magnitudes and eccentricity directions of the circular grating moiré patterns. The ANN approach is compared to graphical analysis method (GAM), an image analysis based method, in terms of accuracy and computational time for 2-D displacement measurement of circular grating moiré patterns. The experiments prove that ANN approach has a higher accuracy to GAM with mean errors with 95% confidence of 0.068 ± 0.013 mm for eccentric magnitudes and 1.85 ± 0.465º. An improvement of 66.18% in the computation time is also reported in the comparison. A straightforward solution for the moire fringe recognition system of circular grating moire pattern is achieved using ANN approach. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/14357 | |
| dc.language.iso | en | en_US |
| dc.title | Development of moire fringe recognition system using artificial neural network for 2 d displacement measurement | en_US |
| dc.type | Thesis | en_US |
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