Method for Examining the Performance of Seafloor Observatory Sensors

2020 ◽  
Vol 75 (4) ◽  
pp. 371-377
Author(s):  
V. A. Karpov ◽  
K. A. Sementsov ◽  
M. A. Nosov ◽  
S. V. Kolesov ◽  
H. Matsumoto ◽  
...  
Keyword(s):  
Author(s):  
Huiping Xu ◽  
Changwei Xu ◽  
Rufu Qin ◽  
Yang Yu ◽  
Shangqin Luo ◽  
...  

Author(s):  
K. Moran ◽  
S. Farrington ◽  
E. Massion ◽  
C. Paull ◽  
R. Stephen ◽  
...  
Keyword(s):  

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2628 ◽  
Author(s):  
Yusheng Zhou ◽  
Rufu Qin ◽  
Huiping Xu ◽  
Shazia Sadiq ◽  
Yang Yu

With the construction and deployment of seafloor observatories around the world, massive amounts of oceanographic measurement data were gathered and transmitted to data centers. The increase in the amount of observed data not only provides support for marine scientific research but also raises the requirements for data quality control, as scientists must ensure that their research outcomes come from high-quality data. In this paper, we first analyzed and defined data quality problems occurring in the East China Sea Seafloor Observatory System (ECSSOS). We then proposed a method to detect and repair the data quality problems of seafloor observatories. Incorporating data statistics and expert knowledge from domain specialists, the proposed method consists of three parts: a general pretest to preprocess data and provide a router for further processing, data outlier detection methods to label suspect data points, and a data interpolation method to fill up missing and suspect data. The autoregressive integrated moving average (ARIMA) model was improved and applied to seafloor observatory data quality control by using a sliding window and cleaning the input modeling data. Furthermore, a quality control flag system was also proposed and applied to describe data quality control results and processing procedure information. The real observed data in ECSSOS were used to implement and test the proposed method. The results demonstrated that the proposed method performed effectively at detecting and repairing data quality problems for seafloor observatory data.


2011 ◽  
Vol 56 (26) ◽  
pp. 2839-2845 ◽  
Author(s):  
HuiPing Xu ◽  
YanWei Zhang ◽  
ChangWei Xu ◽  
JianRu Li ◽  
Ding Liu ◽  
...  

2015 ◽  
pp. 211-228 ◽  
Author(s):  
K. Kawaguchi ◽  
S. Kaneko ◽  
T. Nishida ◽  
T. Komine

2019 ◽  
Vol 7 (11) ◽  
pp. 414 ◽  
Author(s):  
Yang Yu ◽  
Huiping Xu ◽  
Changwei Xu

Seafloor observatories enable continuous power supply and real-time bidirectional data transmission, which marks a new way for marine environment monitoring. As in situ observation produces massive data in a constant way, the research involved with data acquisition, data transmission, data analysis, and user-oriented data application is vital to the close-loop operations of seafloor observatories. In this paper, we design and implement a sensor web prototype (ESOSW) to resolve seafloor observatory information processing in a plug-and-play way. A sensor web architecture is first introduced, which is information-oriented and structured into four layers enabling bidirectional information flow of observation data and control commands. Based on the layered architecture, the GOE Control Method and the Hot Swapping Interpretation Method are proposed as the plug-and-play mechanism for sensor control and data processing of seafloor observatory networks. ESOSW was thus implemented with the remote-control system, the data management system, and the real-time monitoring system, supporting managed sensor control and on-demand measurement. ESOSW was tested for plug-and-play enablement through a series of trials and was put into service for the East China Sea Seafloor Observation System. The experiment shows that the sensor web prototype design and implementation are feasible and could be a general reference to related seafloor observatory networks.


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