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基于电磁逆问题求解的开关电弧形态重构方法研究 被引量:8

Research on Spatial Morphology Reconstruction of Switching Electric Arc Based on Solution to the Inverse Electromagnetic Problem
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摘要 对电弧的空间形态及其运动特性的测量和分析,有助于揭示电弧从产生、发展到熄灭的物理过程中的相关规律,是研究并提高开关电器产品性能的有效途径之一。研究并提出了一种基于电磁逆问题求解来重构开关电弧实际形态的方法。依据开关电弧周围空间磁场分布,利用数学反演的方法获得电弧形态,是一种典型的连续场域逆问题。为了克服该类问题的不适定性,针对低压开关电器的结构和工作特点,结合空气介质开关电弧等离子体的物理特性,建立了电弧形态重构逆问题的数学模型;对正问题进行了深入分析,从而在物理上增加了一定的先验信息;基于现代智能优化方法,为逆问题的求解设计了快速而稳定的算法。实例分析表明,提出的方法能够实现开关电弧空间形态的有效重构,为开关电弧测试技术的研究和发展提供了有益的补充。 The measurement and" analysis for the spatial morphology and dynamic behavior of the electric arc is conductive to revealing the relevant laws in the whole physical process from arc ignition, expansion to extinction, which is an effective way to improve the performance of the switch apparatus, In the paper, an approach to reconstituting the electric arc spatial morphology based on the inverse electromagnetic problem solving is studied and presented. Obtaining the arc pattern through inversing the magnetic field data around arc is a typical inverse problem of continuous field. To deal with the iU-posedness of the problem, in this paper, the mathematic model of inverse problem of arc morphology reconstruction was established based on the comprehensive consideration of the structure and characteristics of low-voltage switching devices, and the physical properties of the switching arc plasma in air; the priori information in physics was increased through analyzing the forward problems deeply; an efficient and stable algorithm was designed based on the modem intelligent optimization method. Results of case analysis show that the proposed method can achieve the effective reconstruction of the spatial form of switching arc. It is also able to provide a useful supplement to the research and development of the testing technology of switching arc.
出处 《中国电机工程学报》 EI CSCD 北大核心 2013年第12期159-166,199,共8页 Proceedings of the CSEE
基金 中央高校基本科研业务费专项资金资助项目(XJJ2011019)~~
关键词 电磁逆问题 开关电弧形态 重构 智能优化 inverse electromagnetic problem switching electric arc morphology reconstruction intelligent optimization
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