Structure estimation of deep neural network for triangulation displacement sensors

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Structure estimation of deep neural network for triangulation displacement sensors

Mizutani, Y.; Kataoka, S.; Nagai, Y.; Uenohara, T.; Takaya, Y.

CIRP annals, 2022, 2022-00-00, Volume: 71, Issue: 1

Journal Article

The structure of deep neural networks (DNNs) used in triangulation displacement sensors was investigated via numerical and experimental analyses. After measuring the fluctuation of the actual measurements in experiments, a numerical model of the measurements was constructed by adding normally distributed noise to the ideal waveform to build a training data set. The structure of the DNNs was optimized by evaluating the major components of the DNNs by numerical calculations. The DNNs were then installed in a measurement system for distance measurement with sub-pixel accuracy.

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Mizutani, Y. | Kataoka, S. | Nagai, Y. | Uenohara, T. | Takaya, Y.

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