锻压技术

表面粗糙锻件的超声检测信号处理技术研究

英文标题：Research on signal processing technique of ultrasonic testing for forging workpiece with rough surface

作者：杨博

单位：钢铁研究总院

分类号：

出版年,卷(期):页码：2014,39(10):128-131

摘要：

针对表面粗糙锻件的超声检测信号分别做了基于傅里叶变换的信号处理工作和基于小波变换的信号处理工作。其中基于傅里叶变换的信号处理主要包括频谱分析和FIR滤波，基于小波变换的信号处理主要包括时频分析和小波去噪。经FIR滤波后，表面粗糙锻件上平底孔缺陷信号的信噪比(SNR)与滤波前相比提高了3.9 dB，但是超声检测信号的均方根误差(RMSE)与滤波前相比减小了0.085；对信号做小波去噪处理后，平底孔缺陷信号的信噪比与去噪前相比提高了9.9 dB，而且信号的均方根误差与去噪前相比几乎没发生变化。通过实验对比发现，基于小波变换的信号处理技术可以对表面粗糙锻件的超声检测信号达到更好的去噪效果。

The ultrasonic testing signal of forging workpiece with rough surface was processed based on the Fourier transform and wavelet transform respectively. The signal processing work based on the Fourier transform mainly refers to the spectrum analysis and FIR filter, and the signal processing work based on the wavelet transform mainly refers to the time-frequency analysis and Wavelet remove noise. After FIR filter, the SNR of defect signal of flat bottom hole on the forging workpiece with rough surface was improved by 3.9 dB compared with the original signal, but the RMSE of ultrasonic testing signal was reduced by 0.085. After wavelet remove noise, the SNR of defect signal was improved by 9.9 dB, but the RMSE was almost unchanged compared with the original signal. By comparing the signal processing results, it is showed that the wavelet transform method is better than the Fourier transform method on the ultrasonic testing signal processing forging workpiece with rough surface.

基金项目：

杨博（1987-），男，硕士研究生

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