A Novel Signal Processing and Defect Recognition Method Based on Multi-Sensor Inspection System

摘要：

This article presented a novel signal processing and defect recognition method in MFL inspection system. During the preprocessing course, time-frequency analysis, median and adaptive filter, and interpolation processing are adopted to preprocess MFL inspection signal. In order to obtain high sensitivity and precision, we adopted multi-sensor data fusion technique to inspection data. A wavelet basis function (WBF) neural network was used to recognize defect parameters. Through constructing a knowledge-based off-line inspection expert system, the system improved its defect recognition capability greatly.

关键词： Sensors system Signal processing Data fusion Wavelet basis function

作者: Tao Jin Peiwen Que

作者单位: Dept. of Electrical Engineering, Fuzhou University, Fuzhou 350108, P. R. China Dept. of Measurement technology and Instruments, Shanghai Jiao Tong University, Shanghai 200030, P.

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 435-438

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）