一个物理导向的双传感器框架用于轴承故障诊断在PMDC电机驱动器中
Tae-Seong Sim1, Nnamdi Chukwunweike Aronwora1, Jang-Wook Hur1
1Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering), Kumoh National Institute of Technology, 61 Daehak-ro, Gumi-si 39177, Gyeonsangbuk-do, Republic of Korea.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
本研究介绍了交叉参考能量注意 (CREA),这是一种新的双传感器方法,用于诊断永久磁直流 (PMDC) 电机中的轴承故障. 在可变扭矩条件下,CREA显著提高了故障检测准确度.
科学领域:
- 机械工程 机械工程
- 状态监控 状态监控
- 信号处理 信号处理
背景情况:
- 滚动元件轴承故障是旋转机器机械故障的主要原因之一.
- 永久磁直流 (PMDC) 电机的基于振动的诊断受到可变扭矩的挑战,导致负载依赖的激发和通道干扰.
- 这些干扰会影响振幅测量,并降低用于故障诊断的传统统计特征的可靠性.
研究的目的:
- 提出一个物理导向的双传感器特征框架,交叉参考能量注意 (CREA),用于在PMDC电机中增强三类轴承状态诊断.
- 开发一种方法,以隔离与故障相关的信息,同时抑制发动机产生的干扰.
- 在可变扭矩条件下验证CREA与传统方法的有效性.
主要方法:
- 实施CREA,一个双传感器框架,利用硬件不可知,经验选择的中频载波带来隔离故障信号.
- 整合一个空间分离的参考传感器来评估信号传输的一致性,并抑制当地的电机噪声.
- 在PMDC电机动力表上进行实验验证,该动力表有种子轴承缺陷,采用GroupKFold交叉验证和每运行正常化.
主要成果:
- 在测试条件下,传统的发动机侧基线特征显示精度降低 (0.495 ± 0.110).
- 四个特征的CREA表示实现了显著更高的准确性 (0.999 ± 0.002).
- 废除和SHAP分析证实了载波带能量特征的占主导地位,以及交叉传感器指标的互补作用.
结论:
- CREA有效地隔离了故障特定的振动,并抑制了在可变扭矩下运行的PMDC电机中的噪声.
- 双传感器方法提供了强大的和高度准确的轴承状态诊断,优于传统方法.
- 通过利用结构传输特征,CREA的物理导向设计确保了可靠的状态监控.
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