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Research on TFM Imaging of Main Pipe Weld of Compound Steel Based on FMC/SMC

机译:基于FMC / SMC的复合钢主管焊接TFM成像研究

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Main pipe weld of compound steel with welding layer of coarse-grained austenitic stainless steel leads to the reduction of image resolution and signal-to-noise ratio (SNR) using phased array ultrasonic testing (PAUT). Total focusing method (TFM) can be employed to improve imaging quality, but computational efficiency is influenced significantly by element number. It is very important to balance quality and efficiency of TFM imaging by reasonably choosing array element. Focusing on 75 mm thickness main pipe weld of compound steel having a Φ2 mm side-drilled hole in 65 mm, the TFM imaging were compared with data acquisition modes of full matrix capture (FMC) and sparse matrix capture (SMC). The results showed that, with the increasement of element number, the quality of TFM images were both improved. When the element number was 8, compared with FMC-TFM image, the array performance indicator (API) of SMC-TFM image decreased 20% and SNR differed by 0.75dB, while API and SNR were almost the same with 48 elements. The detection result was up to element number and location, so SMC could be utilized to ensure imaging quality and improve computational efficiency in practical inspection.
机译:复合钢的主管焊接粗粒奥氏体不锈钢焊接层导致使用相位阵列超声波检测(PAUT)的图像分辨率和信噪比(SNR)的降低。可以采用总关注方法(TFM)来提高成像质量,但计算效率受元素数量的影响。通过合理选择阵列元素来平衡TFM成像的质量和效率非常重要。专注于75毫米厚度的复合钢的主管焊缝,其中φ2mm侧钻孔在65 mm中,与全矩阵捕获(FMC)和稀疏矩阵捕获(SMC)进行数据采集模式进行比较TFM成像。结果表明,随着元素数量的增加,TFM图像的质量均得到改善。当元素数为8时,与FMC-TFM图像相比,SMC-TFM图像的阵列性能指示符(API)降低了20%,SNR不同0.75dB,而API和SNR几乎与48个元素几乎相同。检测结果达到元件数量和位置,因此SMC可用于确保成像质量并提高实际检查中的计算效率。

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