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

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.