A Consensus-Based Approach for Information Fusion

Li Jiao; Hai Zhang; Hong Wei Liu

doi:10.4028/www.scientific.net/AMM.90-93.1691

Paper Titles

Study on Change Regularity of Air Temperature Underground Tunnel Based on Intermittent Operating of Heat Pump
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Reduced-Scale Experiments on Smoke Extraction Capability in Tunnel Fire
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In Situ Testing of the Vibration Isolation Effect of the Vibration Isolating Trench
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Large Deformation Prediction and Feedback for a Reservoir Slope near a Large-Scale Hydropower Station in the Upstream of Yellow River
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A Consensus-Based Approach for Information Fusion
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Influence of Source Distance on the Characteristics of AE Signal from Cement-Based Materials
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Ferromagnetic ZnO-TiO₂ Core-Shell Nanowire PhotoCatalyst with High Efficiency and Recyclability
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Extraction of Soil Salinization from Remote Sensing Information and LUCC Data Based on Knowledge Discovery over the Arid Area: A Case Study on Kuka County in Xinjiang
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Spatial Analysis of Land Use and Land Cover Changes on the Basis of RS and GIS
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 90-93A Consensus-Based Approach for Information Fusion

A Consensus-Based Approach for Information Fusion

Abstract:

The purpose of data fusion is to combine and process the data of multi-sensors, thus to obtain much more exact and reliable results than that of the single sensor. An improved data fusion method for commensurate sensors is presented in this paper. It overcomes the shortcoming of the traditional consensus algorithm with two sensors, which has different confidence distance while measuring in different precision. The relation matrix is fuzzified to avoid the subjective error in determining the threshold value. The results of numerical simulation shows that the improved method can make full use of the effective information from the sensors and it can help to improve the accuracy of measurement. Even when parts of sensors are affected or fully disabled, it still can get correct diagnosing results in damage identification.

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Periodical:

Applied Mechanics and Materials (Volumes 90-93)

Pages:

1691-1697

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.90-93.1691

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Online since:

September 2011

Authors:

Li Jiao, Hai Zhang, Hong Wei Liu

Keywords:

Confidence Distance, Consensus Algorithm, Damage Identification, Information Fusion, Relation Matrix

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