基于叶尖定时的风机叶片裂纹故障识别研究
Research on fan blade crack fault identification based on tip timing
盛昌文 1姜永正 1黄磊 2曾立英 2苏邦伟2
作者信息
- 1. 湖南科技大学机械设备健康维护湖南省重点实验室 湘潭 411201
- 2. 湘潭市工矿电传动车辆质量检验中心 湘潭 411201
- 折叠
摘要
风机叶片作为风电机组的关键部件,其裂纹故障尤为常见.裂纹的存在会导致叶片或机组出现损坏.为此,基于叶尖定时原理和分析方法,提出一种风机叶片裂纹故障的识别方法.首先,依据叶尖定时原理,分析叶片在载荷作用下裂纹对叶尖偏移的影响,建立叶尖偏移与叶尖偏移时间之间的数学模型.其次,通过仿真分析叶片在不同状态下叶尖偏移程度,结合不同工况参数与叶尖偏移时间之间的数学模型,识别裂纹特征信号.最后,利用风机模拟试验台实测叶尖信号,结果表明本文所提的识别方法对裂纹的特征信号的成功提取达到了 92%以上,并且能够实时完成裂纹信号的提取和分析,说明此方法能够实现裂纹故障实时识别.
Abstract
Fan blade is a key component of wind turbine,and its crack fault is particularly common.The presence of cracks can cause damage to the blade or unit.Therefore,based on the tip timing principle and analysis method,a method of fan blade crack fault identification is proposed.Firstly,according to the principle of tip timing,the influence of blade crack on tip offset under load is analyzed,and the mathematical model between tip offset and tip offset time is established.Secondly,through the simulation analysis of blade tip offset degree in different states,combined with the mathematical model between different working condition parameters and tip offset time,the crack characteristic signal is identified.Finally,the results show that the recognition method proposed in this paper can successfully extract more than 92% of the characteristic signal of the crack,and can complete the extraction and analysis of the crack signal in real time,indicating that this method can realize the real-time recognition of the crack fault.
关键词
风机叶片/叶尖定时/叶尖偏移/裂纹故障/裂纹识别Key words
fan blade/tip timing/tip offset/crack fault/crack identification引用本文复制引用
基金项目
湖南省自然科学基金(2023JJ60548)
出版年
2024
NETL
NSTL
万方数据