姜伟, 张春雷, 时林林, 贾寒光, 俞鹏飞, 周振威. 基于单/多参数的DC-DC模块电源健康评估技术研究[J]. 华南师范大学学报(自然科学版), 2019, 51(2): 14-20.
引用本文: 姜伟, 张春雷, 时林林, 贾寒光, 俞鹏飞, 周振威. 基于单/多参数的DC-DC模块电源健康评估技术研究[J]. 华南师范大学学报(自然科学版), 2019, 51(2): 14-20.
JIANG Wei, ZHANG Chunlei, SHI Linlin, JIA Hanguang, YU Pengfei, ZHOU Zhenwei. Research on health evaluation model of DC-DC power module based on Mahalanobis distance method[J]. Journal of South China Normal University (Natural Science Edition), 2019, 51(2): 14-20.
Citation: JIANG Wei, ZHANG Chunlei, SHI Linlin, JIA Hanguang, YU Pengfei, ZHOU Zhenwei. Research on health evaluation model of DC-DC power module based on Mahalanobis distance method[J]. Journal of South China Normal University (Natural Science Edition), 2019, 51(2): 14-20.

基于单/多参数的DC-DC模块电源健康评估技术研究

Research on health evaluation model of DC-DC power module based on Mahalanobis distance method

  • 摘要: 随着电子产品的快速发展,系统设备对电源系统的性能以及可靠性提出了更高的要求,将基于状态的维修思想引入电源可靠性保障领域十分必要。实现模块电源基于健康管理的智能维护的首要基础是要准确获得电源的健康状态。针对某两种型号DC-DC模块电源,本文提出了一种基于分布间距离度量的单或多监测参数的健康评估方法。基于DC-DC电源的4个评估参数的历史监测数据,文中采用mRMR特征选择的方式提取出相关敏感退化特征,然后采用基于CV值(置信值)单参数及基于马氏距离多参数的健康评估方法,对某两款28V直流转5V以及28V直流转3.3V直流的 DC-DC模块电源进行健康状态评估,试验分析结果验证了本文提出的评估算法的正确性和实用性。文中提出的电源评估算法对于轻度退化程度以上的电源评估问题具有较高的准确率,该研究成果对DC-DC模块电源的健康评估以及解决电源产品的可靠性保证提供一种切实可行且具有工程化前景的方法。

     

    Abstract: With the rapid development of electronic product technology, the equipment requires higher performance and reliability of power supply, so it is necessary to introduce state-based maintenance into the field of power supply reliability. The key to intelligent maintenance of modular power supply based on health management is to get the health status of power accurately. For two types of DC-DC module power supply, this paper presents a health assessment method of single or multiple monitoring parameters based on the distance between parameter distributions.Based on the historical monitoring data of 4 parameters of the DC-DC power supply, this paper uses the mRMR feature selection method to extract the related sensitive degradation characteristics, and uses the CV value (confidence value) single parameter and the martensitic distance multi parameter health assessment method to evaluate two DC-DC powers with 28VDC to 5VDC and 28VDC to 3.3VDC. The experimental results prove the correctness and practicability of the algorithm proposed in this paper. The algorithm proposed in this paper has higher accuracy for degraded power assessment.The results of this paper provide a practical and engineering method for the health assessment of DC-DC power supply and the reliability assurance of power products.

     

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