Quantitative detection of small defects in TOFD dead zone of austenitic stainless steelbased on frequency domain sparse blind deconvolution
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摘要: 针对超声衍射时差法（TOFD）检测奥氏体不锈钢近表面盲区内小尺寸缺陷时的信号混叠及结构噪声问题，提出了频域稀疏盲解卷积法。在厚为35 mm奥氏体不锈钢试块TOFD近表面检测盲区内加工深为3.0 mm，高为3.0 mm的人工缺陷，基于匹配追踪算法（MP）对TOFD试验信号进行稀疏分解，解耦噪声部分，再利用同态变换并结合L1，L2范数约束建立反演问题目标函数，并利用内点法求解。结果表明，在无需参考信号的情况下，该方法能够分离TOFD表面直通波和缺陷上、下端点衍射波，计算求得缺陷深为3.04 mm，高为2.65 mm，最大误差不超过11.7%。
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关键词:
- 超声衍射时差法(TOFD) /
- 奥氏体不锈钢 /
- 近表面盲区 /
- 检测分辨率 /
- 频域稀疏盲解卷积
Abstract: To solve the problem of signal aliasing and structural noise in detecting small defects in the near-surface dead zone of austenitic stainless steel by time of flight diffraction (TOFD), a frequency domain sparse blind deconvolution method was proposed. The artificial defects with a depth of 3. 0 mm and a height of 3. 0 mm were processed in the dead zone of TOFD near surface detection of austenitic stainless steel test block with a thickness of 35 mm. The experimental signals of TOFD were sparsely decomposed based on Matching pursuit (MP) algorithm to decouple the noise parts. The objective function of inversion problem was established by homomorphic transformation combined with L1 and L2 norm constraints, and solved by interior point method. The results showed that without reference signal, the method can separate the direct wave and the diffraction wave on the upper and lower edge of the defect by TOFD. The calculated defect depth was 3. 04 mm, the height was 2. 65 mm, and the maximum error was less than 11.7%. -
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