Online visual inspection method for fuel assemblies in nuclear power plants

计算机视觉 人工智能 计算机科学 滤波器(信号处理) 职位(财务) 失真(音乐) 参数统计 水下 特征(语言学) 反褶积 变形 卡尔曼滤波器 算法 数学 地质学 统计 海洋学 语言学 哲学 计算机网络 经济 放大器 带宽(计算) 财务
作者
Ranran Sheng,Zhen Zhang
出处
期刊:Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)
标识
DOI:10.1117/12.2500445
摘要

When underwater camera is used to carry out the visual inspection after fuel reloading in nuclear power plants, heat exchange between fuel assemblies and water can generate underwater turbulence effect, which causes imaging distortion, and then affects position measurement accuracy of nuclear fuel assemblies. A new online visual inspection method for fuel assemblies in nuclear power plants is proposed in this paper. The method consists of image restoration and deformation inspection. A turbulence image degradation model is established at first. In the model that water turbulence weakly satisfy a Gaussian distribution. A temporal high pass filter by image quality assessment and a mean filter in time domain are used to remove the morphing of acquired original sequence images according to the degradation model. And then a spatial Wiener deconvolution filter is used to remove the image blurring that is caused by the above mentioned mean filter. The next step is using the deformation inspection algorithm to get the fuel assembles precise position. The distance of feature holes (S-hole) is solved by calibrated underwater parametric camera model. The experimental results show that the underwater image restoration method can effectively remove the image morphing that is generated by turbulence effect. The proposed online visual inspection method has a high detection precision. And the average error of the solved feature holes’ distance is less than 0.1 mm when the execution time of the method is lower than 0.5 s.
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