基于一种高级差别函数约简算法的故障诊断分析

Guang-yi Zhang, Yan-qin Su, Shan Gao
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引用次数: 0

摘要

粗糙集理论能有效、正确地剔除故障诊断中冗余和不精确的信息,提高了实时性,有利于将事后、常规的装备后勤保障转变为实时后勤保障。因此,研究基于粗糙集理论的设备故障诊断具有重要意义。针对常见的基于可辨函数的属性约简算法的不足,将一种先进的基于可辨函数的属性约简算法应用于某航空无线电设备的故障诊断。结果表明,该算法不仅诊断有效、准确,而且节省了大量时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Fault Diagnosis Based on One Advanced Discernibility Function Reduction Algorithm
Rough sets theory can eliminate the redundant and imprecise information effectively and correctly in fault diagnosis, which improve the real time and has much advantage of transforming afterwards and regular equipment logistics support to real-time logistics support. So the research on equipment fault diagnosis based on rough sets theory has much signification. The paper applies one advanced reduction algorithm based on discernibility function to some aero radio equipment's fault diagnosis according to the deficiency of familiar attribution reduction algorithm based on discernibility function. The results show the algorithm can not only diagnose effectively and correctly but save much time.
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