Title :
Multisensor data fusion based on the fuzzy neural network in nondestructive testing
Author :
Zhaoli Zheng ; Shenghe Su
Author_Institution :
Dept. of Autom. Test., Harbin Inst. of Technol.
Abstract :
NDT data fusion is a fast-growing signal processing technique. It combines information from multi sources, reducing signal uncertainty and improving the overall performance of the testing. Traditional NDT data fusion models are mostly based on statistical theory. They have some shortcomings. For example, they must have prior knowledge and the areas in which they are used are limited. Data fusion based on fuzzy neural network is a relative new topic. Its application in NDT is a new area. This paper gives a new fuzzy neural network model adapted to NDT multisensor data fusion. The simulation result illustrates that this model solves the problem of the traditional model
Keywords :
fuzzy neural nets; nondestructive testing; sensor fusion; fuzzy neural network; multisensor data fusion; nondestructive testing; signal processing technique; signal uncertainty; simulation result; Artificial neural networks; Automatic testing; Fuzzy neural networks; Fuzzy systems; Intelligent networks; Neural networks; Nondestructive testing; Sensor fusion; Signal processing; Statistics;
Conference_Titel :
Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on
Conference_Location :
Pafos
Print_ISBN :
0-7803-5682-9
DOI :
10.1109/ICECS.1999.813206