基于文本挖掘的飞机故障分类与检索模型研究

Xingxing Xu, Shenghan Zhou, Yiyong Xiao, Wenbing Chang, Fajie Wei, Ming Yang
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引用次数: 1

摘要

随着信息技术的发展,大量的设备管理系统在航空领域得到了应用。这些系统通常具有故障管理功能。故障发生后,要及时输入设备故障的文字信息,如“组合开关损坏”、“进气管破裂”等故障现象。此外,相应的故障原因和处理方法也需要进行完整的记录。因此,随着系统的使用,会产生大量的设备故障文本。如果能够充分利用这些非结构化数据,通过文本挖掘发现其中的知识,对故障分析和维修决策具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text Mining-based Research on Aircraft Faults Classification and Retrieval Model
With the development of information technology, a large number of equipment management systems have been used in the aviation field. These systems generally have failure management functions. After the failure occurs, it is necessary to input the text information of equipment failure in time, such as “combination switch damage”, “intake pipe rupture” and other failure phenomena. In addition, the corresponding failure causes and troubleshooting methods also need to be fully recorded. Therefore, as the system has been used, a large number of equipment failure texts will be generated. If we can make full use of these unstructured data and discover the knowledge through text mining, it will be of great significance to fault analysis and maintenance decision-making.
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