在不同负载条件下的旋转机器中基于振动检测错位的协同集成方法
Sylwester Szewczyk1,2, Roman Barczewski3, Wiesław J Staszewski1
1AGH University of Krakow, Faculty of Mechanical Engineering and Robotics, Department of Robotics and Mechatronics, al. Mickiewicza 30, 30-059 Krakow, Poland.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
这项研究引入了一种新的振动分析方法,使用协同集成可靠地检测旋转机械的轴不对齐,即使在负载变化下. 该技术通过通过信号静止和协同集成残留物识别故障及其严重程度来增强状态监测.
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:
- 轴不对齐是旋转机械的常见问题,对传统的基于振动的诊断技术构成挑战,特别是在可变的操作负载下.
- 当前的方法在负载条件波动时难以可靠地检测失调,需要先进的诊断框架.
研究的目的:
- 开发和验证一种新的基于振动的框架,用于检测旋转机械中的轴不对齐.
- 通过使用协同集成分析,解决在不同负载条件下可靠检测失调的挑战.
主要方法:
- 采用了三阶段方法,将增强的迪基-富勒 (ADF) 测试与协同集成分析结合起来.
- 该方法分析原始振动信号的静态性,对时间序列进行协同集成,并对后协同集成数据的静态性进行重新评估.
- 在各种负载下,在健康和不对齐状态下,在配备了电机,变速箱和液压的试验平台上进行了实验验证.
主要成果:
- 拟议的基于协同整合的框架成功检测到轴不对齐,尽管负载条件的变化.
- 该方法在识别错位的严重程度方面表现出有效性.
- 同集成过程中的残留物对损伤具有很高的敏感性,对于状态监测非常有价值.
结论:
- 开发的框架为在动态负载条件下检测旋转机械轴不对齐提供了强大的解决方案.
- 同集成分析及其残留物为基于振动的先进状态监测和故障诊断提供了有效的功能.
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