舰船电子工程
艦船電子工程
함선전자공정
SHIP ELECTRONIC ENGINEERING
2012年
6期
118-120
,共3页
装备故障诊断%BP神经网络%基于案例推理%故障诊断模型
裝備故障診斷%BP神經網絡%基于案例推理%故障診斷模型
장비고장진단%BP신경망락%기우안례추리%고장진단모형
{ault diagnosis of equipment%BP neural network%CBR (case-based reasoning)%fault diagnosis model
分析了BP神经网络和基于案例推理（CBR）在故障诊断领域应用中的优点、局限性和互补性，设计了二者相结合的装备故障诊断模型，通过某型装备的故障诊断实例，验证了该算法的有效性。
分析瞭BP神經網絡和基于案例推理（CBR）在故障診斷領域應用中的優點、跼限性和互補性，設計瞭二者相結閤的裝備故障診斷模型，通過某型裝備的故障診斷實例，驗證瞭該算法的有效性。
분석료BP신경망락화기우안례추리（CBR）재고장진단영역응용중적우점、국한성화호보성，설계료이자상결합적장비고장진단모형，통과모형장비적고장진단실례，험증료해산법적유효성。
The characteristics and complementarities of BP neural network and case-based reasoning （CBR） are analyzed in this paper. According to that, a fault diagnosis model for equipment is designed based on the combination of BP neural network and CBR. The validity of the scheme has been attested through a fault instance of equipment.
