电力系统保护与控制2017，Vol.45Issue(11)：43-48,6.DOI:10.7667/PSPC160782
基于多重分形谱和支持向量机的风电机组行星齿轮箱故障诊断与研究
Diagnosis and research of wind turbine planetary gearbox faults based on multifractal spectrum support vector machine (SVM)
摘要
Abstract
The vibration signal of wind turbine is a typical kind of signal with nonstationary and nonlinear properties. The ability of traditional methods to process the kind of signal is limited. In order to solve the shortage of the traditional methods and improve the ability of fault diagnosis, this paper proposes a new method to detect the fault based on the multifractal and support vector machine (SVM). Firstly, the multifractal spectrum of the input signal is calculated through the definition of multifractal. And then the eight fractal characteristics of signal are extracted. Finally, taking the characteristics as the input vector of SVM, it achieves the classification and recognition of normal signal and fault signals of four kinds of sun gears under different rotation speed. The experimental result confirms that the proposed method can effectively extract the characteristics of the planetary gearbox signal, and can raise the fault recognition rate under the condition of different rotational speed.关键词
风电机组/行星齿轮箱/故障检测/多重分形谱/支持向量机Key words
wind turbine/planetary gearbox/fault detection/multifractal spectrum/support vector machine引用本文复制引用
李东东,周文磊,郑晓霞,王浩..基于多重分形谱和支持向量机的风电机组行星齿轮箱故障诊断与研究[J].电力系统保护与控制,2017,45(11):43-48,6.基金项目
国家自然科学基金项目(51507098,51507100) （51507098,51507100）
上海市人才发展基金(201365) （201365）
上海市科委(15YF1404600, 13DZ2251900,10DZ2273400)和上海市"曙光计划"资助(15SG50) This work is supported by National Natural Science Foundation of China (No. 51507098 and No. 51507100), Shanghai Talent Development Fund (No. 201365), Science and Technology Commission of Shanghai (No. 15YF1404600 and No. 13DZ2251900 and No. 10DZ2273400) and Shuguang Program (No. 15SG50). （15YF1404600, 13DZ2251900,10DZ2273400）
