基于POA优化支持向量回归模型的航天电磁继电器贮存寿命预测  

Prediction of Storage Life of Aerospace Electromagnetic Relay Based on POA Optimization Support Vector Regression Model

作　　者：朱佳淼 王召斌[1] 李久鑫 ZHU Jiamiao;WANG Zhaobin;LI Jiuxin(College of Automation,Jiangsu University of Science and Technology,Zhenjiang 212003,China)

机构地区：[1]江苏科技大学自动化学院,江苏镇江212003

出　　处：《电器与能效管理技术》2023年第8期61-67,共7页Electrical & Energy Management Technology

基　　金：国家自然科基金资助项目(51507074);江苏省研究生实践创新计划项目(SJCX23_2128)。

摘　　要：为了提高航天电磁继电器贮存寿命预测精度,提出了一种基于鹈鹕优化算法(POA)优化支持向量回归(SVR)模型的航天电磁继电器贮存寿命预测方法,以解决SVR模型内核参数选择难的问题。随后基于某型号继电器的加速退化试验所得数据,进行了验证。最后,通过POA-SVR方法与SVR方法和SMA-SVR方法对比,平均相对误差分别下降了24.82%、3.69%,说明所提方法可以有效提高继电器贮存寿命的预测精度。To improve the prediction accuracy of the storage life of aerospace electromagnetic relays,a method based on the pelican optimization algorithm(POA)to optimize the support vector regression(SVR)model for the storage life prediction of aerospace electromagnetic relays is proposed.POA is utilized to optimize SVR model and solve the selection difficulty of kernel parameters in SVR model.Then the performance degradation data obtained from an accelerated degradation test of a certain type of relay is used to validate the proposed method.Finally,compared with the SVR method and SMA-SVR method,the average relative errors decreased by 24.82%and 3.69%,which proves that the proposed method can effectively enhance the prediction accuracy of the relays storage life.

关 键 词：航天电磁继电器 鹈鹕优化算法 支持向量机回归 寿命预测 

分 类 号：TM581.3[电气工程—电器]