基于独立分量分析的缺陷信号串扰消除

基金项目:

安徽工程科技学院青年基金(自然科学)立项项目资助(2007YQ034)

安徽省年度科研计划项目资助(08020203022)

详细信息

Reduction of Disturbance Between Flaw Signals Based on Independent Component Analysis

摘要: 漏磁检测设备中纵向传感器阵列特殊的物理结构, 使得采集的缺陷信号之间不可避免地产生串扰, 因而降低了检测设备的可靠性。结合采集信号的阵列特性, 通过使用基于独立分量分析(ICA)的阵列信号处理方法, 分离出各路消除串扰的源信号。仿真试验结果表明, ICA 的定点算法可以消除信号之间的串扰, 满足检测设备要求, 具有较大的应用潜能。
- 独立分量分析 /
- 定点算法 /
- 漏磁检测 /
- 缺陷信号 /
- 串扰消除
Abstract: The special structure of longitudinal sensor array in magnetic leakage detecting equipment leads to the inevitable disturbance between flaw signals and the low performance of equipment. Considering the characteristic of array in detecting signals, the array signal process method based on the independent component analysis(ICA) was used to separate the non-disturbance source signals. Simulation experiment was carried out, and the result showed that this method could reduce the disturbance between flaw signals and met the detected equipment requirements. Thus the fixed point algorithm for ICA has large potential in flaw signals process.
- Independent component analysis /
- Fixed point algorithm /
- Magnetic leakage testing /
- Flaw signal /
- Disturbance reduced

[1]	何辅云.磁探伤中多路缺陷信号的滑环传送方法［J］.合肥工业大学学报(自然科学版), 1998, 21(3): 128-131.
[2]	焦李成, 慕彩红, 王伶.通信中的智能信号处理［M］.北京: 电子工业出版社, 2006: 87-90.
[3]	杨福生, 洪波.独立分量分析的原理与应用［M］.北京: 清华大学出版社, 2006: 1-6.
[4]	何辅云, 王晓芒.地下油气输送管道电磁高速检测技术及系统［J］.合肥工业大学学报, 2002, 25(2): 218-221.
[5]	Hyvrinen A. Fast and robust fixed-point algorithms for independent component analysis［J］. IEEE Transactions on Neural Networks, 1999, 10(3): 626-634.
[6]	Bingham E, Hyvarinen A. A fast fixed-point algorithm for independent component analysis［J］. Neural Computation, 1997, 9(7): 1483-1492.
[7]	张洪渊, 贾鹏, 史习智.确定盲分离中未知信号源个数的奇异值分解法［J］.上海交通大学学报, 2001, 35(8): 1155-1158.