摘要：The recent years has seen the automatic assessment system of the operators of subsea production simulation be in great demand. Firstly, this paper gives a specific introduction to the simulation training system of subsea production simulation based on virtual reality. Secondly, it aims to improve the assessment system for operators of ROV, winch and crane in subsea production simulation and improve the operation level, and solve the technical problems of subsea production simulation with low cost and low risk. This paper is based on the physical conditions of virtual reality simulation of 'human-machine-environment', and the assessment results of human experts. An intelligent assessment algorithm of subsea production simulation operators based on the residual network is designed. The residual structure and Batch Normalization are applied in this algorithm, which has significantly improved the accuracy of the model. The analysis results show that the mean square error of this algorithm stands only 1.4281, which means this method is pretty suitable for the training mode and assessment of subsea production simulation operators.
© 2019 IEEE.

卷、期、页：v 1,p188-192

发表日期：2019-08-01

收录情况：EI（工程索引）

发表期刊名称：Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

通讯作者：钱柯玮,马登辉

第一作者：姜珊,左信,徐宝昌

论文类型：会议论文

论文概要：钱柯玮,姜珊,左信,马登辉,徐宝昌，Intelligent Assessment of Operators of Subsea Production Simulation System Based on Residual Network，Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019，2019，v 1,p188-192

论文题目：Intelligent Assessment of Operators of Subsea Production Simulation System Based on Residual Network