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Corrosion Damage Identification and Lifetime Estimation of Ship Parts using Image Processing

机译:基于图像处理的船舶零件腐蚀损伤识别与寿命估算

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Corrosion is a process that leads to early failure of ship parts, high maintenance costs and a shortened service life of the ship, as a whole. Human visual inspection is currently the most widely used method to assess corrosion. In this paper, we propose the use of image processing to determine the extent of corrosion and estimate the time period within which the ship parts have to be replaced. In the case of availability of pre-corrosion images, the histograms of the pre-corrosion and post-corrosion images are compared and their similarity is quantified as the Sum of Squared Distances (SSD) value. Our method then produces a numerical output which signifies the level of corrosion. We then correlate extent of damage and ship part replacement period. In the absence of pre-corrosion images, we classify superpixels in the post-corrosion image as undamaged or damaged with an accuracy of 92 per cent, using Random Forest classifier. We have also evaluated the performance of corrosion prevention measures such as galvanization, painting, etc on different parts of the ship, for example, parts exposed to only air and parts exposed to both saline water and air.
机译:腐蚀是导致整个船舶部件早期失效,高昂维护成本和缩短船舶使用寿命的过程。目视检查是目前评估腐蚀最广泛使用的方法。在本文中,我们建议使用图像处理来确定腐蚀程度并估计必须更换船体部件的时间。在提供腐蚀前图像的情况下,将腐蚀前和腐蚀后图像的直方图进行比较,并将它们的相似性量化为平方和(SSD)值。然后,我们的方法产生一个数值输出,表示腐蚀程度。然后,我们将损坏程度与船舶零件更换期限相关联。在没有腐蚀前图像的情况下,我们使用随机森林分类器将腐蚀后图像中的超像素分类为未损坏或损坏的像素,准确率为92%。我们还评估了在船舶的不同部分(例如仅暴露于空气的部分以及暴露于盐水和空气的部分)的防腐蚀措施(如镀锌,喷漆等)的性能。

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