| 摘要: |
| 近年来管道内腐蚀引起的安全事故频繁发生，现在主流的修复材料是只用一种或两种刚性粒子进行改性的环氧树脂， 在应对复杂管内环境时经常会在硬度和疏水性方面表现出不足，从而易导致二次事故的发生。为提升修复材料的硬度和疏水性且为不同环境提供最合适的材料配比，设计一种用于管道内修复的新型刚性纳米粒子改性环氧树脂修复涂层。这种涂层以石墨烯改性双酚 A 型环氧树脂为基材，加入不同比例的纳米 Al2O3、纳米 TiO2、纳米 SiO2，通过超声波分散处理进行制备。 通过正交试验法设计试验方案，分别对涂层的 SEM 形貌、水接触角和硬度进行测试，建立关于接触角和硬度的多因素灰色模型，采用遗传算法获取涂层材料的最佳配比。试验结果表明，用灰色模型可以准确地建立涂层性能与刚性粒子之间的关系， 该涂层最佳配比可以有效提高石墨烯改性双酚 A 型环氧树脂的硬度和疏水性，且平均误差在 4%以内，可为管内修复材料的制备提供基础。 |
| 关键词: 管道内防腐 环氧树脂 纳米改性 灰色模型 遗传算法 |
| DOI：10.11933/j.issn.1007?9289.20211120001 |
| 分类号:TQ323；TB332 |
| 基金项目: |
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| Design of Pipeline Repair Coating Based on Multi-factor Grey Model and Genetic Algorithm |
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YAN Zhouyu, ZHAO Hong, DONG Xiaoxiao
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College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249 , China
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| Abstract: |
| Accidents brought on by pipeline corrosion have been common in recent years. The number of pipeline failure accidents caused by external factors has decreased annually, and the proportion of pipeline failures caused by corrosion has been increasing. Therefore, reducing or avoiding the internal corrosion of oil pipelines is an urgent problem that must be solved. Currently, the mainstream repair material is epoxy resin modified with only one or two rigid particles, which often exhibits insufficient hardness and hydrophobicity when dealing with a complex tube environment and can easily lead to the occurrence of secondary accidents. To improve the hardness and hydrophobicity of the repair materials and provide the most suitable material ratio for different environments, a new rigid nanomodified epoxy resin repair coating was designed for in-pipe repairs. The coating is based on a graphene-modified bisphenol A epoxy resin. Using the orthogonal experimental design technique, nanopowders with different proportions of nano-Al2O3, nano-TiO2, and nano-SiO2 were divided into 17 experimental groups, and the nanopowders from each group were combined with the same amount of unmodified epoxy resin. Rigid nanoparticles of different proportions were evenly dispersed in epoxy resin using multiple ultrasonic dispersions, and intermolecular fastening was carried out using a coupling agent. After filtering, drying, and curing, 17 new repair coatings with uniform densities were obtained. In the theoretical section, the grey prediction model is used to generate the known data series, valuable information is extracted by modeling, and a mathematical model is established. In this study, a multi-factor grey model was used to simulate and fit the data. A modeling method was adopted. The whitening equation was used to describe the law and form a response function to obtain the predicted results, thereby providing theoretical support for the multimaterial fusion experiments. In the experimental part, the nanopowders from each of the 17 experimental groups designed by the orthogonal test method were tested by SEM for morphology, water contact angle, and hardness, and the dispersion of nanorigid particles was observed by SEM electron scanning microscope. Hydrophobicity was determined using water contact angle data generated by a water contact angle measuring instrument. The hardness data were obtained using a hardness meter by attaching a test coating to the pipe. A multi-factor gray model of the contact angle and hardness was established, and the optimal ratio of the coating materials was obtained using a genetic algorithm. A multi-factor grey prediction model was established based on the water contact angle and hardness data, which were processed using a genetic algorithm. For the hardness value and contact angle of the 17 experimental groups, the optimal parameters were obtained by constantly calculating the fitness function through the selection, crossover, and optimization operations of the experimental data and the combination of output parameters. The optimal coating ratio was determined using the adaptive value (hardness + contact Angle hardness), and the absolute value of the adaptive value obtained (hardness: 49.834 N / mm2 , contact angle: 97.7°) was 147.534. The adaptive value of the pure epoxy resin without rigid particles was 117.5 (hardness: 31.6 N / mm2 ). The contact angle was 85.9°, the optimal ratio for SiO2∶Al2O3∶TiO2 0.146∶4.849∶0.006. The experimental results show that the gray model can accurately establish the relationship between the coating properties and rigid particles. The optimal coating ratio increased the hardness and hydrophobicity of graphene-modified bisphenol A epoxy resin by 60% and 23%, respectively, with an average error of less than 4%. The relationship between the nanorigid particles and coating properties can be used as a theoretical basis for the configuration of different coatings in different working environments. |
| Key words: anti-corrosion in pipeline epoxy resin nano-modification grey model genetic algorithm |
