| 引用本文: | 张廼龙,刘洋,高嵩,陈杰,荆宇航.盘型悬式绝缘子瓷件的应力分析和结构优化[J].哈尔滨工业大学学报,2021,53(2):98.DOI:10.11918/202008006 |
| ZHANG Nailong,LIU Yang,GAO Song,CHEN Jie,JING Yuhang.Stress analysis and structural optimization of porcelain for disc suspension insulator[J].Journal of Harbin Institute of Technology,2021,53(2):98.DOI:10.11918/202008006 |
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| 摘要: |
| 为减少盘型悬式绝缘子断裂事故的发生,研究了绝缘子瓷件的应力水平以及结构的优化.建立盘型悬式绝缘子的有限元模型以计算绝缘子受拉伸作用下的应力分布特性,以及在不同拉力方向的作用下,绝缘子瓷件上的应力情况.采用有限元和机器学习相结合的方法对绝缘子的结构进行优化.结果表明:在拉力作用下,瓷件与水泥胶合剂的接触面部分分离,导致绝缘子瓷件中部壁面的应力水平较高,拉力方向与绝缘子轴线的夹角越大,瓷件上的应力水平越高.在有限元计算的基础上,利用机器学习方法,对绝缘子的结构参数进行优化设计,得到了最优结构参数,最优结构较原始结构应力水平降低了30%,并对最优结构进行有限元计算验证,发现两者误差率仅为0.644%,结果可靠且优化效果显著.在绝缘子的胶装过程中,应增强胶装强度,在绝缘子的安装中,应尽量减小绝缘子的受拉方向与轴线的夹角,以有效增加绝缘子的工作寿命.结构优化得到的最优参数可以为结构设计提供理论指导和技术支持. |
| 关键词: 盘型悬式绝缘子 有限元 应力集中 机器学习 结构优化 |
| DOI：10.11918/202008006 |
| 分类号:TB321 |
| 文献标识码:A |
| 基金项目:国网公司科技项目(5200-201918084A-0-0-00) |
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| Stress analysis and structural optimization of porcelain for disc suspension insulator |
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ZHANG Nailong1,LIU Yang1,GAO Song1,CHEN Jie1,JING Yuhang2
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(1.Research Institute, State Grid Jiangsu Electric Power Co. Ltd., Nanjing 211103, China; 2.Department of Astronautical Science and Mechanics, Harbin Institute of Technology, Harbin 150001, China)
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| Abstract: |
| In order to reduce the fracture accident of disc suspension insulators, the stress level of porcelain and the optimization of its structure were studied. The finite element model of the disc suspension insulator was established to investigate the stress distribution characteristics of the insulator under tension, and the stress on the porcelain under different tension directions was analyzed. The insulator structure was optimized based on finite element method and machine learning method. Results show that under the action of tension, the contact surface between porcelain and cement was partially separated, resulting in higher stress level on the middle wall of porcelain. The greater the angle between the tension direction and the axis of insulator was, the higher the stress level on the porcelain became. On the basis of finite element calculation, the machine learning method was adopted to optimize the structural parameters of the insulator, and the optimal structural parameters were obtained. The stress level of the optimal structure was reduced by 30% compared with that of the original structure. The finite element calculation of the optimal structure shows that the error rate was only 0.644%, indicating that the result is reliable and the optimization effect is significant. Therefore, in the process of cementing of insulator, the cementing strength should be enhanced. In the installation of insulator, the angle between the tension direction of the insulator and the axis should be minimized so as to effectively increase the working life of the insulator. The optimal parameters obtained by structural optimization can provide theoretical guidance and technical support for structural design. |
| Key words: disc suspension insulator finite element method stress concentration machine learning structural optimization |
