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《Journal of Transcluction Technology》 2004-03
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Neural Network-Style Fusion of Pipelines' Defect Data Scanned by Multi-Ultrasonic Sensors

CHEN Tian-lu, QUE Pei-wen, JIN Tao, LEI Hua-ming(Institute of Automatic Detection, Shanghai Jiaotong University, Shanghai 200030, China)  
According to the state of inspecting pipeline, the paper defects designs a testing system of ultrasonic sensor array . and applies neural network technology into the field of data fusion, The data of the pipeline defects gathered by scanning of those ultrasonic sensors are fused from the use of improved BP-LM algorithm.Inspection results in lab show that this data fusion method based on neural network optimizes data markedly. The improved BP-LM algorithm has better performance and shorter convergence time.
【Fund】: 国家 8 6 3计划资助项目 项目编号 :2 0 0 1AA6 0 2 0 2 1
【CateGory Index】: TP212
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1 WANG Xiao\|ping, HUANG Hai, JIANG Hua\|bing\;(Dept. of Scientific Instruments Engineering, Zhejiang Univ., Hangzhou, 310027, China);The improving of Vogl quick algorithm for BP neural network[J];浙江大学学报(工学版);2000-02
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