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《Journal of Ship Mechanics》 2010-10
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Identification of noise sources based on multi-sensors information fusion

CUI Li-lin a,ZHANG Lin-ke a,ZHU Hai-chao a,LUAN Rui-peng b(a.Institution of Noise & Vibration;b.Department of Computer Science,Navy University of Engineering,Wuhan 430033,China)  
Identification of underwater vehicle mechanical noise sources can be considered as a pattern recognition problem on small samples.Using the signals of multiple sensors is one of the most effective methods to solve the problem.Currently there is no appropriate method to calculate the weightiness of each sensor during the evaluation.In this paper,the transductive confidence machine(TCM) was used to calculate the confidence of classification prediction,which was an effective representation for the weightiness of each sensor.First,an improved strangeness measuring method was given to increase the accuracy of confidence prediction.Then a new algorithm,named TCM-IKNN-M(Transductive Confidence Machine for Improved K-Nearest Neighbors based on Multi_sensors),was proposed based on the predicted confidence and improved strangeness measuring method.The results of the experiment conducted on a cabin model show that TCM-IKNN-M algorithm can greatly increase the right rate of identification by fusing the information from multiple sensors.
【Fund】: 国家自然科学基金资助项目(50775218)
【CateGory Index】: TB561;TB534.1
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