期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Study on General Performance of Jack-up Under Elevated Condition 被引量:8
1
作者 李红涛 杨清峡 李晔 《China Ocean Engineering》 SCIE EI 2009年第3期577-584,共8页
Method of checking for jack-up elevated performance including leg structure strength, fixation system or jacking system beating capacity, pre-load requirements, spud can beating capacity and overturning stability is s... Method of checking for jack-up elevated performance including leg structure strength, fixation system or jacking system beating capacity, pre-load requirements, spud can beating capacity and overturning stability is suggested in this paper. As an example, a jack-up with truss legs is analyzed by finite element analysis method. This paper may be helpful to the rig owners, operators and designers. 展开更多
关键词 JACK-UP finite element general performance elevated condition
下载PDF
Two-Dimensional Images of Current and Active Power Signals for Elevator Condition Recognition
2
作者 Xunsheng Ji Dazhi Wang Kun Jiang 《Journal of Harbin Institute of Technology(New Series)》 CAS 2023年第2期48-60,共13页
In this paper, an improved two-dimensional convolution neural network(2DCNN) is proposed to monitor and analyze elevator health, based on the distribution characteristics of elevator time series data in two-dimensiona... In this paper, an improved two-dimensional convolution neural network(2DCNN) is proposed to monitor and analyze elevator health, based on the distribution characteristics of elevator time series data in two-dimensional images. The current and effective power signals from an elevator traction machine are collected to generate gray-scale binary images. The improved two-dimensional convolution neural network is used to extract deep features from the images for classification, so as to recognize the elevator working conditions. Furthermore, the oscillation criterion is proposed to describe and analyze the active power oscillations. The current and active power are used to synchronously describe the working condition of the elevator, which can explain the co-occurrence state and potential relationship of elevator data. Based on the improved integration of local features of the time series, the recognition accuracy of the proposed 2DCNN is 97.78%, which is better than that of a one-dimensional convolution neural network. This research can improve the real-time monitoring and visual analysis performance of the elevator maintenance personnel, as well as improve their work efficiency. 展开更多
关键词 elevator condition CURRENT active power two-dimensional convolution network(2DCNN)
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部