A residual life evaluation method of high precision FOG based on artificial intelligence algorithm

Yueze Wang; Zijian Zhang; Wei Luo; Sheng Jin; Jun Yan

doi:10.1117/12.2604309

24 November 2021 A residual life evaluation method of high precision FOG based on artificial intelligence algorithm

Yueze Wang, Zijian Zhang, Wei Luo, Sheng Jin, Jun Yan

Proceedings Volume 12069, AOPC 2021: Novel Technologies and Instruments for Astronomical Multi-Band Observations; 1206906 (2021) https://doi.org/10.1117/12.2604309
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

As a new generation of optical gyroscope, FOG has been widely used in many important fields. With the wide application of high-precision FOG, users put forward higher requirements for the reliability of FOG. As a new research hotspot, the remaining life prediction and evaluation of high-precision FOG has become the focus of many technicians. This paper attempts to combine the residual life evaluation of high-precision FOG with deep learning algorithm, and uses deep learning method to evaluate the residual life of high-precision FOG. Experiments show that the method can effectively predict and evaluate the residual life of high-precision FOG. It achieves the purpose of accurate maintenance, repair and replacement, and is of great significance to improve the reliability of high-precision FOG.

Citation Download Citation

Yueze Wang, Zijian Zhang, Wei Luo, Sheng Jin, and Jun Yan "A residual life evaluation method of high precision FOG based on artificial intelligence algorithm", Proc. SPIE 12069, AOPC 2021: Novel Technologies and Instruments for Astronomical Multi-Band Observations, 1206906 (24 November 2021); https://doi.org/10.1117/12.2604309

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