摘要
在对火炮身管缺陷进行漏磁检测时,由于内表面膛线的存在,漏磁信号中除缺陷信号外,还有系统噪声和膛线干扰信号。说明了自适应滤波方法和小波变换分别去除膛线干扰信号和系统噪声的原理。在仿真试验中,自适应滤波的权值学习算法采用最小均方算法,自适应滤波的原始输入和参考输入信号来自于不同的两个传感器;选取二阶样条小波为小波函数,选用硬阈值函数和固定阈值的方法处理小波系数。结果表明,自适应滤波方法和小波变换很好地去除了膛线干扰信号和系统噪声,提取出了缺陷信号。
When defects of gun barrel are tested by use of magnetic flux leakage （MFL） method, because of the existence of rifles in barrel inner surface, except for the defect signals, there existed system noises and rifle interference signals in MFL signals. The adaptive filter method and wavelet transform were respectively used to eliminate rifle interference signals and system noises, and their principles were introduced. In simulation experiment, weight value learning algorithm of adaptive filter made use of least mean square algorithm, and the raw input and the reference input signals were from two different sensors. The second-order spline wavelet was chosen as wavelet function, and hard-thresholding function and fixed threshold value were adopted to process wavelet coefficients. The result indicated that the system noises and the rifle interference signals can be effectively eliminated by adaptive filter and wavelet transform, and the defect signals can be extracted.
出处
《火炮发射与控制学报》
北大核心
2008年第1期77-80,共4页
Journal of Gun Launch & Control
基金
国家自然科学基金项目资助(50175109)
关键词
材料检测与分析技术
漏磁检测
自适应滤波
小波变换
去噪
膛线干扰
materials examination and analysis
magnetic flux leakage testing
adaptive filter
wavelet transform
de-noising
rifle interfere
