个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:力学与航空航天学院
学科:工程力学. 固体力学. 船舶与海洋结构物设计制造. 计算力学. 航空航天力学与工程
办公地点:综合实验1号楼(海宇楼)605
联系方式:Email: lxyuhua@dlut.edu.cn 565598@qq.com
电子邮箱:lxyuhua@dlut.edu.cn
基于卷积网络的浮式平台人员舒适度评价
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发表时间:2022-10-10
发表刊物:Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University
卷号:42
期号:1
页面范围:82-88
ISSN号:1006-7043
摘要:To solve the influence of the six-degree-of-freedom (DOF) movement of a floating platform on the comfort of platform personnel, this paper examines the comfort platform of floating platform personnel based on a convolutional neural network (CNN). Based on fractal theory and statistical analysis methods, a dimensionality reduction analysis of measured load information is performed in this study to select mixed feature parameters. Meanwhile, the motion response model of the semi-submersible platform is simplified to the six-DOF motion of a rigid body. The central difference and vector superposition method are used to derive the correspondence between the acceleration and the six DOF at any point of the platform. A personnel comfort evaluation method based on the ISO 6897-1984(E) specification is proposed for the vertigo problem caused by the platform movement. The relationship model between the load characteristic parameters and personnel comfort level is established using the fully connected CNN method, and the personnel comfort assessment method based on the environmental load parameters is proposed. The train accuracy reaches 99.77%, and the test accuracy achieves 100%. The prediction results can provide some guidance for platform operations and services. Copyright ©2021 Journal of Harbin Engineering University.
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