DocumentCode :
2620646
Title :
Fuzzy similarity-based data fusion algorithm and its application to engine testing
Author :
Li, Xiong ; Xu, Zongchang ; Dong, Zhiming
Author_Institution :
Dept. of Command & Adm., Acad. of Armored Force Eng., Beijing, China
Volume :
2
fYear :
2005
fDate :
25-27 July 2005
Firstpage :
516
Abstract :
According to the requirements of multisensor data fusion in real-time engine testing, a novel, fuzzy similarity-based data fusion algorithm is given in this paper. Based on fuzzy set theory, it calculates the fuzzy similarity between a certain sensor´s measurement values and the multiple sensors´ objective prediction values to determine the importance weigh of each sensor, and realize the multisensor testing parameter data fusion. According to the algorithm theory, its application software is also designed in the paper. The applied example proves that the algorithm can give priority to the high-stability and high-reliability sensors and it is laconic, efficient and feasible to real-time circumstance measure and data processing in engine condition monitoring and measurement.
Keywords :
fuzzy set theory; internal combustion engines; real-time systems; sensor fusion; algorithm theory; fuzzy set theory; fuzzy similarity-based data fusion; multisensor data fusion; multisensor testing parameter data fusion; real-time engine testing; Algorithm design and analysis; Application software; Condition monitoring; Data processing; Engines; Fuzzy set theory; Sensor fusion; Software algorithms; Software design; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9017-2
Type :
conf
DOI :
10.1109/GRC.2005.1547345
Filename :
1547345
Link To Document :
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