基于自适应EEMD的风电机组联轴器松动故障诊断  

Looseness Fault Diagnosis on Coupling of Wind Turbines Based on Adaptive EEMD

作　　者：李国英[1] 王诗彬[2] 陈雪峰[2] LI Guoying;WANG Shibin;CHEN Xuefeng(School of Economics and Management,Xi′an Shiyou University Xi′an,710065,China;The State Key Laboratory for Manufacturing Systems Engineering,Xi′an Jiaotong University Xi′an,710061,China)

机构地区：[1]西安石油大学经济管理学院,西安710065 [2]西安交通大学机械制造系统工程国家重点实验室,西安710061

出　　处：《振动．测试与诊断》2022年第2期292-298,407,408,共9页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(51335006);西安石油大学博士科研启动基金资助项目(134890001)。

摘　　要：联轴器是风电机组高速旋转齿轮箱和发电机之间的唯一机械连接件,针对联轴器松动后存在振动信号微弱、干扰大、故障特征难以识别的难题,提出了一种以协同信噪比(collaborative signal-to-noise ratio index,简称CSNR)为测度指标的自适应集成经验模式分解(ensemble empirical mode decomposition,简称EEMD)故障诊断方法。将该方法应用于数值仿真信号,实现了仿真信号构成分量的准确分离;应用于风场风电机组联轴器的松动故障诊断,有效提取了联轴器松动强噪声微弱信号中的故障特征,验证了该方法在工程实际应用中的有效性和实用性。The coupling is the unique mechanical connection between the high-speed rotating machinery gearbox and the generator in the wind turbine.Looseness and skid faults of coupling directly threaten the stable and reliable operation of wind turbines,and even cause major accidents or damage to other equipments.After coupling loosening,the observed signals are also contaminated by strong background noises and harmonic interferences.The fault characteristics are difficult to identify.To address those problems,adaptive ensemble empirical mode decomposition(EEMD)with the collaborative signal-to-nosisratio(CSNR)index is proposed.The method in this paper is used to analyze the numerical simulation,and components of the simulation signal are separated accurately.This new method is applied to the looseness fault diagnosis on coupling of wind turbines,and the fault characteristics of weak signals under the background of strong noise of looseness are extracted effectively,verifying the effectiveness and practicability of the method in practical engineering applications.

关 键 词：集成经验模式分解 风电机组 故障诊断 振动信号 

分 类 号：TH133.4[机械工程—机械制造及自动化]