CAJ | 학술논문

将可拓数据挖掘方法和模式识别技术相结合，用于解决基于大量数据的故障模式识别问题。利用粗糙集理论进行属性约减和权值确定，保证了获得权值的客观性和稳定性。然后用汽车发动机故障诊断的实例验证了模型的可靠性。最后根据基于变换的可拓集分类思想，探讨了故障预防的一种方法。
장가탁수거알굴방법화모식식별기술상결합，용우해결기우대량수거적고장모식식별문제。이용조조집이론진행속성약감화권치학정，보증료획득권치적객관성화은정성。연후용기차발동궤고장진단적실례험증료모형적가고성。최후근거기우변환적가탁집분류사상，탐토료고장예방적일충방법。
The extension data mining methods and pattern recognition technology are combined to solve the problem of fault diagnosis involved with large amounts of data.By taking advantage of the theory of rough set to make attribute reduction and weight value determination, it ensures the objectivity and stabil-ity of weights.Then it verifies the reliability of the model with the example of fault diagnosis of automobile engine.Finally, according to the classification method of extension set based on the transform, this paper presents a method for fault prevention.