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Study of on-line temperature monitoring system for hull welding based on Xgboost-PSO

机译:基于Xgboost-PSO的船体焊接温度在线监测系统的研究

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Welding is a very complicated process in ship manufacturing engineering. Lack of temperature control will lead to various defects in welding. Therefore, temperature monitoring during welding is of great significance to the quality of ship welding. This research is based on the temperature data collected by thermocouples, and then communicates with the host computer through Wi-Fi. The machine learning algorithm Xgboost is used to realize the non-linear correction of thermocouples and the cold-end compensation in the host computer, and the particle swarm optimization (PSO) algorithm is used to construct dynamic compensator to reduce dynamic error. Finally, the on-line monitoring of welding temperature is realized in the form of host computer software.
机译:焊接是船舶制造工程中非常复杂的过程。缺乏温度控制将导致焊接中的各种缺陷。因此,焊接过程中的温度监控对船舶焊接质量具有重要意义。这项研究基于热电偶收集的温度数据,然后通过Wi-Fi与主机进行通信。机器学习算法Xgboost用于在主机中实现热电偶的非线性校正和冷端补偿,而粒子群优化算法(PSO)用于构造动态补偿器以减少动态误差。最后,通过上位机软件的形式实现对焊接温度的在线监测。

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