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预测和优化方法用于船舶建筑中组件的接质量
Jinfeng Liu1, Yifa Cheng2, Xuwen Jing3
1Jiangsu University of Science and Technology, Zhenjiang, 212100, Jiangsu, China. liujinfeng@just.edu.cn.
Scientific reports
|April 23, 2024
概括
本研究介绍了一种用于造船的数据驱动接质量预测方法,增强智能接控制. 这种新的方法实现了90%以上的准确性,提高了接过程的效率和可预测性.
科学领域:
- 工业工程 工业工程 工业工程
- 材料科学 材料科学 材料科学
- 制造业 制造技术 制造技术
背景情况:
- 接在造船中至关重要,占工作负载的70%和成本的40%.
- 目前的接质量预测方法缺乏智能制造的准确性和及时性.
- 船舶组装接工艺需要提高质量控制以提高效率和可预测性.
研究的目的:
- 开发一种基于数据和模型的方法,用于预测船舶建造中的接质量.
- 解决现有方法的局限性,重点关注效率,及时性和可预测性.
- 通过准确的质量预测来增强智能接控制.
主要方法:
- 对接质量影响因素和工艺参数相关性的分析.
- 建立数据收集架构,并减少监控的特征维度.
- 使用自适应模拟化,粒子群优化和反向传播神经网络开发一个融合预测模型.
主要成果:
- 确定了关键影响因素,并确定了工艺参数与接质量之间的相关性.
- 实施了强大的数据收集和监控系统.
- 在74个板接实验中实现了超过90%的预测准确度.
结论:
- 拟议的数据驱动方法显著提高了接质量预测的准确性和及时性.
- 融合优化和神经网络模型有效地增强了船舶建造中的智能接控制.
- 这种方法为复杂的工业接过程中的动态质量控制提供了可靠的解决方案.
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