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管内高压智能封堵技术是20世纪90年代由PSI公司发展起来的一项新型封堵技术,卡紧能力是封堵器的关键技术,由锁定锚爪完成。为了更好地设计锁定锚爪,使其与管壁之间能够产生有效的卡紧力,需要对其结构进行优化。利用神经网络高度的非线性映射能力建立了锁定锚爪角度、锁定锚爪连接厚度、锁定锚爪间距、锁定锚爪整体倾角、锁定锚爪曲率半径间的函数关系;利用遗传算法的全局寻优能力求解由该函数作为目标函数的优化问题,从而获得锁定锚爪与管道间接触力最大的几个主要因素的最优搭配。优化结果表明:优化后锚爪与管道间的接触力增加了87.81%,锁定锚爪整体性能显著提高。
High-pressure pipe sealing technology is a new type of sealing technology developed by PSI Company in the 1990s. The clamping capacity is the key technology of the occlusion device, which is completed by the locking anchor. In order to better design the locking fluke to make effective clamping force with the pipe wall, its structure needs to be optimized. Based on the high nonlinear mapping ability of neural network, the relationship between locking anchor angle, locking anchor connecting thickness, locking anchor spacing, locking anchor integral inclination and locking anchor radius is established. By means of genetic algorithm, The ability to solve this function as an objective function optimization problem, so as to obtain the optimal combination of several main factors that have the greatest contact force between the locking fluke and the pipeline. The optimization results show that the contact force between the fluke and the pipe is increased by 87.81% after optimization, and the overall performance of the locking fluke is remarkably improved.