five

Sensing Science and Engineering Centre (SEC) Vibration Data

收藏
Mendeley Data2024-03-27 更新2024-06-29 收录
下载链接:
https://researchdatafinder.qut.edu.au/display/n10653
下载链接
链接失效反馈
官方服务:
资源简介:
Two structural columns host the sensors (named A3 and A8) and sensors are mounted on the ceiling slabs of every second floor, i.e. levels 3,5,7 and 9 for both columns. Most locations measure three axes of acceleration, except for Level 3 Column A8 and Level 7 Column A8 which only measure x axis. Two additional sites are instrumented, a footbridge leading out of the building and a site to monitor the vibration under a Transmission Electron Microscope (TEM). The footbridge has a total of 8 axes simultaneously measured with addition to two Acoustic Emmisions (AE) sensors monitoring the bridge support and mid span. The TEM has a three-axis accelerometer mounted under the concrete and rubber slab the microscope is mounted to and monitors the vibration the microscope is exposed to. Samples are simultaneously sampled at each location and different sample sites are triggered via a central location to minimise clock drift. Data is sampled at 2000 samples per second per axis 24 hours a day, 7 days a week and logged into csv files. In total there are 31 Axes of data collected throughout the building. Data is uploaded from the data collection server to the storage server in 30 minute intervals. Data is stored in "g's". National Instruments NI-9234 module acquiring data at 2KHz, anti-aliasing filter at 900Hz. Software specifically written to collect, organise and store data onto QUT's storage systems. Time stamped vibration data from multiple locations throughout the Science and Engineering Centre building on the Gardens Point campus of Queensland University of Technology. Files are stored in Comma Separated Values (.csv). At approximately 90MB/hour/channel, software is required that can handle large datasets such as Mathworks MATLAB or National Instruments DIAdem.
创建时间:
2023-06-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作