Highly precise signal-subdivision method of grating based on BP neural network

Wei-Fang Chen; Hao-Jie Xia; Shen-Wang Lin; Hsueh-Cheng Liao

doi:10.1117/12.819729

31 December 2008 Highly precise signal-subdivision method of grating based on BP neural network

Wei-Fang Chen, Hao-Jie Xia, Shen-Wang Lin, Hsueh-Cheng Liao

Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71304P (2008) https://doi.org/10.1117/12.819729
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China

Abstract

This paper has researched signal processing methods of grating measurement system, and has come out a method to subdivide grating signals based on BP neural network. This measuring method focuses on the special property of the obtained grating signal. The method also decreases the precision requirement of the signal. When the measuring system changes, subdivision models can be altered automatically by software. BP neural networks can subdivide grating signals with few sampling points but high magnitude. This subdivide-method combines software and hardware, has simple structure, does not require complex circuit, and has a strong adaptive system.

Citation Download Citation

Wei-Fang Chen, Hao-Jie Xia, Shen-Wang Lin, and Hsueh-Cheng Liao "Highly precise signal-subdivision method of grating based on BP neural network", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304P (31 December 2008); https://doi.org/10.1117/12.819729

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