一种交叉遗传优化MHW的风电机组微弱特征提取方法

李冠瑾; 刘文艺; 高钦武

doi:10.13433/j.cnki.1003-8728.2017.1018

一种交叉遗传优化MHW的风电机组微弱特征提取方法

doi: 10.13433/j.cnki.1003-8728.2017.1018

1.
江苏师范大学机电学院, 江苏徐州 221116

基金项目:

国家自然科学基金项目（51505202）、江苏省自然科学基金项目（BK20140238）、江苏省青蓝工程项目（2016）、江苏省大学生创新项目（201510320088Y）及江苏省研究生创新工程项目（KYCX17_1588）资助

详细信息

作者简介:
李冠瑾(1993-),硕士研究生,研究方向为风电机组故障诊断,447479806@qq.com

通讯作者:
刘文艺(联系人),副教授,博士,硕士生导师,liuwenyi1984@126.com

计量
- 文章访问数: 176
- HTML全文浏览量: 19
- PDF下载量: 8
- 被引次数: 0
出版历程
- 收稿日期: 2016-06-03
- 刊出日期: 2017-10-05

A Wind Turbine's Weak Feature Extraction Method Using Cross Genetic Optimized MHW

1.
School of Mechatronic Engineering, Jiangsu Normal University, Jiangsu Xuzhou 221116, China

摘要

摘要: 针对变速变载、闪电雷击、雨雪冰雹等恶劣工作环境干扰下风电机组微弱特征的提取困难问题，提出了一种基于交叉遗传优化MHW的微弱特征提取方法。该方法通过变形参数调整对MHW小波形状进行拟合匹配，并通过交叉遗传优化算法对该变形参数进行优化，进而通过连续小波变换提取匹配波形优化的微弱特征。通过风电场风电机组齿轮箱振动数据分析，验证了该方法可以较好地抑制强背景噪声干扰，提取风电机组微弱故障特征。
- 风电机组 /
- 微弱特征提取 /
- 交叉遗传优化方法 /
- Mexican hat小波 /
- 小波变换
Abstract: To overcome the difficulty in extracting the weak features of a wind turbine under poor working conditions such as variable speed and load, lightning and thunder strike, sleet and hail, etc, this paper proposed a novel wind turbine's weak feature extraction method based on cross genetic optimized Mexican hat wavelet (MHW) method. This method uses deformation parameters to optimize the MHW shape. Then the cross genetic optimization algorithm is introduced to optimize the deformation parameters. The matching shape is used to do the continuous wavelet transform to extract the weak features. The analysis of the vibration signal of the gearbox of the wind turbine on a wind farm proves that the proposed method can not only suppress the background noise interruption but also effectively extract the wind turbine's weak features.
- wind turbine /
- feature extraction /
- cross genetic algorithm /
- optimization method /
- mexican hat wavelet

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参考文献(15)

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