摘要
故障预测及健康管理(prognostics and health management,PHM)对于保障系统的安全可靠具有重要作用。随着电力电子装置在各领域的应用愈发广泛,急需研究电力电子装置的PHM技术。特征参数提取是PHM技术的基础,该文首先简要说明了电力电子电路特征参数提取的研究现状。然后针对基于混杂系统模型的电力电子电路参数辨识方法中,存在较多影响实际辨识精度的非理想因素这一关键问题,以电路中目标器件为建模对象建立线性模型,提出了一种通用性较好的Buck型变换器参数提取方法,并结合Matlab仿真分析了该方法的性能,包括收敛速度以及辨识精度。最后进行实验验证,实验结果表明,该方法的参数辨识精度可达95%以上,验证了这一方法的有效性。
The prognostics and health management （PHM） have very important significance for ensuring the security of systems. The widely use of power electronic equipment is now making the PHM technology for power electronics become more important. The feature parameter extraction plays a key role in realizing PHM of power electronic circuits and current research work concerning is described in brief. The accuracy of conventional parameter identification of power electronic circuits based on hybrid system models suffers from too many non-ideal factors in practice. In this regard, a more widely used parameter extracting method for the Buck converters is proposed by establishing a linear model containing target components of the circuit. In addition, the performance including convergence speed and identification precision of the proposed method is analyzed with the assist of Matlab. At last, experiment results show that the parameter identification accuracy is over 95%, by which the effectiveness of the method is verified.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2016年第20期5624-5631,5739,共8页
Proceedings of the CSEE
基金
国家自然科学基金项目(51377079)
中央高校基本科研业务费专项基金项目(kfjj20150307)~~
关键词
BUCK型变换器
特征参数提取
参数辨识
混杂系统
线性模型
故障预测及健康管理
Buck converters
feature parameter extraction
parameter identification
hybrid system
linear model
prognostics and health management （PHM）
