一个轮的数字双胞胎 根裂的预后
Omri Matania1, Eric Bechhoefer2, Jacob Bortman1
1BGU-PHM Laboratory, Department of Mechanical Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva 8410501, Israel.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
这项研究引入了一个数字双胞胎,用于预测轮根裂的传播,这是工业4.0机械维护的关键挑战. 数字双胞胎准确地估计了物理资产剩余的维护时间.
科学领域:
- 工程 工程师 工程师 工程师
- 计算机科学 计算机科学
- 材料科学 材料科学 材料科学
背景情况:
- 工业4.0强调智能制造和预测性维护.
- 机械维护,特别是轮维护,在预测元件故障方面面临着挑战.
- 轮根裂纹传播是一个关键的故障模式,需要准确的预测.
研究的目的:
- 引入一种新的数字双胞胎,用于预测轮根裂传播.
- 开发用于连续监测和对轮组件剩余使用寿命估计的系统.
- 为解决预测工业环境中轮根裂传播的未解决的问题.
主要方法:
- 开发一个数字双胞胎,整合信号处理和模型装配.
- 持续监测轮根裂纹状况.
- 对实体资产进行维护所需的剩余时间的估计.
主要成果:
- 数字双胞胎成功监控轮根裂状况.
- 能够准确估计剩余的维护时间.
- 在行星轮上的实验验证证明了数字双胞胎在预测故障严重程度和维护需求方面的有效性.
结论:
- 开发的数字双胞胎有效地解决了预测轮根裂传播的挑战.
- 这项技术在工业机械的预测性维护方面取得了重大进展.
- 数字生提供了一种可靠的方法来估计剩余的使用寿命,优化维护计划.
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