飞机疲劳试验裂纹声发射信号的人工神经网络模式识别

详细信息

The Neural Network Pattern Recognition of Crack AE Signal During Aircraft Fatigue Testing

摘要: 对某型飞机疲劳试验过程中采集的信号, 先后采用频谱、多分辨率小波方法对原始信号作了分析, 但这两种方法的分析结果不甚理想, 从而改用人工神经网络模式识别的方法提取出了可能是裂纹信号的波形信号。该试验为类似疲劳试验等强噪声环境下的声发射信号模式识别提供了一种可供参考的方法。
- 声发射检测 /
- 裂纹 /
- 神经网络 /
- 疲劳试验 /
- 强噪声
Abstract: Utilizing the FFT and wavelet methods to analyze the original crack AE(Acoustic Emission) signal during aircraft fatigue testing, but the results were not ideal. Then, the neural network pattern recognition method was hence applied, and the crack AE waveform was extracted. The experiment put forward a reference to AE signal pattern recognition under strong background noise as fatigue testing.
- Acoustic emission testing /
- Crack /
- Neural network pattern recognition /
- Fatigue testing /
- Strong noise

[1]	耿荣生, 王本志, 景鹏, 等.某型飞机主起落架支柱外筒头部枢轴疲劳损伤的声发射监测［J］.无损检测, 2008, 30(3): 142-145.
[2]	耿荣生, 沈功田, 刘时风.声发射信号处理和分析技术［J］.无损检测, 2002, 24(1): 23-28.