A multi-source data collection and information fusion method for distribution network based on IOT protocol

2021 ◽  
Vol 651 (2) ◽  
pp. 022076
Author(s):  
Yongxiang Cai ◽  
Xiaobing Xiao ◽  
Hao Tian ◽  
Yu Fu ◽  
Peng Wu ◽  
...  
2008 ◽  
Vol 392-394 ◽  
pp. 596-600 ◽  
Author(s):  
Hong Jun Wang ◽  
Xiang Jun Zou ◽  
D.J. Zou ◽  
J. Liu ◽  
Tian Hu Liu

In picking manipulator location system, it is the key problem that the positions of obi-object and picking manipulator are exactly determined in complex environment. Based on multi-sensor information fusion method, a data fusion system of multi-sensor integrating laser-sensor for absolute location with ultrasonic-sensor for inspection impediment was presented. Firstly, data collection and fusion were implemented employing a two- level distribution system. Secondly, the method of data collection and fusion in virtual environment was discussed, and the result data could drive picking manipulator 3D model to dynamically move in real-time using event and route mechanisms provided by virtual environment, which could simulate the process of picking manipulator being accurately located. Finally, a location simulation system was developed by VC++ and EON SDK.


2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.


2021 ◽  
Vol 4 (1) ◽  
pp. 251524592092800
Author(s):  
Erin M. Buchanan ◽  
Sarah E. Crain ◽  
Ari L. Cunningham ◽  
Hannah R. Johnson ◽  
Hannah Stash ◽  
...  

As researchers embrace open and transparent data sharing, they will need to provide information about their data that effectively helps others understand their data sets’ contents. Without proper documentation, data stored in online repositories such as OSF will often be rendered unfindable and unreadable by other researchers and indexing search engines. Data dictionaries and codebooks provide a wealth of information about variables, data collection, and other important facets of a data set. This information, called metadata, provides key insights into how the data might be further used in research and facilitates search-engine indexing to reach a broader audience of interested parties. This Tutorial first explains terminology and standards relevant to data dictionaries and codebooks. Accompanying information on OSF presents a guided workflow of the entire process from source data (e.g., survey answers on Qualtrics) to an openly shared data set accompanied by a data dictionary or codebook that follows an agreed-upon standard. Finally, we discuss freely available Web applications to assist this process of ensuring that psychology data are findable, accessible, interoperable, and reusable.


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