基于数字双胞胎的减速器故障诊断
Weimin Liu1, Bin Han1, Aiyun Zheng1
1College of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China.
Sensors (Basel, Switzerland)
|April 27, 2024
概括
一种新的数字双胞胎方法提高了工业减速机故障诊断的准确性,达到99.5%的整体精度. 这种方法克服了改善机械健康监测的传统模型的局限性.
科学领域:
- 机械工程 机械工程
- 计算机科学 计算机科学
- 工业物联网工业物联网工业物联网
背景情况:
- 现有的故障诊断模型与单个故障类型,低相似性和糟糕的可视化作斗争.
- 需要先进的故障诊断方法,提供更高的准确性和更好的状态监控.
- 数字双胞胎技术为克服这些局限性提供了一个有希望的途径.
研究的目的:
- 提出一种新的基于数字双胞胎的故障诊断方法.
- 解决现有的故障诊断建模技术的缺陷.
- 提高故障诊断中状态监控的准确性和视觉表示性.
主要方法:
- 建立了一个故障诊断测试平台,用于在恒定和可变速度下分析故障.
- 将故障数据集成到Unity3D平台中,用于在线诊断和实时更新.
- 进行了数字双胞胎模型的工业测试,并将其性能与其他先进方法进行了比较.
主要成果:
- 拟议的数字双胞胎方法在整个减速器中实现了99.5%的整体精度.
- 这种准确性远远超过了专注于单个组件的方法 (例如,轴承93.5%,轮轴96.3%,外92.6%).
- 数字双胞胎模型在工业环境中展示了高精度和应用可行性.
结论:
- 基于数字双胞胎的故障诊断方法与传统方法相比,提供了更高的准确性和有效性.
- 这项技术为在线,实时故障诊断和状态监控提供了强大的解决方案.
- 拟议的方法对工业应用具有很高的可行性,提高了机器的可靠性.
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