通过改进的叶片尖定时技术来确定同步振动的振动属性和可靠的频率估计,而无需一次革命传感器
Marios Sasakaros1, Luca Mann1, Markus Schafferus1
1Institute of Power Plant Technology, Steam and Gas Turbines, RWTH Aachen University, 52062 Aachen, Germany.
Sensors (Basel, Switzerland)
|January 25, 2025
概括
这项研究引入了一种改进的刀片尖端定时 (BTT) 技术,可以准确地监测驱动器振动,而无需一次革命 (OPR) 传感器. 这种方法提高了准确性,并在空间有限的应用中实现了BTT.
科学领域:
- 机械工程 机械工程
- 振动分析 振动分析
- 状态监控 状态监控
背景情况:
- 来自周期性激发的同步振动可以降低螺旋寿命.
- 叶片尖端定时 (BTT) 提供了对螺旋叶片的非侵入性监控.
- 传统的BTT依赖于不可靠的一次革命 (OPR) 传感器,并且由于采样不足而遭受信号异化,往往需要额外的应变量表 (SG) 测量.
研究的目的:
- 开发和验证改进的BTT技术,用于准确的同步振动分析.
- 为了消除在BTT系统中对OPR传感器的需求.
- 为了使可靠的振动频率评估从未采样的BTT数据没有SG测量.
主要方法:
- 刀片识别使用独特的制造公差.
- 基于螺旋的圆周位置进行的新型叶片偏移计算,并考虑转速变化.
- 改进的多样采样方法与非统一的快速富里埃变换用于振动频率估计.
主要成果:
- 精确的OPR-free叶片偏移计算,不受轴震动的影响.
- 从采样不足的BTT信号中可靠地估计多个振动频率,消除了对SG测量的需求.
- 根据SG测量和使用实验性轮增压器数据在实际操作条件下的商业BTT系统进行验证.
结论:
- 拟议的BTT技术提高了准确性并扩大了适用性,特别是在空间有限的系统中.
- 可靠的振动属性测定可以在没有OPR传感器或SG测量的情况下实现.
- 这些方法证明了在旋转机械的状态监测方面具有重要的工业适用性.
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