In nuclear power plants, it is a common procedure to use video inspection when reloading fuel assemblies regularly. Because of the turbulence generated by residual heat of nuclear fuel assemblies, a video sequence suffers from severe geometric deformations and is hard to be used to position the location hole of fuel assemblies. The paper proposes a novel algorithm to recover a geometrically correct image of nuclear fuel assemblies or scene from a video sequence distorted by turbulence underwater and achieve the precise position of the location hole. At the first, an average image is utilized to compare with image sequences to estimate nonrigid registration based on B-splines. By the estimated nonrigid registration, new image sequences are obtained and are used to get a new average image. After multiple iterations, the better image sequence can be shown. Then the better image sequence are divided into image patches. The more blurry and severely distorted image patches are removed in image patch sequences. Finally, the selected image patches are synthesized together. Based on restored images, template matching is utilized to quickly find the initial position of the location hole. And then the sub-pixel centroid method is used to achieve the sub-pixel position in the image. The calibrated camera parameters are utilized to calculate the position of the location hole of the fuel assemblies. Experiments verify that the algorithm can online locate the center of location holes on recovered images underwater, and has high measurement precision.
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, which causes imaging distortion. Turbulence severely affects core verification of nuclear fuel assemblies, serial number of which should be identified. With the aim to recover the images from a video sequence severely distorted by turbulence, an image enhancement method is proposed. At first, an image quality assessment metric FSIM is used to select the better quality frames. Next an iterative robust registration algorithm is used to eliminate most geometric deformations and recover the water surface. The temporal mean of the sequence is utilized to overcome the structured turbulence of the waves through the algorithm. Finally, the sparse errors are extracted from the sequence through rank minimization to remove unstructured sparse noise. After image processing, optical character recognition is performed by KNN and CNN, obtaining high recognition rates of 99.33%, 100% respectively. The experimental results show that the suggested method significantly performs better in distorted image restoration and image text recognition on the task of visual inspection of nuclear fuel assemblies.
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.
Phase-only hologram is the way to generate holograms generated by computers. Although the imaging quality is generally acceptable, the edge and line patterns of the reconstructed images are fuzzy. In this paper, we propose two methods which are the image preprocessing of the original images based on edge-preserve to improve the imaging quality. One is to use the Smallest Univalue Segment Assimilating Nucleus (SUSAN) for the extraction of original image edge, and the other one is to employee the Gaussian filter in frequency domain to separate high frequency and low frequency. Numerical reconstructions and optical reconstructions with a phase-only spatial light modulator (SLM) show that these methods can enhance the edge and line patterns of the reconstructed images, and the merits and drawbacks of the imaging quality using two methods are analyzed.
Visual inspection is a common procedure during outages of nuclear power plants. For the underwater visual inspection of the nuclear plant reactor after fuel reloading, the water turbulence generated by nuclear fuel assemblies can seriously degrade the quality of video. Online image restoration is required in order to meet the need of minimizing the duration of visual inspection. The paper proposes a new method to solve the image degradation and to realize online image restoration when visual inspection. First, the image degradation model is founded. In the model that water turbulence weakly satisfies a Laplacian distribution, it is demonstrated in the paper that the geometric distortion can be removed and a corrected image can be recovered. Then the image is partitioned into small patches which have partly overlapping between adjacent areas. Image quality assessment is used to make phases of image patches homomorphism. Image quality index method is used to image quality measurement in practice. Moreover, the phase average patches combine into a new image. At last the wiener filter is used to estimate the image which would have been observed without turbulence. The experimental result shows that the method can well realize restoration of images affected by turbulence and obtain a satisfactory effect, which can help the operator to carry out the visual inspection which underwater camera is used to achieve more accurate operation information of the fuel reloading.