风力发电机高速旋转齿轮箱轴承变速故障信号检测研究
Research on Variable Speed Fault Detection of High Speed Rotating Gearbox Bearings in Wind Turbines
王韦智1
作者信息
- 1. 大唐山西新能源公司,山西太原 030000
- 折叠
摘要
高速运转会导致轴承产生大量的振动和噪声,使得故障信号与背景噪声相混合,难以准确检测,一旦出现轴承变速故障将会威胁风力发电机的正常运行.为解决这一问题,提出风力发电机高速旋转齿轮箱轴承变速故障信号检测方法.通过小波阈值和经验模态分解方法,对采集到的风电机高速旋转齿轮箱轴承振动信号去噪处理;基于奇异值分解方法,提取风电机高速旋转齿轮箱轴承振动信号特征向量;通过灰狼算法-支持向量机模型,实现对其轴承变速故障检测.实验结果表明,所提方法的风力发电机高速旋转齿轮箱轴承变速故障检测的准确率高.
Abstract
High speed operation can cause a large amount of vibration and noise in the bearings,making the fault signal mixed with background noise,making it difficult to accurately detect.Once a bearing speed change fault occurs,it will threaten the normal operation of wind turbines.In order to solve this problem,the detection method of variable speed faults in the bearings of the high-speed rotating gearbox of wind turbines is proposed.By using wavelet threshold and empirical mode decomposition methods,the collected vibration signals of high-speed rotating gearbox bearings of wind turbines are denoised;based on Singular value decomposition method,the eigenvector of bearing vibration signal of high-speed rotating gearbox of wind turbine is extracted;by using the grey wolf algorithm support vector machine model,the bearing vari-able speed fault detection is achieved.The experimental results show that the proposed method has a high accuracy in detecting variable speed faults of bearings in high-speed rotating gearbox of wind turbines.
关键词
小波阈值/支持向量机/灰狼算法/变速故障/风力发电机Key words
wavelet threshold/support vector machine/grey wolf algorithm/variable speed fault/wind turbines引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据