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Updated: Sep 13, 2025

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循环信息化的三轴传感器,用于智能和可持续的制造
Parisa Esmaili1, Luca Martiri1, Parvaneh Esmaili2
1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, I-20133 Milan, Italy.
Sensors (Basel, Switzerland)
|July 30, 2025
概括
这项研究提出了一个新的框架,用于仅使用加速度计数据进行预测性维护. 它有效地检测机器退化,计算成本低,非常适合工业环境.
科学领域:
- 制造业 工程 制造工程
- 信号处理 信号处理
- 机器健康监测 机器健康监测
背景情况:
- 工业4.0和5.0推动了对智能,可持续制造的需求.
- 强大的预测性维护受到运营变化和有限的数据访问的阻碍.
- 现有的方法与不稳定的流程数据分割作斗争,导致误解.
研究的目的:
- 引入一个轻量级,嵌入式兼容的框架,用于健康状况签名提取.
- 为了使预测性维护只使用单轴加速度计数据.
- 解决细分不稳定过程数据的挑战,以便进行准确的诊断.
主要方法:
- 实证模式分解 (EMD) 用于健康状况签名提取.
- 循环同步细分使用加速仪衍生速度和交叉相关性.
- 提取的内在模式函数 (IMFs) 的频域分析.
主要成果:
- 拟议的框架有效地检测微妙的机器退化.
- 该方法显示了低计算足迹,适合嵌入式系统.
- 在现实世界的制造业基准上成功进行评估.
结论:
- 开发的框架在动态加工条件下有效地提取健康状况签名.
- 循环同步细分策略克服了无控制器系统的局限性.
- 该方法适用于嵌入式预测性维护系统的部署,特别是在传统机器上.
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