Background：

The data (Jiaolong_DSMS_V2.csv) was collected and provided by the National Deep Sea Center in Qingdao, Shandong, China. The initial data was collected in the exploration task for the JiaoLong Deep-sea Manned Submersible on March 19, 2017. The form of data is the multi-variate time series with around 24 features. We hide the measurement units of all the variables. We aim to provide a benchmark dataset for real-time safety assessment (RTSA) methods of dynamic systems, enabling researchers to conduct their research effectively.

Variable Description:

Monitored Variable	Explanations in Chinese
Roll Angle of Motion Sensor	运动传感器横倾角
Pitch Angle of Motion Sensor	运动传感器纵倾角
Yaw Angle of Motion Sensor	运动传感器航向角
Velocity in Bow Direction	运动传感器艏向速度
Roll Velocity of Motion Sensor	运动传感器横摇速度
Pitch Velocity of Motion Sensor	运动传感器纵倾速度
Salinity	盐度
Temperature	温度
Depth	深度
Velocity	速度
Thrust in X-axis	x轴向推力
Thrust in Y-axis	y轴向推力
Thrust in Z-axis	z轴向推力
Moment about X-axis	绕X轴力矩
Moment about Y-axis	绕Y轴力矩
Moment about Z-axis	绕Z轴力矩
Oxygen Concentration	氧气浓度
Carbon Dioxide Concentration	二氧化碳浓度
Cabin Pressure	舱内压力
Cabin Temperature	舱内温度
Cabin Humidity	舱内湿度
Emergency Hydraulic Source Pressure	应急液压源压力
Backup 2	备份2
Backup 3	备份3

Label Description:

Safety Level	Descriptions
Level I	DSMS is currently in safety state. There are no safety risks from the external environment and the system is in a healthy state internally.
Level II	DSMS is currently operating in a mildly unsafe state. There may be safety risks in the external environment or controllable abnormalities within the system.
Level III	DSMS is currently operating in an unsafe state. There are certain safety risks in the external environment or dangerous abnormalities inside the system.

Dataset Description:

Number of monitored variables	24
Number of safety levels	3
Number of time points	30000
Imbalance ratio (I: II: III)	10512 : 10985 : 8503

Visualization:

Citation

@article{liu2022OABL,
  title={An Online Active Broad Learning Approach for Real-Time Safety Assessment of Dynamic Systems in Nonstationary Environments},
  author={Liu, Zeyi and Zhang, Yi and Ding, Zhongjun and He, Xiao},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2022},
  doi={10.1109/TNNLS.2022.3222265},
  publisher={IEEE}
}
@INPROCEEDINGS{10295743,
  author={Liu, Zeyi and Hu, Songqiao and He, Xiao},
  booktitle={2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)}, 
  title={Real-time Safety Assessment of Dynamic Systems in Non-stationary Environments: A Review of Methods and Techniques}, 
  year={2023},
  volume={},
  number={},
  pages={1-6},
  doi={10.1109/SAFEPROCESS58597.2023.10295743}}

Notes:

• We are from the research group of THU-FDD, Department of Automation, Tsinghua University. For more information, please feel free to contact us! Emails: liuzy21@mails.tsinghua.edu.cn, hsq23@mails.tsinghua.edu.cn.

• We have updated a newer version of the dataset (Version 2) on October 27, 2023. Compared with the previous version (Version 1), it contains more monitoring variables and more detailed descriptions.