The explosive growth of electronic devices brings a soaring demand for rapid electromagnetic compatibility (EMC) diagnosis. However, there is a significant learning curve for the electrical engineers to apply EMC knowledge. In this article, an efficient EMC diagnosis and management methodology was proposed, which provided a fast way for EMC analysis in seconds other than traditional simulation or calculation. The approach organized the EMC knowledges as knowledge graph composed by the interference/sensitive units, and mathematical set rules. The optimized graph structure is in form of rule, maxterm, basic unit, and entity layers. Based on the condensed relationships, it achieved high searching efficiency and graph expansibility. To facilitate the information retrieval from the knowledge graph, the interference/sensitive units and related parameters were acquired from interactive sessions, in which long short-term memory method was used to extract entities. The EMC specialized corpora were fed in training to enhance the accuracy of inference. Finally, the EMC diagnosis and management reports were automatically generated by knowledge graph searching application. The proposed method improved the calculation efficiency by three times. The storage of relationships and attributes of nodes was reduced by 76% and 60.7%. The identification accuracy was enhanced from 77.7% to 99.5%. The presented method is practically useful for EMC design in crosstalk analysis, radiated, and conducted interference diagnoses.

中文翻译：

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利用集体知识图谱和机器学习进行智能电磁兼容诊断和管理


电子设备的爆炸式增长带来了快速电磁兼容性（EMC）诊断的需求激增。然而，电气工程师应用 EMC 知识有一个重要的学习曲线。本文提出了一种高效的EMC诊断和管理方法，为传统仿真或计算之外的秒级EMC分析提供了一种快速方法。该方法将EMC知识组织为由干扰/敏感单元和数学规则集组成的知识图。优化后的图结构采用规则、最大项、基本单元、实体层的形式。基于压缩关系，实现了较高的搜索效率和图的可扩展性。为了便于从知识图谱中进行信息检索，从交互会话中获取干扰/敏感单元和相关参数，其中使用长短期记忆方法来提取实体。 EMC专业语料库被用于训练，以提高推理的准确性。最后，通过知识图谱搜索应用程序自动生成EMC诊断和管理报告。所提出的方法将计算效率提高了三倍。节点关系和属性存储量分别减少76%和60.7%。识别准确率从77.7%提高到99.5%。所提出的方法对于串扰分析、辐射和传导干扰诊断中的 EMC 设计非常有用。