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基于稀疏盲反卷积算法的波导阵列成像方法

Waveguide array imaging method using sparse blind deconvolution algorithm

  • 摘要: 高温承压设备长期运行在严苛环境中,往往会因裂纹引发设备失效,因而准确地识别裂纹缺陷对提升设备运行的安全性至关重要。波导阵列技术可解决传感器高温失效的问题,应用波导阵列传感装置可以实现高温环境中缺陷的可视化成像。然而受激励脉冲与声衰、衍射等声学效应的影响,波导阵列成像存在纵向分辨率不足等问题。为了解决该难题,文章提出采用稀疏盲反卷积算法改善波导阵列成像质量,借助有限元模拟,对不同角度裂纹进行波导阵列成像检测研究,检验该算法性能,并进行试验验证。研究发现波导阵列成像效果受裂纹与超声波传播方向之间夹角的影响较大,当裂纹方向接近超声传播方向时,较难识别裂纹特征,但 采用稀疏盲反卷积算法可以提高成像清晰度,并减弱裂纹尖端衍射效应对成像的影响,改善纵向分辨率,提高检测精度。

     

    Abstract: Equipment running for long period in high temperature and high pressure environments often experience equipment failure due to cracks, making accurate defect identification crucial for improving equipment operation safety. Waveguide array technology can address the issue of sensor failure at high temperatures, enabling visual imaging of defects in such environments using waveguide array sensor devices. However, due to factors such as excitation pulse influence, acoustic attenuation, diffraction and other acoustic effects, waveguide array imaging faces challenges with insufficient vertical resolution. To tackle this problem, we propose the sparse blind deconvolution algorithm to enhance the image quality of waveguide arrays. Finite element simulation is used to verify the effectiveness of the algorithm in detecting cracks with different angles while experiments are conducted to test and validate its performance. We find that the imaging effect of waveguide arrays is significantly influenced by the angle between the crack and ultrasonic propagation direction. When the crack direction aligns closely with ultrasonic propagation direction, it becomes difficult to identify crack characteristics accurately. Employing the sparse blind deconvolution algorithm can improve imaging clarity, weaken the impact from diffraction effects at crack tips, enhance vertical resolution and improve the detection accuracy.

     

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