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The use of a novel auto-focus technology based on a GRNN for the measurement system for mesh membranes

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Abstract

Mesh membranes are widely used in nebulizers for inhalation therapy in the medical industry and in piezoelectric actuators for humidifiers, so the most important dimension of a mesh membrane is the diameter of the circular holes. Traditionally, a number of holes in a mesh membrane and non-coplanar mesh membrane array are manually inspected, which is expensive and time consuming. To address this problem, this study develops a novel auto-focus measurement system, which includes the hardware and software systems. The hardware system is composed of the modules for the motion stage and the auto-focus optical mechanism. The software system consists of two phases: (1) training the general regression neural network (GRNN) for auto-focus technology, in the offline phase, and (2) automatically capturing sharp mesh images using a GRNN and reliably measuring holes using the three measurement algorithms, in the online phase. The results of the experiments confirm that the proposed auto-focus technology, which uses a GRNN, obtains the correct focus position. The accuracy of the measurement of the diameter of a hole can reach 0.89 μm, the successful measure rate is almost 98 % and the average measurement time is 4.8 s per mesh. These results show that the proposed system is not only robust for auto-focus technology, but also efficient and effective for the measurement of mesh membrane arrays.

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Acknowledgments

This research was performed with the support of LIGA Precision Technology Co. Ltd., Taiwan, ROC. The authors particularly thank the LIGA Precision Technology Co. Ltd. for providing the test samples and for sharing valuable experience of mesh membrane arrays.

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Correspondence to Chin-Sheng Chen.

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Chen, CS., Weng, CM., Lin, CJ. et al. The use of a novel auto-focus technology based on a GRNN for the measurement system for mesh membranes. Microsyst Technol 23, 343–353 (2017). https://doi.org/10.1007/s00542-015-2473-z

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  • DOI: https://doi.org/10.1007/s00542-015-2473-z

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