摘要
通过构建风力发电机油液监测理化指标及光谱元素的灰色自关联矩阵,对运动黏度(40℃)、总酸值、水分、污染度NAS等级、铁、硅、磷元素等指标进行关联性分析。研究表明,风机齿轮油在使用过程中的总酸值与运动黏度变化同为油品氧化变质直接引起,灰色关联性最强;水分的存在会使磷系添加剂水解,同时使总酸值增加;未被过滤掉的氧化产物同时影响污染度NAS等级和酸值;铁元素含量及总酸值因相互影响灰色关联性也较强;硅元素对铁元素变化影响最大。灰色自关联矩阵为风机齿轮箱润滑故障诊断分析提供理论支持。
The grey self-incidence matrix of physicochemical index and elements content of spectrum analysis in oil mo- nitoring of wind turbine was constructed to analyze the correlation of kinematic viscosity at 40 ℃ , total acid number,water content,pollution NAS grade,iron, silicon and phosphorus elements.The research shows that the change of total acid num- ber and kinematic viscosity of the gear oil of wind turbine is directly caused by oxidation deterioration, and they possess the strongest grey correlation.The hydrolysis of phosphorus additives is accelerated by water, and the acid number is enhanced. The oxidation products unfiltered affect the pollution grade and acid number of gear oil.The grey correlation of iron element content and total acid number is also strong due to their interaction.Effect of silicon element on iron element content in oil is the most because of wear.Self-incidence matrix constructed can provide the theoretical basis for lubricating fault diagno- sis of wind turbine.
出处
《润滑与密封》
CAS
CSCD
北大核心
2016年第12期112-116,共5页
Lubrication Engineering
基金
国家科技支撑计划项目(2015BAA06B02)
关键词
油液分析
灰色关联分析
故障诊断
自关联矩阵
oil analysis
grey correlation analysis
fault diagnosis
self-incidence matrix
