基于Copula-vines的电机线圈发热故障状态监测研究

Research on Motor Coil Heating Fault Condition Monitoring Based on Copula-vines

中文关键词: 小型交流电机  多参数  Copula-vines  故障诊断预警

英文关键词: miniature ac motor  multiple parameters  copula-vines  early fault warning

中文摘要:

      小型交流电机作为现代工业化的重要基础设备之一,实现对其整体运行状态的实时监测显得尤其重要。通过对电机现有基本多元监测参数构建联合分布的密度函数作为正常运行的状态标准,利用藤理论将多元参数分组分解为两两相关结构,构建最优二元联合分布的Copula函数模型实现对电机状态准确描述。以相对熵作为评价监测数据与正常数据的概率密度的分布差异。实验表明,基于多元Copula函数构建的小型交流电机状态参数联合分布的概率密度函数作为故障特征值,能在电机线圈发热初期及时预警。系统实现了基于现有监测参数对电机故障状态实现快速预识别,从而避免电机运行事故的发生。

英文摘要:

      Miniature AC motor is an important basis equipment in modern industry, and the real-time monitoring of its overall operational parameters is particularly important. The joint distribution density function based on the monitored parameters of the electric motor is utilized to evaluate its operation state. The Vine-theory is applied to decompose multiple parameters into two groups in correlated structure and the Copula function model is established to achieve the accurate operation status of the electric motor. The relative entropy is selected as the evaluation parameter for the probability density distribution between the monitoring data and normal data. Experimental results show that the probability density function, which is established based on the miniature AC motor operation parameters, is identifiable in indicating the failure flag of the operation for the electric motor. The system is proved could achieve rapid identification for the failure operation parameters of the motor and avoid operation accidents.