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高温合金小直径棒材超声检测信号的余弦变换分析及识别
引用本文:卢超,张维,彭应秋,李坚.高温合金小直径棒材超声检测信号的余弦变换分析及识别[J].无损检测,2003,25(3):124-127,401.
作者姓名:卢超  张维  彭应秋  李坚
作者单位:南昌航空工业学院测试技术与控制工程系,南昌,330034
基金项目:航空高校科学基金(EC99810915),江西省教育厅科学基金(4962076)
摘    要:将离散余弦变换(DCT)用于直径为φ26mm的变形高温合金棒材超声检测信号的特征分析,提取缺陷回波的离散余弦变换幅度谱作为特征矢量,并对提取的特征利用人工神经网络进行训练和分类,实验和距离可分性测度计算结果表明,与离散傅里叶变换提取的谱类别特征相比,离散余弦变换使缺陷信号的谱类别特征有明显增强。

关 键 词:高温合金  超声检验  棒材  信号处理  模式识别  离散余弦变换  航空发动机  涡轮叶片
文章编号:1000-6656(2003)03-0124-04

COSINE TRANSFORM ANALYSIS AND PATTERN RECOGNITION OF ULTRASONIC TESTING SIGNALS FOR THE HIGH TEMPERATURE ALLOY BARS WITH SMALL DIAMETER
LU Chao,ZHANG Wei,PENG Ying-qiu,LI Jian.COSINE TRANSFORM ANALYSIS AND PATTERN RECOGNITION OF ULTRASONIC TESTING SIGNALS FOR THE HIGH TEMPERATURE ALLOY BARS WITH SMALL DIAMETER[J].Nondestructive Testing,2003,25(3):124-127,401.
Authors:LU Chao  ZHANG Wei  PENG Ying-qiu  LI Jian
Abstract:Discrete cosine transform was used for extracting features of ultrasonic testing signals from the high temperature deformed alloy bars with diameter of 26mm. Then the flaw signal feature value based on discrete cosine transform spectrum was trained and classified by artificial neural networks. Theoretical and experimental results showed that discrete cosine transform could obviously enhance the spectrum features of flaw signals compared with Fourier transform.
Keywords:Ultrasonic testing  Bar  Signal processing  Pattern recognition
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